Reliability and Safety Modeling of a Digital Feed Water Control System

Much digital instrumentation and control systems embedded in the critical medical healthcare equipment aerospace devices and nuclear industry have obvious consequence of different failure modes. These failures can affect the behavior of the overall safety critical digital system and its ability to deliver its dependability attributes if any defected area that could be a hardware component or software code embedded inside the digital system is not detected and repaired appropriately. The safety and reliability analysis of safety critical systems can be accomplished with Markov modeling techniques which could express the dynamic and regenerative behavior of the digital control system. Certain states in the system represent system failure while others represent fault free behavior or correct operation in the presence of faults. This paper presents the development of a safety and reliability modeling of a digital feedwater control system using Markov based chain models. All the Markov states and the transitions between these states were assumed and calculated from the control logic for the digital control system. Finally based on the simulation results of modeling the digital feedwater control system the system does meet its reliability requirement with the probability of being in fully operational states is 0.99 over a 6 months time.Comment: 13 pages, 7 figures, conferenc

Reliability and Safety Modeling of a Digital Feed-Water Control System

 إن الكثير من الأجهزة الرقمية وأنظمة التحكم المضمنة في معدات الرعاية الصحية الطبية الحيوية، وأجهزة الطيران، والصناعات النووية لها نتائج واضحة لأنماط الفشل المختلفة. يمكن أن تؤثر حالات الفشل هذه على سلوك النظام الرقمي الشامل للسلامة وقدرته على تقديم سمات الموثوقية الخاصة به إذا لم يتم الكشف عن أي منطقة معيبة يمكن أن تكون مكونًا من مكونات الأجهزة أو رمز البرنامج المضمّن داخل النظام الرقمي وإصلاحه بشكل مناسب. يمكن تحقيق تحليل السلامة والموثوقية للأنظمة الهامة للسلامة باستخدام تقنيات نمذجة ماركوف التي يمكن أن تعبر عن السلوك الديناميكي والتجديدي لنظام التحكم الرقمي. تمثل حالات معينة في النظام فشل النظام، بينما تمثل حالات أخرى سلوكًا خاليًا من الأخطاء أو عملية صحيحة في وجود أخطاء. تقدم هذه الورقة تطوير نمذجة السلامة والموثوقية لنظام التحكم الرقمي في مياه التغذية باستخدام نماذج السلسلة القائمة على ماركوف. تم افتراض جميع حالات ماركوف والتحولات بين هذه الحالات وحسابها من منطق التحكم لنظام التحكم الرقمي. أخيرًا ، استنادًا إلى نتائج المحاكاة لنمذجة نظام التحكم الرقمي في مياه التغذية ، فإن النظام يلبي متطلبات الموثوقية الخاصة به مع احتمال أن يكون في حالة التشغيل الكامل هو 0.99 على مدار 6 أشهر.Much digital instrumentation and control systems embedded in the critical medical healthcare equipment, aerospace devices, and nuclear industry have obvious consequence of different failure modes. These failures can affect the behavior of the overall safety-critical digital system and its ability to deliver its dependability attributes if any defected area that could be a hardware component or software code embedded inside the digital system is not detected and repaired appropriately. The safety and reliability analysis of safety-critical systems can be accomplished with Markov modeling techniques which could express the dynamic and regenerative behavior of the digital control system. Certain states in the system represent system failure, while others represent fault free behavior or correct operation in the presence of faults. This paper presents the development of a safety and reliability modeling of a digital feedwater control system using Markov-based chain models. All the Markov states and the transitions between these states were assumed and calculated from the control logic for the digital control system. Finally, based on the simulation results of modeling the digital feedwater control system, the system does meet its reliability requirement with the probability of being in fully operational states is 0.99 over a 6 months’ time. &nbsp

Opportunities for Practicing Sustainable Building Construction in Kurdistan Region, Iraq

Construction sector of Kurdistan region of Republic of Iraq has witnessed a huge development in construction sector last ten years. However, there are lack of awareness and legislation regarding the sustainable construction in buildings sector. The aim of the paper is to find the required mechanism to introduce sustainable practice and implement sustainable construction in the buildings construction sector at Northern Iraq. The main objectives in this study are identifying the barriers in sustainable construction at Northern Iraq and investigate the law and regulations in dealing with these barriers

ANTIBATERIAL ACTIVITY OF (HERICIUM ERINACEUS) EXTRACT ON SOME CLINICAL PATHOGENIC ISOLATES

The purpose of this research was to find the effect of alcoholic extract of the lion's mane mushroom (Hericium erinaceus) against certain clinical pathological isolates isolated from Iraqi patients suffering from various diseases such as gingivitis, urinary tract infection, diarrhea and severe vomiting, and also a biopsy was taken from the stomach of people suffering from ulcers. Out of 150 males and females sample 107 samples were isolated and identified by chemical detection and VITEK 2 technique, and by PCR  for Halicobacter pylori as follows: Staph aureus(56),Salmonella typhi(6),Pseudomonas aeruginosa(10),Escherichia coli(15),Halicobacter pylori(10),Klebsiella pneumonia(10),Candida albicans(10) samples. lion’s mane mushroom powder was extracted with 80% ethyl alcohol, and active components were investigated by chemical reagents and Gc-mass. The chemical detection of Alcoholic extract revealed the existence of  flavonoids, alkaloids, phenols, terpenoids, glycosides, and polysaccharides. The efficacy of the extract was tested using 4 concentrations (400, 200, 100, and 50 mg/ml) on bacterial and yeast isolate (C.albicans).The diameter of the inhibitory zone increased with increasing extract concentrations, according to the findings. Zone of inhibition for all isolates started at 100mg/ml except C.albicans(50mg/ml)and E.coli (200mg/ml

Prediction of Pneumonia and COVID-19 Using Deep Neural Networks

Pneumonia, caused by bacteria and viruses, is a rapidly spreading viral infection with global implications. Prompt identification of infected individuals is crucial for containing its transmission. This study explores the potential of medical image analysis to address this challenge. We propose machine-learning techniques for predicting Pneumonia from chest X-ray images. Chest X-ray imaging is vital for Pneumonia diagnosis due to its accessibility and cost-effectiveness. However, interpreting X-rays for Pneumonia detection can be complex, as radiographic features can overlap with other respiratory conditions. We evaluate the performance of different machine learning models, including DenseNet121, Inception Resnet-v2, Inception Resnet-v3, Resnet50, and Xception, using chest X-ray images of pneumonia patients. Performance measures and confusion matrices are employed to assess and compare the models. The findings reveal that DenseNet121 outperforms other models, achieving an accuracy rate of 99.58%. This study underscores the significance of machine learning in the accurate detection of Pneumonia, leveraging chest X-ray images. Our study offers insights into the potential of technology to mitigate the spread of pneumonia through precise diagnostics

Identification, Genotyping and Antimicrobial Susceptibility Testing of Brucella spp. Isolated from Livestock in Egypt

Brucellosis is a highly contagious zoonosis worldwide with economic and public health impacts. The aim of the present study was to identify Brucella (B.) spp. isolated from animal populations located in different districts of Egypt and to determine their antimicrobial resistance. In total, 34-suspected Brucella isolates were recovered from lymph nodes, milk, and fetal abomasal contents of infected cattle, buffaloes, sheep, and goats from nine districts in Egypt. The isolates were identified by microbiological methods and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Differentiation and genotyping were confirmed using multiplex PCR for B. abortus, Brucella melitensis, Brucella ovis, and Brucella suis (AMOS) and Bruce-ladder PCR. Antimicrobial susceptibility testing against clinically used antimicrobial agents (chloramphenicol, ciprofloxacin, erythromycin, gentamicin, imipenem, rifampicin, streptomycin, and tetracycline) was performed using E-Test. The antimicrobial resistance-associated genes and mutations in Brucella isolates were confirmed using molecular tools. In total, 29 Brucella isolates (eight B. abortus biovar 1 and 21 B. melitensis biovar 3) were identified and typed. The resistance of B. melitensis to ciprofloxacin, erythromycin, imipenem, rifampicin, and streptomycin were 76.2%, 19.0%, 76.2%, 66.7%, and 4.8%, respectively. Whereas, 25.0%, 87.5%, 25.0%, and 37.5% of B. abortus were resistant to ciprofloxacin, erythromycin, imipenem, and rifampicin, respectively. Mutations in the rpoB gene associated with rifampicin resistance were identified in all phenotypically resistant isolates. Mutations in gyrA and gyrB genes associated with ciprofloxacin resistance were identified in four phenotypically resistant isolates of B. melitensis. This is the first study highlighting the antimicrobial resistance in Brucella isolated from different animal species in Egypt. Mutations detected in genes associated with antimicrobial resistance unravel the molecular mechanisms of resistance in Brucella isolates from Egypt. The mutations in the rpoB gene in phenotypically resistant B. abortus isolates in this study were reported for the first time in Egypt

The Dynamics of Energy-Grain Prices with Open Interest

This paper examines the short- and long-run daily relationships for a grain-energy nexus that includes the prices of corn, crude oil, ethanol, gasoline, soybeans, and sugar, and their open interest. The empirical results demonstrate the presence of these relationships in this nexus, and underscore the importance of ethanol and soybeans in all these relationships. In particular, ethanol and be considered as a catalyst in this nexus because of its significance as a loading factor, a long-run error corrector and a short-run adjuster. Ethanol leads all commodities in the price discovery process in the long run. The negative cross-price open interest effects suggest that there is a money outflow from all commodities in response to increases in open interest positions in the corn futures markets, indicating that active arbitrage activity takes place in those markets. On the other hand, an increase in the soybean open interest contributes to fund inflows in the corn futures market and the other futures markets, leading to more speculative activities in these markets. In connection with open interest, the ethanol market fails because of its thin market. Finally, it is interesting to note that the long-run equilibrium (cointegrating relationship), speeds of adjustment and open interest across markets have strengthened significantly during the 2009-2011 economic recovery period, compared with the full and 2007-2009 Great Recession periods

Effect of Type and Dates of Canes Taking in Rooting and Growth of Grapevine (Vitis Vinifera L.) Cv. Taifi.

This study was carried out during growing season 2011-2012 on 17 years old Taifi in a private vineyard located near Zawita town, Duhok governorate, Kurdistan region, Iraq, in order to study the effect of type and dates of taking the cutting on rooting and growth of grape transplants, two types of cuttings (basal and middle cutting) were taken at three dates, first at late autumn ( November D1), second at winter (February, D2) and the third at late winter (March, D3), the basal cutting were taken with a part of wood. Results indicated that the basal cutting overtopped in shoot length, No. shoots and leaves per plant, root dry weight and rooting percentage, while never shows it influence on the content of chlorophyll. Whereas first date of taking cutting significantly increased all parameters mentioned above. Interaction of basal cutting + first time of taking had the best significantly values

Modeling Emerging Semiconductor Devices for Circuit Simulation

Circuit simulation is an indispensable part of modern IC design. The significant cost of fabrication has driven researchers to verify the chip functionality through simulation before submitting the design for final fabrication. With the impending end of Moore’s Law, researchers all over the world are looking for new devices with enhanced functionality. A plethora of promising emerging devices has been proposed in recent years. In order to leverage the full potential of such devices, circuit designers need fast, reliable models for SPICE simulation to explore different applications. Most of these new devices have complex underlying physical mechanism rendering the model development an extremely challenging task. For the models to be of practical use, they have to enable fast and accurate simulation that rules out the possibility of numerically solving a system of partial differential equations to arrive at a solution. In this chapter, we show how different modeling approaches can be used to simulate three emerging semiconductor devices namely, silicon- on- insulator four gate transistor(G4FET), perimeter gated single photon avalanche diode (PG-SPAD) and insulator-metal transistor (IMT) device with volatile memristance. All the models have been verified against experimental /TCAD data and implemented in commercial circuit simulator