A Generative Model For Zero Shot Learning Using Conditional Variational Autoencoders

Zero shot learning in Image Classification refers to the setting where images from some novel classes are absent in the training data but other information such as natural language descriptions or attribute vectors of the classes are available. This setting is important in the real world since one may not be able to obtain images of all the possible classes at training. While previous approaches have tried to model the relationship between the class attribute space and the image space via some kind of a transfer function in order to model the image space correspondingly to an unseen class, we take a different approach and try to generate the samples from the given attributes, using a conditional variational autoencoder, and use the generated samples for classification of the unseen classes. By extensive testing on four benchmark datasets, we show that our model outperforms the state of the art, particularly in the more realistic generalized setting, where the training classes can also appear at the test time along with the novel classes

Design and Development of High Voltage High Pulse Power Supply using FPGA for Dynamic Impedance Matching

High Voltage High Pulse Power Supply (HVHPPS) is designed with the goal to match fixed load, so thatprecise pulse output can be achieved. Generally the loads involve magnetron, klystron, and particle accelerators etc. The HVHPPS output pulse shape changes with load impedance variation due to various reasons. Due to changes in impedance, the performance of Pulse Power Supply degrades and reflects the power at the source end which causes component failure and system shut down. To overcome such problems, a scale down High Voltage High Pulse Power is designed and developed to match the dynamic impedance variations upto 25 % of mismatch. In earlier days, all HVHPPS were designed using microcontrollers where the problem of pulse to pulse monitoring and computational speed was compromised. The availability of variable and self-defined, Field Programmable Gate Array (FPGA) controller, which provided flexibility to design the pulse to pulse shaping and various vital parameter monitoring, made it possible. This paper presents the design and implementation of HVHPPS over an FPGA platform to meet the fast response requirement. This paper provides a solution for impedance mismatch problems associated with such types of power supply, and also presents specifications for major components in a high voltage pulse power system for various types of load ranges. An experimental test hardware was designed and developed for HVHPPS to implement dynamic impedance algorithm and validate the results

Correlation between magnetic resonance imaging and arthroscopy in internal derangement of knee

Background: Ligament injuries apart from fractures are more common in the knee joint owing to its complex anatomy. They account for a large number of referrals to our hospital, both from the general practitioner and from the accident and emergency department. Although there have been studies in literature comparing MRI with arthroscopy, the continuing improvement in diagnostic methods now available makes it especially important to compare the results and recommendations offered in the literature.Methods: The aim of this study was to find out the diagnostic accuracy of MRI scans and to examine the value of MRI as a standard preoperative examination correlating them with the gold standard of arthroscopy. This is a prospective study involving 57 patients who were admitted in Department of Orthopaedics, Mahatma Gandhi Medical College and Research Institute, with the history of injury to the knee and diagnosed to have internal derangement of the knee clinically, using standardized clinical tests. MRI of the affected knee joint was done for all these patients either before or after admission. The patients were then subjected to diagnostic and therapeutic arthroscopy.Results: The sensitivity of MRI in comparison with Arthroscopy was 100% in all studied lesions. The specificity of MRI in comparison with Arthroscopy was 94.1%, 98.1%, 100% and 97.6% for ACL, PCL, Medial meniscus and Lateral meniscus respectively.Conclusions: According to our study MRI is a very good at determining the normal anatomy of the intra articular structures of the knee joint and is highly reliable in excluding pathology, in our case tear in ligaments. Hence we recommend MRI in doubtful cases of internal derangement of the knee joint whereby unnecessary diagnostic arthroscopy can be avoided which can significantly bring down the economic burden among rural population

Fetal and maternal outcome of severe pre-eclampsia remote from term: expectant versus interventional management

Background: This study was conducted to compare the safety and effect on maternal and perinatal outcome of expectant versus interventional management in women with preterm severe preeclampsia with gestational age between 28 to 34 weeks. Methods: This was a non-blinded prospective analytical study carried out in the department of obstetrics and gynaecology, SSG hospital, Vadodara from January 2021-December 2021. 40 women diagnosed with severe pre-eclampsia remote from term meeting the inclusion criteria were divided in two groups (20 in each). First group comprised of women undergoing interventional management i.e. prompt delivery and the second group comprised of women undergoing expectant management till 34 completed weeks. The women in the expectant management underwent pregnancy termination before 34 weeks if any complication arises (e.g. anhydramnios, abruption, eclampsia etc). Results: The mean prolongation of pregnancy in the expectant management group was 11.45 days (range: 4-35 days). There was no increase in incidence of maternal complications (p value: 0.003). The fetal outcome was favourable in the expectant management group in terms of higher gestational age at delivery (33 versus 31 weeks; p value: 0.001), higher birth weight (1.7 versus 1.5 kg; p value: 0.05), higher APGAR score at 1 minute (7.5 versus 7; p value :0.05), lesser incidence of neonatal complications (55% versus 95%; p value 0.003). Conclusions: Considering the results of this study, it can be concluded that expectant management is recommended in patients with severe preeclampsia remote from term with intensive monitoring

Security of Graph Data: Hashing Schemes and Definitions

Use of graph-structured data models is on the rise - in graph databases, in representing biological and healthcare data as well as geographical data. In order to secure graph-structured data, and develop cryptographically secure schemes for graph databases, it is essential to formally define and develop suitable collision resistant one-way hashing schemes and show them they are efficient. The widely used Merkle hash technique is not suitable as it is, because graphs may be directed acyclic ones or cyclic ones. In this paper, we are addressing this problem. Our contributions are: (1) define the practical and formal security model of hashing schemes for graphs, (2) define the formal security model of perfectly secure hashing schemes, (3) describe constructions of hashing and perfectly secure hashing of graphs, and (4) performance results for the constructions. Our constructions use graph traversal techniques, and are highly efficient for hashing, redaction, and verification of hashes graphs. We have implemented the proposed schemes, and our performance analysis on both real and synthetic graph data sets support our claims

Fuzzy Delphi and hybrid AH-MATEL integration for monitoring of paint utilization

This study investigates the unattended aspects of paint utilization selection criteria in industries. In today competitive business environment almost all companies focus towards sustainable manufacturing. The utilization evaluation and selection criteria for paint and its consumption reduction is the top priority for industry. Especially in automotive industries, paint shop stands as a centre for hazardous waste due to wastage of paint and thinner during the painting process. This research work focuses on optimizing consumption of paint by finding most important criteria affecting paint consumption and optimizing the same to achieve maximum paint yield. The study uses the routes of Delphi technique in a fuzzy environment to find out the most important criteria for paint utilization selection, so that maximize utilization and minimize consump-tion reduction of paint has been achieved. An integrated approach of AHP and DEMATEL methods has been implemented to prioritize the criteria and to familiarize the relationship within criteria. The outcomes of the study substantiate and proves that this study is the best way to select a particular paint utilization selection criteria for the paint shop and also to anticipate the optimal level of paint utilization.N/