Mean squared error of empirical predictor

The term ``empirical predictor'' refers to a two-stage predictor of a linear combination of fixed and random effects. In the first stage, a predictor is obtained but it involves unknown parameters; thus, in the second stage, the unknown parameters are replaced by their estimators. In this paper, we consider mean squared errors (MSE) of empirical predictors under a general setup, where ML or REML estimators are used for the second stage. We obtain second-order approximation to the MSE as well as an estimator of the MSE correct to the same order. The general results are applied to mixed linear models to obtain a second-order approximation to the MSE of the empirical best linear unbiased predictor (EBLUP) of a linear mixed effect and an estimator of the MSE of EBLUP whose bias is correct to second order. The general mixed linear model includes the mixed ANOVA model and the longitudinal model as special cases

Real Time Domestic Power Consumption Monitoring using Wireless Sensor Networks

This paper subsumes the implementation of automation in tracking the electrical consumption data of household systems over the network (WEB). This could sub-sequentially cut down the manual work involved in the process of collecting no: of units consumed from each house, thereby avoiding the manual costs and errors by building an automatic network access. The installation of this system is quite an easy task, which do not need much hardware work. The key elements that make this system are Current sensor and Voltage sensor interfaced to an Arduino board (A General Purpose Micro Controller board) with an Ethernet shield and a WIFI Router for transmission of data wirelessly to the server for storing consumption values into the database. Hosting web pages with the database connectivity will make the administrator generate electricity bill automatically that facilitates user’s to view and pay his electricity bill online

Application of artificial neural networks for the prediction of aluminium agglomeration processes

Aluminium is universal and vital constituent in composite propellants and typically used to improve performance. Aluminum agglomeration takes place on the burning surface of aluminized propellants, which leads to reduced combustion efficiency and 2P flow losses. To understand the processes and behaviour of aluminum agglomeration, particles size distribution of composite propellants were studied using a quench particle collection technique, at 2 to 8 MPa and varying quench distances from 5mm to 71mm. To predict the agglomerate diameter of metallized/ultra-fine aluminium of composite propellants, a new artificial neural network (ANN) model was derived. Five Layered Feed Forward Back Propagation Neural Network was developed with sigmoid as a transfer function by varying feed variables in input layer such as Quench distance (QD) and pressure (P). The ANN design was trained victimization stopping criterion as one thousand iterations. Five ANN models dealing with the combustion of AP/Al/HTPB and one ANN model of AP/UFAl/HTPB composite propellants were presented. The validated ANN models will be able to predict unexplored regimes wherein experimental data are not available. From the present work it was ascertained that, for agglomeration produced by quench collection technique, the ANN is one of a substitute method to predict the agglomerate diameter and results can be evaluated rather than experimented, with reduced time and cost. The resulting agglomerates sizes from ANN model, matches with the experimental results. The percentage error is less than 3.0% of the label propellants used in this work

Objective structured practical examination (OSPE) as a tool in formative assessment of II MBBS students, in pathology

Background: Assessment drives the student learning. Regular periodical assessment not only improves learning habits, but also enhances the competence in all levels of medical education. Traditional practical examination is more subjective. It depends on examiners subjectivity, varying difficulty level of various experiments, and also internal marks variation etc. These flaws can be overcome by newer methods like OSPE. The aim of the study was to implement OSPE as a tool of internal assessment for practical skills in the II MBBS. To compare this with traditional practical examination (TPE). To obtain the students and faculty feedback regarding OSPE as a tool of assessment.Methods: A cross sectional study was carried out for 158 students in II internal pathology practical examination for six days in the second week of September 2016 at Department of Pathology, Dr. Pinnamaneni Siddhartha institute of medical sciences & Research Foundation, Chinnaoutpalli. Faculty and students were sensitized; blueprint were used to arrange twenty OSPE stations for the exercises conducted as per TPE and for the same 25 marks as per TPE. Simultaneously, all the students were subjected to both TPE and OSPE at the same time and venue. TPE was assessed by two professors and OSPE by separate eight faculty members independently without interaction with the students. The procedural stations were evaluated by using checklist and the response stations which consisted of short answers and MCQs, facilitated correction. Feedback was given to the student on their performance and feedback was obtained from the students and faculty regarding OSPE by questionnaire with Yes/No answers.Results: Performance score of students in OPSE (13.73 ±2.49) was higher as compared to TPE (9.27±1.86) which was statistically significant. Based on the response to the questionnaire, students perception towards OSPE was analyzed. Majority strongly agree OSPE to be fairer, more transparent and objective in comparison to TPE. In contrast, all the faculty members unanimously opined that OSPE was difficult to arrange, time taken and faculty versus students ratio was high for evaluation. Though, the faculty (91%) overall opined that OSPE should be included as a method of assessment.Conclusions: Present study revealed that OSPE was acceptable, feasible and reliable to the students as well as for faculty for the internal assessment in pathology. Opinions of both students and faculties strongly agreed that OPSE is more effective objective assessment tool

Post-surgical giant pseudo meningocele in a patient with cervical neurofibroma: Case report and literature review

A patient aged 48-year-old, presented to the outpatient department with neck pain and weakness of all the limbs for three months. On examination, he had power 3/5 in all the limbs with bilateral hand grip weakness of 50%. Neuroimaging study showed a dumbell shaped lesion with compression of the spinal cord in the cervical region that was identified as a C4/C5 neurofibroma. Cervical laminectomy and excision of the tumour and unilateral lateral mass screw and rod fixation was done. Post operatively patient was discharged with improved motor power. One month after surgery, he presented with bulging at the operative site, which was diagnosed as a pseudo meningocele that did not respond to conservative therapy. As swelling was increasing size and becoming tense and also complaining of severe neck pain and postural hypotension, it was managed surgically, three months after first surgery, by excision of pseudo meningocele with primary repair of dural defect with muscle graft and lumbar drain inserted intraoperatively which was removed after five days. Patient’s neck pain and hypotensive episode were improved after repair. Possible causes for the development of post-operative pseudo meningocele can be soft tissue and paravertebral muscle damage or high intradural pressures that causes leakage of cerebrospinal fluid from a very small dural defect. Shunt insertion should be reserved for patients with impaired cerebrospinal fluid absorption or those with a refractory fistula, despite medical therapies and direct surgical repairs

Seasonal dynamics of Shatavarin-IV, a potential biomarker of Asparagus racemosus by HPTLC: Possible validation of the ancient Ayurvedic text.

174-181The medicinal property of Asparagus racemosus is primarily attributed to its constituent steroidal saponins, particularly the major component, shatavarin-IV. Thus, it can serve as a biomarker and its level can decide of the utility of the plant cultivar as a drug. Hence, a sensitive, reliable and quantitative High Performance Thin Layer Chromatography (HPTLC) method has been established for quantification of shatavarin-IV in the methanolic extracts of the roots collected in both summer and rainy seasons. The extracts of the powders of dried roots were applied to silica gel 60 F254 aluminum-supported precoated TLC plates and developed with n-hexane: ethyl acetate: methanol, 80:10:10 (v/v), as the mobile phase. Shatavarin-IV was detected and quantified by densitometry at λ = 336 nm. The accuracy of the method was checked by conducting recovery studies at three different levels of shatavarin-IV. The average recovery was found to be 101% and 107% for summer and rainy seasons respectively. The shatavarin-IV contents, as estimated by the proposed method were 12.5 μg gm-1 and 10.9 μg gm-1 in summer and rainy roots respectively. The entire method was performed six times (n=6) to check the repeatability. The proposed HPTLC method for quantitative monitoring of shatavarin-IV in A. racemosus roots collected in different seasons strictly adhered to the validation issues laid down by the ICH guidelines. The method is reliable reproducible and highly precise and selective

Seasonal dynamics of Shatavarin-IV, a potential biomarker of Asparagus racemosus by HPTLC: Possible validation of the ancient Ayurvedic text.

The medicinal property of Asparagus racemosus is primarily attributed to its constituent steroidal saponins, particularly the major component, shatavarin-IV. Thus, it can serve as a biomarker and its level can decide of the utility of the plant cultivar as a drug. Hence, a sensitive, reliable and quantitative High Performance Thin Layer Chromatography (HPTLC) method has been established for quantification of shatavarin-IV in the methanolic extracts of the roots collected in both summer and rainy seasons. The extracts of the powders of dried roots were applied to silica gel 60 F254 aluminum-supported precoated TLC plates and developed with n-hexane: ethyl acetate: methanol, 80:10:10 (v/v), as the mobile phase. Shatavarin-IV was detected and quantified by densitometry at λ = 336 nm. The accuracy of the method was checked by conducting recovery studies at three different levels of shatavarin-IV. The average recovery was found to be 101% and 107% for summer and rainy seasons respectively. The shatavarin-IV contents, as estimated by the proposed method were 12.5 μg gm-1 and 10.9 μg gm-1 in summer and rainy roots respectively. The entire method was performed six times (n=6) to check the repeatability. The proposed HPTLC method for quantitative monitoring of shatavarin-IV in A. racemosus roots collected in different seasons strictly adhered to the validation issues laid down by the ICH guidelines. The method is reliable reproducible and highly precise and selective

Conformal Group Recommender System

Group recommender systems (GRS) are critical in discovering relevant items from a near-infinite inventory based on group preferences rather than individual preferences, like recommending a movie, restaurant, or tourist destination to a group of individuals. The traditional models of group recommendation are designed to act like a black box with a strict focus on improving recommendation accuracy, and most often, they place the onus on the users to interpret recommendations. In recent years, the focus of Recommender Systems (RS) research has shifted away from merely improving recommendation accuracy towards value additions such as confidence and explanation. In this work, we propose a conformal prediction framework that provides a measure of confidence with prediction in conjunction with a group recommender system to augment the system-generated plain recommendations. In the context of group recommender systems, we propose various nonconformity measures that play a vital role in the efficiency of the conformal framework. We also show that defined nonconformity satisfies the exchangeability property. Experimental results demonstrate the effectiveness of the proposed approach over several benchmark datasets. Furthermore, our proposed approach also satisfies validity and efficiency properties.Comment: 23 page