Metrics and Algorithms for Processing Multiple Continuous Queries

Data streams processing is an emerging research area that is driven by the growing need for monitoring applications. A monitoring application continuously processes streams of data for interesting, significant, or anomalous events. Such applications include tracking the stock market, real-time detection of diseaseoutbreaks, and environmental monitoring via sensor networks.Efficient employment of those monitoring applications requires advanced data processing techniques that can support the continuous processing of unbounded rapid data streams. Such techniques go beyond the capabilities of the traditional store-then-query Data BaseManagement Systems. This need has led to a new data processing paradigm and created a new generation of data processing systems,supporting continuous queries (CQ) on data streams.Primary emphasis in the development of first generation Data Stream Management Systems (DSMSs) was given to basic functionality. However, in order to support large-scale heterogeneous applications that are envisioned for subsequent generations of DSMSs, greater attention willhave to be paid to performance issues. Towards this, this thesis introduces new algorithms and metrics to the current design of DSMSs.This thesis identifies a collection of quality ofservice (QoS) and quality of data (QoD) metrics that are suitable for a wide range of monitoring applications. The establishment of well-defined metrics aids in the development of novel algorithms that are optimal with respect to a particular metric. Our proposed algorithms exploit the valuable chances for optimization that arise in the presence of multiple applications. Additionally, they aim to balance the trade-off between the DSMS's overall performance and the performance perceived by individual applications. Furthermore, we provide efficient implementations of the proposed algorithms and we also extend them to exploit sharing in optimized multi-query plans and multi-stream CQs. Finally, we experimentally show that our algorithms consistently outperform the current state of the art

A Proposed E-learning Technology Management Model for Universities in Response to the COVID-19 Global Crisis

The overall purpose of the study is to propose an e-learning technology management model that responds to the outbreak of the coronavirus disease 2019 (COVID-19) and that has led to the closure of almost all the world’s universities in 2020/2021, leading to many complications in arranging for remote teaching and learning processes. The basic design of the study included the analysis of different technology management models in terms of scope and integration. In addition to a survey directed to several international higher education and e-learning experts as well as a thematic analysis for qualitative data obtained from experts’ comments and views. The major findings, from both quantitative and qualitative analysis, structured the design of the model that has the advantage of mobilizing all university resources towards the achievement of intended learning outcomes. It focuses on six domains for elearning technology management: a) planning, b) governance and administration, c) capacity building, d) development, e) interactive teaching and learning, and f) assessment and evaluation. Hence, the proposed elearning technology management model provides better access, and more economic management of resources, and maximizes return on investment with better learning outcomes at higher education institutions

Geochemical and biomarker characteristics of crude oils and source rock hydrocarbon extracts: An implication to their correlation, depositional environment and maturation in the Northern Western Desert, Egypt

AbstractOil–oil and oil–source rock correlations are used in this study in order to achieve their relationship, depositional environments and diagenetic processes in the source rocks. Three oil samples and source rock hydrocarbon extracts were analyzed using relative geochemical analyses, and gas chromatography–mass spectrometry are used for this purpose. The results revealed that the extracts of the Alam El Bueib and Khatatba formations are derived from mixed organic sources in which terrestrial dominates marine sources, and deposited in transitional environments under less anoxic conditions. The extracts of Bahariya formation are derived from mixed marine inputs with a limited terrestrial contribution. The Alam El Bueib oil shows more contribution of terrestrial than marine sources. Also, a genetic close relation between them supported the indigenous mixed source of Alam El Bueib oil which related to different sources including the Khatatba, Alam El Bueib and Bahariya formations. Accordingly, the Alam El Bueib formation can be considered as an important source for petroleum generation in the Northern Western Desert

VizPut: Insight-Aware Imputation of Incomplete Data for Visualization Recommendation

In insight recommendation systems, obtaining timely and high-quality recommended visual analytics over incomplete data is challenging due to the difficulties in cleaning and processing such data. Failing to address data incompleteness results in diminished recommendation quality, compelling users to impute the incomplete data to a cleaned version through a costly imputation strategy. This paper introduces VizPut scheme, an insight-aware selective imputation technique capable of determining which missing values should be imputed in incomplete data to optimize the effectiveness of recommended visualizations within a specified imputation budget. The VizPut scheme determines the optimal allocation of imputation operations with the objective of achieving maximal effectiveness in recommended visual analytics. We evaluate this approach using real-world datasets, and our experimental results demonstrate that VizPut effectively maximizes the efficacy of recommended visualizations within the user-defined imputation budget.Comment: This is part of my thesis chapter https://espace.library.uq.edu.au/view/UQ:812c68

The effectiveness of Nedam's Constructive Model in Teaching Technology to Develop Productive Thinking Skills and Technological Awareness among Middle School Students in Palestine

هدفت الدراسة إلى الكشف عن فاعلية استخدام نموذج نيدام البنائي في تدريس التكنولوجيا لتنمية مهارات التفكير المنتج والوعي التكنولوجي لدي طلبة المرحلة المتوسطة بفلسطين، واتبعت الدراسة المنهج شبه التجريبي، ولتحقيق هذه الأهداف تم إعداد أداتي الدراسة وهما اختبار مهارات التفكير المنتج، ومقياس الوعي التكنولوجي، وتكونت مجموعة الدراسة من (90) طالبة، (45) طالبة للمجموعة التجريبية، (45) طالبة للمجموعة الضابطة، من طالبات الصف التاسع الأساسي بمدرسة رامز فاخرة الأساسية للبنات، وقد تم إعداد دليل للمعلم للاسترشاد به في التدريس في ضوء نموذج نيدام البنائي في الفصل الدراسي الثاني للعام 2021/2022، وتم تطبيق أداتي الدراسة قبلياً وبعدياً على المجموعتين، وأشارت النتائج إلى وجود فرق ذات قيمة احتمالية (0.05 ≥ p) بين متوسطي درجات طالبات المجموعة التجريبية، وطالبات المجموعة الضابطة في التطبيق البعدي لكل من اختبار مهارات التفكير المنتج، ومقياس الوعي التكنولوجي، وذلك لصالح طالبات المجموعة التجريبية. كما أن استخدام نموذج نيدام البنائي في تدريس التكنولوجية كان له فاعلية كبيرة في تنمية مهارات التفكير المنتج، والوعي التكنولوجي لدى طالبات الصف التاسع الأساسي. وفي ضوء هذه النتائج أوصت الدراسة باستخدام نموذج نيدام البنائي في تدريس الموضوعات التكنولوجية لما له من أثر فعال.The study aimed to reveal the effectiveness of using Needham's Constructivist Model in teaching technology to develop productive thinking skills and technological awareness among middle school students in Palestine. The study followed the semi-experimental approach. In order to achieve these goals, two study tools were prepared, which are a test of productive thinking skills, and a measure of technological awareness. The sample consisted of (90) female students, (45) students for the experimental group, and the other (45) students for the control group, from the ninth grade students at Ramez Fakhira Basic School for Girls. A teachers’ guideline was developed to guide them in teaching in the light of Needham's Constructive Model in the second semester of the year 2021/2022, and the study tools were applied on the two groups before and after using the guidline, and the results indicated that there is a statistically significant difference with a probability value  (p ≤ 0.05) between the mean scores of the experimental group and the control group in the post application of each of the productive thinking skills test and the technological awareness scale, in favor of the students of the experimental group. The use of Needham's Constructivist Model in teaching technology had a great effect on developing productive thinking skills and technological awareness among ninth grade female students. Accordingly, the study recommended the need to use the Needham's Constructivist Model in teaching technological due to its effectiveness

Hormonal dysfunction in patients with chronic obstructive pulmonary disease

AbstractBackgroundSystemic response to chronic disease in COPD patients might cause hormonal imbalance which in turn affects the severity of the disease. The severity of hypoxia in COPD patients causes alterations in thyroid function tests and IGF-1 levels.MethodsThis work was carried on 50 COPD patients diagnosed and classified according to GOLD criteria and 20 healthy controlled subjects. All subjected to full clinical history, examination, chest X-ray and spirometry. Levels of TT3, TT4, FT3, FT4, IGF-1 and insulin were measured.ResultsTT4, FT3, FT4, TSH, and insulin levels were normal in all COPD. Despite the TT3 hormone level were normal in all stages of COPD, there is reduction in hormone levels in stage III and stage IV than control subjects. There is also reduction in TT3/TT4 ratio in severe COPD and there is correlation between TT3/TT4 ratio and PaO2 in stage III and stage IV but no correlation between TT3/TT4 ratio and PaO2 in stage I and stage II. IGF-1 hormone levels were variable among different stages of COPD.ConclusionThere is was no significant difference between some hormonal levels in COPD and in controls, accordingly hormonal replacement therapy in these patients is doubtful

Application of 4-chloro-7-nitrobenzofurazan for the analysis of propafenone and diltiazem hydrochlorides using kinetic spectrophotometric and spectrofluorimetric methods

Several simple, sensitive, accurate and inexpensive spectrophotometric and spectrofluorimetric methods were developed for the determination of propafenone HCl and diltiazem HCl using 4-chloro-7-nitrobenzofurazan (NBD-Cl) accompanied with kinetic study, either in pure form or in pharmaceutical preparations. In this work, the cited drugs react with (NBD-Cl) in presence of borate buffer of pH = 7.6 at a fixed time of 30 minutes on thermostated water bath at (75-80 °C). The absorbance was measured using spectrophotometric technique at 489 and 481 nm for propafenone HCl and diltiazem HCl, respectively, or by using spectrofluorimetric technique after dilution at the specific wavelength of excitation and emission.The calibration curves were linear in the range of 4-44, 16-96 µg/mL when using spectrophotometric method, and 0.4-3.6, 1.6-8.8 µg/mL when spectrofluorimetric method was applied for propafenone HCl and diltiazem HCl, respectively. The limit of quantitation and the limit of detection were also calculated. The methods were applied successfully to commercial dosage form and can be further applied for their determination on a large scale in quality control laboratories. The obtained results statistically agreed with those obtained by reference methods. The determination of the studied drugs by the fixed concentration and rate constant methods is feasible with the calibration equations obtained, but the fixed time method proves to be more applicable