Constraint-Guided Machine Learning for Solving Optimal Power Flow Problem

Due to the nonlinear and non-convex attributes of the optimization problems in power systems such as Optimal Power Flow (OPF), traditional iterative optimization algorithms require significant amount of time to converge for large electric networks. Therefore, power system operators seek other methods such as DC Optimal Power Flow (DCOPF) to obtain faster results, to obtain the state of the system. However, DCOPF provides approximated results, neglecting important features of the system such as voltage and reactive power. Fortunately, recent developments in machine learning have led to new approaches for solving such problems faster, more flexible, and more accurate. In this research, a Deep Neural Network-based Optimal Power Flow (DNN-OPF) algorithm is implemented on small to large case studies to show the accuracy and efficiency of the ML-based algorithms. Since the ML methods such as NN are considered black-box approaches, the system operators are not satisfied with solving power system models using them, as such methods do not explain the reasoning behind the generated solutions. Moreover, there is no guarantee that the obtained solutions would be converging and close to optimality. To overcome such issues this research provides a novel approach to first classify the converging and non-converging ACOPF problems, and then suggests a constraint-guided method, based on normalizing outputs and using particular activation functions to satisfy the technical limits of the generators such as maximum and minimum generation. Furthermore, a post-processing approach is incorporated to check for the convergence of the power flow equations which are in form of equality constraints. The suggested method is applied on IEEE24-bus, IEEE 300 bus, and PEGASE 1354 bus systems and the results show significant improvement on execution time, comparing to traditional gradient-based methods, such as Newton-Raphson and Gauss–Seidel methods. Also, the approach has been benchmarked against DCOPF model and it is shown that the proposed DNN-OPF not only provides faster speed, but also ensures higher accuracy on the final results. Furthermore, since is a need to run ACOPF problem using different scenarios, to account for continuous changes in the demand, the suggested DNN-OPF is solved for various scenarios from 1 to 10,000 to appreciate the improved execution time obtained from the ML-based approaches. Our results show that DNN can improve execution time a factor of 400 to 800 for large to small networks

The Importance of Non-Invasive Mechanical Ventilation: Current Status in Iran

Over the past two decades, the use of non-invasive positivepressure ventilation (NIPPV) has increased in manyICUs around the world (1). According to a study conductedin French, the use of non-invasive ventilation during 1994to 2001 increased from 20 to 90% (2). The result of serialsurvey from more than 40 countries indicated that theoverall use of NIPPV increased from 4.4% in 1998 to 14% in2010 (3, 4).NIPPV is used in wide variety conditions. It is a wellrecognizedapproach in the management of acute respiratoryfailure, acute exacerbations of chronic obstructivepulmonary disease (COPD), hypoxemic respiratory failure,community-acquired pneumonia, cardiogenic pulmonaryedema, and after solid organ transplants (5). It is also consideredas the most effective treatment available for motorneuron disease when respiratory symptoms appear (6).Non-invasive ventilation is a well-known strategy toavoid endotracheal intubation and its complications (7).Endotracheal intubation in critically ill patients is accompaniedbyhighriskandlife threatening complicationssuch as severe hypoxemia and hypotension, even in intensivecare units (8). NIPPV reduces endotracheal intubationrate, mortality, and length of stay in the intensive care unitand it is a life-saving intervention (9-11)

Gamma irradiation effects on physical properties of squash seeds

In order to study the effects of gamma radiation on some physical properties of squash (Cucurbit pepo. L) seed, five irradiation doses (25, 50, 75, 100 and 200 GY) have been used.  Some physical properties, including dimensional properties (length, width, thickness, geometric mean diameter, sphericity, volume, surface area, projected area, flakiness ratio and elongation ratio), mass, 1,000 seeds mass, bulk density, true density and porosity of gamma irradiated squash seeds were measured.  Statistical indices including maximum, minimum, average, variance, skewness and kurtosis, for dimensional properties and mass of the seeds were calculated.  Results revealed a significant raise in hollow seeds number by increasing gamma irradiation dose from 5% for 25 GY to nearly 100% for 100 and 200 GY.  On the other hand, length, width, thickness, mass of single seed, 1,000 seeds mass and porosity showed an increase followed by a decrease with the increasing gamma irradiation dose.  With the increasing gamma irradiation dose, true and bulk densities were found to decrease from 338.41   kg m-3 to 214.01 kg m-3 and 420.16 kg m-3 to 256.12 kg m-3, respectively.  In 100 and 200 GY all seeds were hollow and very small, therefore dimensions and mass of these seeds were not measured. Keywords: gravimetric properties, dimensional properties, squash seeds, irradiation, gamma ra

Effect of the Thickness of High Tc Superconducting Rectangular Microstrip Patch over Ground Plane with Rectangular Aperture

In recent years, a great interest has been observed in the development and use of new materials in microwave technology. Particularly, a special interest has been observed in the use of superconducting materials in microwave integrated circuits, this is due to their main characteristics. In this paper, the complex resonant frequency problem of a superconductor patch over Ground Plane with Rectangular Aperture is formulated in terms of an integral equation, the kernel of which is the dyadic Green’s function. Galerkin’s procedure is used in the resolution of the electric field integral equation. The surface impedance of the superconductor film is modeled using the two fluids model of Gorter and Casimir. Numerical results concerning the effect of the thickness of the superconductor patch on the characteristics of the antenna are presented

A cost utility and cost effectiveness analysis of different oral antiviral medications in patients with HBeAg-Negative chronic hepatitis B in Iran: an economic microsimulation decision model

Background: Although hepatitis B infection is the major cause of chronic liver disease in Iran, no studies have employed economic evaluations of the medications used to treat Iranian patients with chronic hepatitis B (CHB). Therefore, the cost-effectiveness of the different treatment options for this disease in Iran is unknown. Objectives: The aim of this study was to compare the cost utility and cost-effectiveness of medication strategies tailored to local conditions in patients with HB e antigen (HBeAg)-negative CHB infection in Iran. Methods: An economic evaluation of the cost utility of the following five oral medication strategies was conducted: adefovir (ADV), lamivudine (LAM), ADV + LAM, entecavir (ETV), and tenofovir (TDF). A Markov microsimulation model was used to estimate the clinical and economic outcomes over the course of the patient’s lifetime and based on a societal perspective. Medical and nonmedical direct costs and indirect costs were included in the study and life-years gained (LYG) and quality-adjusted life-years (QALY) were determined as measures of effectiveness. The results are presented in terms of the incremental cost-effectiveness ratio (ICER) per QALY or LYG. The model consisted of nine stages of the disease. The transition probabilities for the movement between the different stages were based on clinical evidence and international expert opinion. A probabilistic sensitivity analysis (PSA) was used to measure the effects of uncertainty in the model parameters. Results: The results revealed that the TDF treatment strategy was more effective and less costly than the other options. In addition, TDF had the highest QALY and LYG in the HBeAg-negative CHB patients, with 13.58 and 21.26 (discounted) in all comparisons. The PSA proved the robustness of the model results. The cost-effectiveness acceptability curves showed that TDF was the most cost-effective treatment in 59% - 78% of the simulations of HBeAg-negative patients, with WTP thresholds less than $14010 (maximum WTP per QALY). Conclusions: The use of TDF in patients with HBeAg-negative CHB seemed to be a highly cost-effective strategy. Compared with the other available medication options, TDF was the most cost-saving strategy. Thus, TDF may be the best option as a first-line medication. Patients can also be switched from other medications to TDF

Antibacterial Efficacy of Different Concentrations of Sodium Hypochlorite Gel and Solution on Enterococcus faecalis Biofilm

Introduction: This in vitro study compared the antibacterial efficacy of 2.5% sodium hypochlorite gel and 2.5% and 5.25% sodium hypochlorite solutions on Enterococcus faecalis (E. faecalis) biofilm. Methods and Materials: The root canals of 60 extracted human single-rooted teeth were contaminated with E. faecalis and incubated for 6 weeks. The samples were randomly assigned to three experimental groups and one control group (n=15). The study protocol in the experimental groups consisted of injection of 5 mL of each irrigant into the root canals. Samples were collected from the root canal walls and 1:10 serial dilutions were prepared and added to Muller Hinton Agar (MHA) plates and incubated at 37°C for 48 h. A classic colony counting technique was used for determining vital E. faecalis bacterial counts in MHA plates. The Kruskal-Wallis test was used for statistical analysis of the data. The level of significance was set at 0.05. Results: The antibacterial effect of the irrigants in all three experimental groups was significantly greater than the control group (P<0.05), with no significant difference between 2.5% and 5.25% NaOCl solutions (P>0.05). The effect of 2.5% and 5.25% NaOCl solutions were significantly superior to 2.5% NaOCl gel (P<0.05). Conclusion: Under the limitations of this study, 2.5% NaOCl gel was effective in reducing E. faecalis counts; however this effect was less than that of NaOCl solutions.Keywords: Antibacterial; Biofilm; Enterococcus Faecalis; Sodium Hypochlorit

AxBench: A Benchmark Suite for Approximate Computing Across the System Stack

Research areas: Approximate computing, Computer architectureAs the end of Dennard scaling looms, both the semiconductor industry and the research community are exploring for innovative solutions that allow energy efficiency and performance to continue to scale. Approximation computing has become one of the viable techniques to perpetuate the historical improvements in the computing landscape. As approximate computing attracts more attention in the community, having a general, diverse, and representative set of benchmarks to evaluate different approximation techniques becomes necessary. In this paper, we develop and introduce AxBench, a general, diverse and representative multi-framework set of benchmarks for CPUs, GPUs, and hardware design with the total number of 29 benchmarks. We judiciously select and develop each benchmark to cover a diverse set of domains such as machine learning, scientific computation, signal processing, image processing, robotics, and compression. AxBench comes with the necessary annotations to mark the approximable region of code and the application-specific quality metric to assess the output quality of each application. AxBenchwith these set of annotations facilitate the evaluation of different approximation techniques. To demonstrate its effectiveness, we evaluate three previously proposed approximation techniques using AxBench benchmarks: loop perforation [1] and neural processing units (NPUs) [2–4] on CPUs and GPUs, and Axilog [5] on dedicated hardware. We find that (1) NPUs offer higher performance and energy efficiency as compared to loop perforation on both CPUs and GPUs, (2) while NPUs provide considerable efficiency gains on CPUs, there still remains significant opportunity to be explored by other approximation techniques, (3) Unlike on CPUs, NPUs offer full benefits of approximate computations on GPUs, and (4) considerable opportunity remains to be explored by innovative approximate computation techniques at the hardware level after applying Axilog