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During the past few decades, optimal control of blood glucose (BG) level with adequate feedback loop has been of ample importance for type-I diabetes mellitus (TIDM) patients as far as an artificial pancreas realization is concerned. Now-a-days, in addition to the BG control, the design of the micro-insulin dispenser (MID) with a robust control algorithm to regulate the other chronic clinical disorders based on prolonged medications is also quite indispensable. A novel model predictive controller with Laguerre Functions (MPC/LF) has been proposed in this current work to solve the aforementioned problem. For the estimation of the MPC/LF parameters, a ninth order linearized structure of the TIDM patient with MID is taken. The productivity of the MPC/LF as to accuracy, robustness and stability has been checked through simulation. The acquired outputs expose the better execution of MPC/LF to control the BG level inside the normo-glycaemic extend (70–120 mg/dl). The validation of upgrading control execution of MPC/LF is exhibited by the relative outcome investigation with other well-known control procedures.

The intention of this chapter is to formulate a genetic algorithm (GA)-based fractional order PID controller (GA-FOPIDC) for monitoring the Blood Glucose (BG) in TIDM patients. In this methodology, the traditional FOPIDC is re-constructed with the genetic algorithm concept to update the control execution. The GA-FOPIDC is a new strategy and its parameters animatedly vary based on the error signal e(t). The approval of the better execution of GA-FOPIDC is built up by relative outcome examination with other existing control techniques. The relative outcomes obviously disclose the superior execution of the recommended strategy to monitor the model dynamics inside a steady range.

To facilitate learning in a target domain, transfer learning borrows knowledge from a source domain. What and how to transfer are two main issues that need to be addressed in transferring learning. Different transfer learning algorithms result in different knowledge transferred between them for a couple of domains. To find the optimal transfer learning algorithm that maximizes learning efficiency in the target domain, scientists need to investigate all current computationally intractable transfer learning algorithms exhaustively. A sub-optimal algorithm is selected as a trade-off, which in an ad hoc way requires considerable expertise. In instructional psychology, meanwhile, it is commonly recognized that people enhance the transfer of teaching abilities to decide what to transfer. This paper discusses what is transfer learning, the different transfer learning techniques, future scope, and applications of it.

During the past few decades, optimal control of blood glucose (BG) concentration with adequate feedback loop has been of ample importance for Type-I diabetes mellitus (TIDM) patients as far as an artificial pancreas realization is concerned. Now-a-days, in addition to the BG control, the design of the micro-insulin dispenser (MID) with a robust control algorithm to regulate the other chronic clinical disorders based on prolonged medications is also quite indispensable. A novel Kalman filtering model predictive controller (KFMPC) has been proposed in this work to solve the aforementioned problem. For designing of the KFMPC, a ninth-order state-space model of the TIDM patient with MID is considered. In this control strategy, the conventional model predictive controller is re-formulated with a state estimator based on the Kalman filtering methodology to improve the control execution. The justification of enhanced control performance of KFMPC is demonstrated by comparative result analysis with other published control techniques. The simulations are carried out through matlab/simulink environment, and the results indicate comparatively better control ability of the suggested algorithm to control the BG level within the normoglycemic range (70–120 mg/dl) as far as accuracy, stability, quick damping, and robustness.

The aim of this manuscript is to formulate a Genetic Algorithm (GA) based Fractional Order PID Controller (GA-FOPIDC) for monitoring the CP, CV, and AP of an IP under abnormal circumferences. In this methodology, the traditional PID is re-constructed with the fractional order concept to update the control execution. The GA-FOPIDC is a new strategy and its parameters animatedly vary based on the error signal e(t). The approval of the better execution of GA-FOPIDC is built up by relative outcome examination with other existing control techniques. The relative outcomes obviously disclose the superior execution of the recommended strategy to monitor the model dynamics inside a steady range as for the accuracy, stability, and robustness.

This manuscript presents a SIMULINK model of glucose metabolism (GM) process and design of a fractional order proportional integral-derivative controller (FOPIDC) to regulate the blood glucose (BG) concentration in Type-I diabetes mellitus (TIDM) patients. In this control strategy, the conventional PID controller (CPIDC) is re-formulated with fractional orders of the integrator and differentiator to improve the control performance. The FOPIDC is a novel approach whose gains dynamically vary with respect to the error signal. The validation of improved control action of FOPIDC is established by comparative result investigation with other published control algorithms. The comparative results clearly reveal the better performance of the proposed approach to control the BG concentration within the normoglycaemic range in terms of accuracy, stability, and robustness.

This manuscript presents a Simulink model of inverted pendulum (IP) and design of a fractional order proportional-integral-derivative controller (FOPIDC) to control of cart position (CP) and angular position (AP) of the pendulum under uncertainties and disturbances. In this control strategy, the conventional PID controller (CPIDC) is re-formulated with fractional orders of the integrator and differentiator to improve the control performance. The FOPIDC is a novel approach whose gains dynamically vary with respect to the error signal. The validation of the improved control performance of FOPIDC is established by comparative result investigation with other published control algorithms. The comparative results clearly reveal the better response of the proposed approach to control the system dynamics within the stable range with respect to accuracy, robustness, and ability to handle uncertainties.

The aim of this paper is to design a Kalman filtering sliding mode controller (KFSMC) for control of cart position (CP), and angular position (AP) of the pendulum under uncertainties and disturbances. For designing of the KFSMC, the fourth-order state-space model of the inverted pendulum (IP) is considered. In this control strategy, the conventional sliding mode controller (CSMC) is reformulated with a state estimator based on the Kalman filtering approach to improve the control performance. The validation of the improved control performance of KFSMC is established by comparative result investigation with other published control algorithms. The comparative results clearly reveal the better response of the proposed approach to control the system dynamics within a stable range with respect to accuracy, robustness, and ability to handle uncertainties.

The aim of this paper is to design a self-tuned proportional and integral controller (STPIC) for a vehicle suspension (VS) system to improve the ride comfort by absorbing the shocks due to a rough and uneven road. In this control strategy, the conventional proportional and integral controller (CPIC) is re-formulated with an automated self-tuned approach to improve the control performance. The STPIC is a novel approach whose gains dynamically vary with respect to the error signal. The validation of the improved control performance of STPIC is established by comparative result investigation with other published control algorithms. The comparative results clearly reveal the better response of the suggested approach to control the oscillation of the VS system within a stable range with respect to the accuracy, robustness, and capability to control uncertainties.

The aim of this paper is to design a linear quadratic regulator (LQR) for a vehicle suspension (VS) system to improve the ride comfort by absorbing the shocks due to a rough and uneven road. For designing of the LQR, a fourth-order linearized model of the VS system is considered. The LQR is a novel approach whose gains dynamically vary with respect to the error signal. The validation of the improved control performance of LQR is established by comparative result investigation with other published control algorithms. The comparative results clearly reveal the better response of the suggested approach to control the oscillation of the VS system within a stable range with respect to the accuracy, robustness, and capability to control uncertainties.

This manuscript presents a SIMULINK model of glucose metabolism (GM) process and design of a linear quadratic regulator (LQR) to regulate the blood glucose (BG) concentration in type-I diabetes mellitus (TIDM) patients. For designing the LQR, a ninth-order-linearized model of the patient with micro-insulin dispenser (MID) is taken. The LQR is a novel approach whose gains dynamically vary with respect to the error signal. The validation of improved control action of LQR is established by comparative result investigation with other published control algorithms. The comparative results clearly reveal the better performance of the proposed approach to control the BG concentration (level) within the normoglycaemic range in terms of accuracy, stability, and robustness.

This paper presents a comparative analysis between the two controllers, PI and fuzzy logic controllers that used for power factor correction using DC-to-DC single-ended primary-inductor converter (SEPIC) converter. MATLAB/Simulink models of SEPIC converter are developed to improve the power factor and output voltage regulation. Average current control technique is used for input power factor correction to get a regulated voltage at the output PI or fuzzy logic controller (FLC) is adopted. The system is tested at both steady-state and transient conditions, and its performance is then estimated and compared in terms of various parameters like total harmonic distortion (THD), input power factor, output voltage ripple for PI and FLC.

This manuscript presents a SIMULINK model of Glucose Metabolism (GM) process and design of a Fuzzy Logic Controller (FLC) to regulate the Blood Glucose (BG) concentration in Type-I Diabetes Mellitus (TIDM) patients. The FLC is a novel approach whose gains dynamically vary with respect to the error and change in error signal. The validation of improved control action of FLC is established by comparative result investigation with other published control algorithms. The comparative results clearly reveal the better performance of the proposed approach to control the BG concentration (level) within the normoglycaemic range in terms of accuracy, stability, and robustness.

Through Pelletization iron ore fines produced spheres of typically 9––16 mm diameter which can be used as the raw material to the blast furnace. In the process of pelletizing the pellets may be produced of different sizes. Since the permeability of the blast furnace depends on the shape and size of the pellet it is desirable to produce nearly spherical pellets with a diameter range of 9–16 mm. There are many physical methods such as using a scale or caliper and solid displacement method to measure the size of the pellet. The shape and size of the pellet can be changed during measurement since they are wet. However, without physically handling them it is very difficult to measure the shape and size. This paper describes digital image processing techniques that are used to extract sphericity and size information from the 2D image of iron ore pellets. The techniques are simple but very useful for industrial applications. Online image processing method is also presented for calculating the sphericity and the size of a single/multiple pellets by software and its toolboxes. The technique can suitably derive the size distribution of a number of pellets. The technique is validated by conducting a number of experiments.

This manuscript presents a SIMULINK model of inverted pendulum (IP) and design of a linear quadratic regulator (LQR) to control of cart position (CP) and angular position (AP) of the pendulum under uncertainties and disturbances. For designing of the LQR, a fourth-order state-space model of the IP is taken. The LQR is a novel approach whose gains dynamically vary with respect to the error signal. The validation of the improved control performance of LQR is established by comparative result investigation with other published control algorithms. The comparative results clearly reveal the better response of the proposed approach to control the system dynamics within the stable range with respect to accuracy, robustness, and ability to handle uncertainties.

Preparation of iron ore fines as feed to blast furnace involves production of spheres of typically 9-16mm diameter through pelletization. The process combines agglomeration and thermal treatment to convert the raw ore into pellets appropriate for use in a blast furnace. The use of pellets of varying shape and size has attracted much interest. The permeability of blast furnace is dependant on the size and shape of the pellets. The productivity of pelletization is based on generation of pellets of size range of 9-16mm. The pelletization process is governed by the physical characteristic of pellets and therefore it is necessary to investigate accurately the shape and size of the pellets in pelletization process. It is desirable to produce nearly spherical pellets with a desired diameter range. In the process of pelletization the pellets may be produced of different sizes. This may be accepted if it is within certain tolerance limit. Therefore, it is essential to measure the size and provide a quantitative value for the shape of the pellets. The size can be measured by many methods such as using a scale or caliper and solid displacement method etc. However, it is very difficult to measure the size and shape of green pellets without physically handling them. Since they are wet and they change their size and shape during measurement. Some researchers have worked using imaging techniques for pellet size analysis [3-4]. This motivated to develop such a system. An attempt is made here to measure the shape and size of the pellets using 2D-digital image processing techniques. Online image processing method is also presented for calculating the sphericity and the size of a single/multiple pellet by software and its toolboxes. The technique can suitably derive the size distribution of a number of pellets. The technique is validated by conducting a number of experiments

As of late, deep learning has gained remarkable growth in various fields, for example, computer vision and natural language processing. Contrasted with conventional machine learning strategies, deep learning has a robust learning capacity and can improve utilization of datasets for feature extraction. In view of its practicability, deep learning turns out to be increasingly mainstream for many researchers to do research works. In this paper we mainly focus on the optimization of different parameters of convolutional neural network of deep learning for classifying 8000 labelled natural images of cat and dog. First the convolutional neural network is trained to learn features then ANN binary classifier is used for classification. Various level of optimization have been done to improve the performance level of the network and finally, we achieved the best classification accuracy of 88.31%.

Background: The aim of present study was to evaluate the utility of HPV-DNA testing in cervical cancer screening. Methods: The study included 110 women presenting to the Gynaecological OPD of SMI Hospital who were subjected to HPV DNA test and one or more of other tests like cytology, colposcopy and histopathological examination. The results were evaluated by standard statistical methods. Results: Out of 110 patients in whom HPV-DNA testing was done, 24 had positive result, 83 had negative result and 3 had borderline test result. Sensitivity & Specificity of HPV-DNA testing was calculated to be 90% and 84.61% respectively. Its positive predictive value and negative predictive value were 69.23% and 95.66%. The percentage of false negative was calculated to be 10% and that of false positive was 15.38%. Conclusions: In our study, the sensitivity and negative predictive value of HPV-DNA testing was found to be more as compared to its specificity and positive predictive value. Widespread HPV testing for primary cervical cancer screening is not recommended as it will increase the volume of HPV testing and will not be cost- effective. It may be used for secondary screening in patients with abnormal or (ASC) cytology results as this will help in their subsequent management.

Introduction: Ectopic pregnancy is an emergency in obstetric wards and a significant cause of maternal morbidity and mortality. Incidences of ectopic pregnancy are increasing. Life can be saved with quickness and alertness. Objective: The objective of this study is to find out and evaluate the incidence, clinical presentation, risk factors, and management outcomes of ectopic pregnancies at Sri Guru Ram Rai Institute of Medical and Health Sciences (SGRRIMHS), Dehradun, Uttarakhand, India. Method: We did a retrospective study of the patients admitted in our hospital (SMI Hospital, SGRRIMHS) and study period was January 1, 2004 to December 31, 2013. Medical records were studied for management, total admission in obstetric wards, total births. Data were collected with the aid of data-entry forms designed for study. There were 4040 ANC patients admitted, out of which 202 cases were ectopic pregnancies. The relevant data collected were analyzed with SPSS for Windows. Result: Ectopic pregnancy constituted 5.0% of all ANC cases admitted in our Hospital. The mean age of patients was 25 ± 2 years, 192 of 202 (95.04%) had ruptured pregnancies, and remaining 10 (4.96%) were unruptured. The commonest clinical presentation was abdominal pain (162 of 20280.19%). The commonest (120 of 202, 59.4%) cause was past history of induced abortion. 4 deaths (1.98%) were recorded. Conclusion: Ecotopic pregnancy is common and recognized cause of maternal morbidity and mortality. It is a recognized risk of induced abortion.

During the past few decades, optimal control of blood glucose (BG) concentration with adequate feedback loop has been of ample importance for type-I diabetes mellitus (TIDM) patients as far as an artificial pancreas (AP) realisation is concerned. Now-a-days, in addition to the BG control, the design of the micro-insulin dispenser (MID) with a robust control algorithm to regulate the other chronic clinical disorders based on prolonged medications is also quite indispensable. A novel model predictive controller with Laguerre functions (MPC/LF) has been proposed in this current work to solve the aforementioned problem. For the estimation of the MPC/LF parameters, a ninth order linearised structure of the TIDM patient with MID is taken. The productivity of the MPC/LF as to accuracy, robustness and stability has been checked through simulation. The acquired results obviously expose the better execution of the proposed strategy to control the BG level inside the normo-glycaemic extend (70-120 mg/dl). The validation of upgrading control execution of MPC/LF is exhibited by the relative outcome investigation with other well-known control procedures.

The mechanisation of the insulin infusion regulation through the artificial pancreas (AP) is needed to design with an objective to control the blood glucose (BG) level in type 1 diabetes mellitus (T1DM) patients. However, to make it applicable in real time, major components needed are availability of proper sensor augmented pumps, glucose monitoring systems, and control techniques. Recent times many researchers suggest robust control techniques for designing a robust controller for computing the required insulin dose for a highly nonlinear human metabolism system. This paper proposes a simulation model of glucose metabolism process and design of a backstepping linear quadratic Gaussian controller (BLQGC) to control the BG level in TIDM patients. The simulations are carried out through MATLAB/SIMULINK environment and the results indicate comparatively better control ability of the proposed algorithm to control the BG concentration within the range of normoglycaemia in terms of accuracy, stability, quick damping and robustness.

Objectives The present study was undertaken to correlate cytology, HPV-DNA test and colposcopy in evaluation of cervical intraepithelial lesions. Materials and methods Patients were subjected to Pap smear, HPV-DNA detection, colposcopy and directed cervical biopsy if required. The various screening methods were correlated and evaluated by standard statistical methods. Observations A total of 324 patients were included in the study. Colposcopy was done in 263, Pap smear in 214, HPVDNA in 100 and HPE in 116 patients. Sensitivity and specificity of Pap smear test, colposcopy and HPV-DNA testing were calculated to be 66.66, 93.54, 86.84, 86.32, 90 and 84.61% respectively. Their positive predictive value and negative value were 75, 90.60, 67.34, 95.28, 69.23 and 95.66% respectively. The percentage of false negative and false positive were calculated to be 33.33, 6.45, 8.95, 13.67, 10 and 15.38% respectively. Conclusion Various screening methods for evaluation of cervical intraepithelial lesions are complimentary to each other and need to be carried out depending on the clinical findings, patient's convenience and compliance, facilities and set-up available. How to cite this article Gupta V, Tandon A, Nanda A, Sharma A, Bansal N, Singhal M. Correlation between Cytology, HPV-DNA Test and Colposcopy in Evaluation of Cervical Intraepithelial Lesions. J South Asian Feder Menopause Soc 2014;2(2):71-74.

The aim of this study was to investigate perinatal outcome and the rate of cesarean section (CS) following intrapartum amnioinfusion in women with meconium-stained amniotic fluid (MSAF).A total of 100 women at term in labor with meconium were randomized to infuse transcervical intrapartum amnioinfusion with saline (50) and routine obstetrical care (50). Perinatal outcome and obstetric outcome were recorded and analyzed in both groups by means of Chi-square test.The CS rate due to fetal distress was 40.0 % in the control group and 20.0 % in the study group. The difference was statistically significant (P 0.01). Respiratory distress of the neonate was significantly less common in the study group than in the control group (4.0 % vs. 12 %; P = 0.0349).Amnioinfusion in cases of meconium-stained liquor significantly improved neonatal outcome and CS rate without increasing any maternal and fetal complications.

Twin pregnancy in association with rudimentary horn pregnancy is extremely rare and more so in spontaneous conceptions. Rudimentary horn pregnancy coexistent with an intrauterine pregnancy usually results in rupture of the rudimentary horn and death of the correspondent twin. We report an unusual case of twin pregnancy following spontaneous conception in association with rudimentary horn rupture. How to cite this article Gupta V, Nanda A, Tandon A, Ahmed A. An Unusual Case of Twin Pregnancy associated with Rudimentary Horn Rupture. J South Asian Feder Obst Gynae 2017;9(2):123-124.

Objective: To correlate outcome and acceptability of medical abortion with gestational age.Method: A one-year prospective trial was done at SGRR-IMHS, Dehradun. A total of 110 patients of gestational age 0.05; significant). Acceptability ofprocedure was 98.33% in group I and 86% in group II and this difference was found to be statistically highly significant (P value > 0.02).Conclusion: Medical abortion is an effective and safe method of termination of early intrauterine pregnancy. However, there was significantdifference in success rate and acceptability before 49 days gestation as compared to that between 49 and 63 days.

Cervical pregnancy is a rare variety of ectopic pregnancy. The diagnosis of cervical pregnancy can be missed by an unsuspecting mind inspite of the routine use of first trimester ultrasonography. We present two cases of cervical pregnancy managed at our hospital alongwith a brief review of literature highlighting the various treatment modalities.

Cervical and vaginal fibroid may be seen in less than 1% of the pregnant women. During labor, they may be responsible for obstruction or cervical dystocia. Usually in such cases, cesarean section is done to deliver the baby. An extensive literature search has shown only few case reports outlining vaginal myomectomy of a prolapsed cervical fibroid during pregnancy and none during labor. We are reporting a case of cervical fibroid which prolapsed outside the introitus during early labor resulting in obstructed labor for which intrapartum vaginal myomectomy was done to facilitate vaginal breech delivery. How to cite this article Gupta V, Kumari N, Srivastava M, Nanda A. Intrapartum Vaginal Myomectomy of a Prolapsed Cervical Fibroid. J South Asian Feder Menopause Soc 2014; 2(2):99-100.

Choriocarcinoma is a malignant tumor of trophoblastic tissue and constitutes about 30 to 40% of the trophoblastic neoplasia cases. Early hematogenous spread is characterstic of choriocarcinoma. We report a case of metastatic cerebral choriocarcinoma in a 23-year-old female with appearance of acute neurological signs following spontaneous intracerebral hemorrhage as the initial presentation. She underwent successful treatment of choriocarcinoma with chemotherapy (EMA-CO regime) and was able to have normal baby with good apgar score. The case emphasizes the importance of suspecting an underlying choriocarciroma in women of child bearing age group presenting with spontaneous cerebral hemorrhage and an uncomplicated term delivery can be expected after complete chemotherapy for GTN.

Background: The present study was undertaken to evaluate the role of colposcopy as a screening and diagnostic tool for cervical cancer and other cervical lesions in high risk women. Methods: All the women included in the study were subjected to colposcopic examination. Colposcopic findings were compared with cytology and histopathological examination. Accuracy of colposcopic examination was calculated by standard statistical methods. Sensitivity, specificity, Positive Predictive Valve (PPV) and Negative Predictive Valve (NPV) of colposcopic examination was calculated. Results: Three hundred patients underwent colposcopic examination. The overall sensitivity and specificity of colposcopy was 85.85% and 87.65% respectively. Positive predictive value was 75.83% and negative predictive value was 95.38%. The percentage of false negative as well as that of false positive was calculated to be 13.74%. The accuracy of colposcopy was found to be more for high grade lesions as composed to low grade lesions. Conclusions: Colposcopy gives immediate and accurate results and its value as diagnostic modality is undisputed. It should also be considered as a primary screening test for high risk women living in remote areas where women cannot visit the doctor repeatedly as the ideal screening triage cannot be implemented in such situations.