Method to Improve the Linearity of Active Commutating Mixers Using Dynamic Current Injection

A double balanced (DBM) CMOS mixer providing high linearity is presented in this paper. A cross-coupled pair used in the IF stage of the mixer to dynamically inject current into the to mixer provide a high linearity. The proposed DBM was fabricated using a standard 130-nm CMOS process and was tested on-wafer. The double balanced mixer delivers 10 dB conversion gain, 9.5 dBm IIP3, and input P1dB of -2.4 dBm. RF bandwidth of the proposed mixer is 6 GHz, covering 0.5 GHz to 6.5 GHz with IF bandwidth of 300 MHz. RF to IF and LO to IF isolation are also better than 59 dB in the whole frequency band. The circuit uses an area of 0.015 mm2 excluding bonding pads and draw 4.5mW from a 1.2V supply.

Mixing behaviour of side injection of air jets and gaseous fuel jets into the axial flow of tunnel kilns

Otto-von-Guericke-Universität Magdeburg, Fakultät für Verfahrens- und Systemtechnik, Dissertation, 2016

Applied web traffic analysis for numerical encoding of SQL Injection attack features.

SQL Injection Attack (SQLIA) remains a technique used by a computer network intruder to pilfer an organisation’s confidential data. This is done by an intruder re-crafting web form’s input and query strings used in web requests with malicious intent to compromise the security of an organisation’s confidential data stored at the back-end database. The database is the most valuable data source, and thus, intruders are unrelenting in constantly evolving new techniques to bypass the signature’s solutions currently provided in Web Application Firewalls (WAF) to mitigate SQLIA. There is therefore a need for an automated scalable methodology in the pre-processing of SQLIA features fit for a supervised learning model. However, obtaining a ready-made scalable dataset that is feature engineered with numerical attributes dataset items to train Artificial Neural Network (ANN) and Machine Leaning (ML) models is a known issue in applying artificial intelligence to effectively address ever evolving novel SQLIA signatures. This proposed approach applies numerical attributes encoding ontology to encode features (both legitimate web requests and SQLIA) to numerical data items as to extract scalable dataset for input to a supervised learning model in moving towards a ML SQLIA detection and prevention model. In numerical attributes encoding of features, the proposed model explores a hybrid of static and dynamic pattern matching by implementing a Non-Deterministic Finite Automaton (NFA). This combined with proxy and SQL parser Application Programming Interface (API) to intercept and parse web requests in transition to the back-end database. In developing a solution to address SQLIA, this model allows processed web requests at the proxy deemed to contain injected query string to be excluded from reaching the target back-end database. This paper is intended for evaluating the performance metrics of a dataset obtained by numerical encoding of features ontology in Microsoft Azure Machine Learning (MAML) studio using Two-Class Support Vector Machines (TCSVM) binary classifier. This methodology then forms the subject of the empirical evaluation.

PCA-ANFIS based prediction for water Injection effectiveness cycle in oil fields.

By proposing a numerical based method on PCA-ANFIS(Adaptive Neuro-Fuzzy Inference System), this paper is focusing on solving the problem of uncertain cycle of water injection in the oilfield. As the dimension of original data is reduced by PCA, ANFIS can be applied for training and testing the new data proposed by this paper. The correctness of PCA-ANFIS models are verified by the injection statistics data collected from 116 wells inside an oilfield, the average absolute error of testing is 1.80 months. With comparison by non-PCA based models which average error is 4.33 months largely ahead of PCA-ANFIS based models, it shows that the testing accuracy has been greatly enhanced by our approach. With the conclusion of the above testing, the PCA-ANFIS method is robust in predicting the effectiveness cycle of water injection which helps oilfield developers to design the water injection scheme.

PCA-FNN based performance prediction for water injection in oilfields.

In order to solve the problem of uncertain cycle of water injection in the oilfield, this paper proposed a numerical method based on PCA-FNN, so that it can forecast the effective cycle of water injection. PCA is used to reduce the dimension of original data, while FNN is applied to train and test the new data. The correctness of PCA-FNN model is verified by the real injection statistics data from 116 wells of an oilfield, the result shows that the average absolute error and relative error of the test are 1.97 months and 10.75% respectively. The testing accuracy has been greatly improved by PCA-FNN model compare with the FNN which has not been processed by PCA and multiple liner regression method. Therefore, PCA-FNN method is reliable to forecast the effectiveness cycle of water injection and it can be used as an decision-making reference method for the engineers.

An investigation into PL/SQL Injection.

SQL injection is a common attack method used to leverage infor-mation out of a database or to compromise a company’s network. This paper investigates four injection attacks that can be conducted against the PL/SQL engine of Oracle databases, comparing two recent releases (10g, 11g) of Oracle. The results of the experiments showed that both releases of Oracle were vulner-able to injection but that the injection technique often differed in the packages that it could be conducted in.

Numerical encoding to tame SQL injection attacks.

Recent years have seen an astronomical rise in SQL Injection Attacks (SQLIAs) used to compromise the confidentiality, authentication and integrity of organisations’ databases. Intruders becoming smarter in obfuscating web requests to evade detection combined with increasing volumes of web traffic from the Internet of Things (IoT), cloud-hosted and on-premise business applications have made it evident that the existing approaches of mostly static signature lack the ability to cope with novel signatures. A SQLIA detection and prevention solution can be achieved through exploring an alternative bio-inspired supervised learning approach that uses input of labelled dataset of numerical attributes in classifying true positives and negatives. We present in this paper a Numerical Encoding to Tame SQLIA (NETSQLIA) that implements a proof of concept for scalable numerical encoding of features to a dataset attributes with labelled class obtained from deep web traffic analysis. In the numerical attributes encoding: the model leverages proxy in the interception and decryption of web traffic. The intercepted web requests are then assembled for front-end SQL parsing and pattern matching by applying traditional Non-Deterministic Finite Automaton (NFA). This paper is intended for a technique of numerical attributes extraction of any size primed as an input dataset to an Artificial Neural Network (ANN) and statistical Machine Learning (ML) algorithms implemented using Two-Class Averaged Perceptron (TCAP) and Two-Class Logistic Regression (TCLR) respectively. This methodology then forms the subject of the empirical evaluation of the suitability of this model in the accurate classification of both legitimate web requests and SQLIA payloads.

Effect of temperature, food availability, and estradiol injection on gametogenesis and gender in the pearl oyster Pinctada margaritifera

The black-lip pearl oyster Pinctada margaritifera is a protandrous hermaphrodite species. Its economic value has led to the development of controlled hatchery reproduction techniques, although many aspects remain to be optimized. In order to understand reproductive mechanisms and their controlling factors, two independent experiments were designed to test hypotheses of gametogenesis and sex ratio control by environmental and hormonal factors. In one, pearl oysters were exposed under controlled conditions at different combinations of temperature (24 and 28°C) and food level (10,000 and 40,000 cells mL−1); whereas in the other, pearl oysters were conditioned under natural conditions into the lagoon and subjected to successive 17β-estradiol injections (100 μg per injection). Gametogenesis and sex ratio were assessed by histology for each treatment. In parallel, mRNA expressions of nine marker genes of the sexual pathway (pmarg-foxl2, pmarg-c43476, pmarg-c45042, pmarg-c19309, pmarg-c54338, pmarg-vit6, pmarg-zglp1, pmarg-dmrt, and pmarg-fem1-like) were investigated. Maximum maturation was observed in the treatment combining the highest temperature (28°C) and the highest microalgae concentration (40,000 cells mL−1), where the female sex tended to be maintained. Injection of 17β-estradiol induced a significant increase of undetermined stage proportion 2 weeks after the final injection. These results suggest that gametogenesis and gender in adult pearl oysters can be controlled by environmental factors and estrogens. While there were no significant effects on relative gene expression, the 3-gene-pair expression ratio model of the sexual pathway of P. margaritifera, suggest a probable dominance of genetic sex determinism without excluding a mixed sex determination mode (genetic + environmental)

Investigation of the hazards of substrate current injection: transient external latchup and substrate noise coupling

Substrate current injection is the origin of external latchup and substrate noise coupling. The trigger current for external latchup depends on the duration of the trigger event. A physics-based model is provided to model the effects of aggressor to victim spacing and orientation on transient triggering of external latchup. The latchup susceptibility of standard cell based designs is also investigated. Guard rings are used to reduce latchup susceptibility and to reduce the substrate noise coupled to sensitive analog circuits. In this work, the effectiveness of different guard ring topologies for the reduction of substrate noise coupling is also investigated.

Flow-injection spectrophotometric determination of dipyrone in pharmaceutical formulations using ammonium molybdate as chromogenic reagent

A simple and rapid flow-injection spectrophotometric method is reported for the determination of dipyrone in pharmaceutical formulations. The method is based on the reaction of dipyrone with ammonium molybdate in acidic medium to produce blue molybdenum, which was detected spectrophotometrically at 620 nm. The analyte was determined in a single-line flow system. The calibration curve obtained was linear in the range of 5x10(-4) to 8x10(-3) mol L-1 for dipyrone concentration and the precision ( s r =1.7%) was satisfactory. The method proved to be selective and adequately sensitive. Application of the method to the analysis of pharmaceutical samples resulted in excellent accuracy; the percent mean recoveries were in the range 95.3%-101% and relative errors less than 5.0% for five pharmaceutical formulations were found.

Spin injection in two-dimensional layered materials and local magnetoresistance side-effects

180 p.

Effect of Playing Interactive Computer Game on Distress of Insulin Injection Among Type 1 Diabetic Children

Background: Diabetic children and their families experience high level stress because of daily insulin injection. Objectives: This study was conducted to investigate the impact of an interactive computer game on behavioral distress due to insulin injection among diabetic children. Patients and Methods: In this clinical trial, thirty children (3-12 years) with type 1 diabetes who needed daily insulin injection were recruited and allocated randomly into two groups. Children in intervention groups received an interactive computer game and asked to play at home for a week. No special intervention was done for control group. The behavioral distress of groups was assessed before, during and after the intervention by Observational Scale of Behavioral Distress–Revised (OSBD-R). Results: Repeated measure ANOVA test showed no significantly difference of OSBD-R over time for control group (P = 0.08), but this changes is signification in the study group (P = 0.001). Comparison mean score of distress were significantly different between two groups (P = 0.03). Conclusions: According to the findings, playing interactive computer game can decrease behavioral distress induced by insulin injection in type 1 diabetic children. It seems this game can be beneficial to be used alongside other interventions.

Estudo do processo de combustão in-situ usando poços horizontais como produtores de óleo (Toe-to-Hell Air Injection)

The method "toe-to-heel air injection" (THAITM) is a process of enhanced oil recovery, which is the integration of in-situ combustion with technological advances in drilling horizontal wells. This method uses horizontal wells as producers of oil, keeping vertical injection wells to inject air. This process has not yet been applied in Brazil, making it necessary, evaluation of these new technologies applied to local realities, therefore, this study aimed to perform a parametric study of the combustion process with in-situ oil production in horizontal wells, using a semi synthetic reservoir, with characteristics of the Brazilian Northeast basin. The simulations were performed in a commercial software "STARS" (Steam, Thermal, and Advanced Processes Reservoir Simulator), from CMG (Computer Modelling Group). The following operating parameters were analyzed: air rate, configuration of producer wells and oxygen concentration. A sensitivity study on cumulative oil (Np) was performed with the technique of experimental design, with a mixed model of two and three levels (32x22), a total of 36 runs. Also, it was done a technical economic estimative for each model of fluid. The results showed that injection rate was the most influence parameter on oil recovery, for both studied models, well arrangement depends on fluid model, and oxygen concentration favors recovery oil. The process can be profitable depends on air rate