Accelerating Stochastic Random Projection Neural Networks

Artificial Neural Network (ANN), a computational model based on the biological neural networks, has a recent resurgence in machine intelligence with breakthrough results in pattern recognition, speech recognition, and mapping. This has led to a growing interest in designing dedicated hardware substrates for ANNs with a goal of achieving energy efficiency, high network connectivity and better computational capabilities that are typically not optimized in software ANN stack. Using stochastic computing is a natural choice to reduce the total system energy, where a signal is expressed through the statistical distribution of the logical values as a random bit stream. Generally, the accuracy of these systems is correlated with the stochastic bit stream length and requires long compute times. In this work, a framework is proposed to accelerate the long compute times in stochastic ANNs. A GPU acceleration framework has been developed to validate two random projection networks to test the efficacy of these networks prior to custom hardware design. The networks are stochastic extreme learning machine, a supervised feed-forward neural network and stochastic echo state network, a recurrent neural network with online learning. The framework also provisions identifying optimal values for various network parameters like learning rate, number of hidden layers and stochastic number length. The proposed stochastic extreme learning machine design is validated for two standardized datasets, MNIST dataset and orthopedic dataset. The proposed stochastic echo state network is validated on the time series EEG dataset. The CPU models were developed for each of these networks to calculate the relative performance boost. The design knobs for performance boost include stochastic bit stream generation, activation function, reservoir layer and training unit of the networks. Proposed stochastic extreme learning machine and stochastic echo state network achieved a performance boost of 60.61x for Orthopedic dataset and 42.03x for EEG dataset with 2^12 bit stream length when tested on an Nvidia GeForce1050 Ti

Ontology Based Public Healthcare System in Internet of Things (IoT)

AbstractInternet of Things is a growing technology that is predicted to discover new drugs and medical treatments. The efficiency and quality of healthcare have high potential features as flexibility, adaptability, affinity, cost shrinkage, and high speed. This technology helps us to understand the specific risks related to security and privacy. This paper targets on a Healthcare information system based on ontology method. In particular, security and privacy challenges are analyzed in the proposed Ontology-based healthcare information system. Emergency medical services (EMS) are a type of emergency service dedicated to providing out-of-hospital acute medical care, transport to definitive care. Moreover, a functional infrastructure plan is provided to exhibit the unification between the proposed application architecture with the Internet of Things and ontology hierarchy

Hydrolyzed Polyacrylamide- Polyethylenimine- Dextran Sulfate Polymer Gel System as a Water Shut-Off Agent in Unconventional Gas Reservoirs

Technologies such as horizontal wells and multi-stage hydraulic fracturing have made ultra-low permeability shale and tight gas reservoirs productive but the industry is still on the learning curve when it comes to addressing various production issues. Some of the problems encountered while hydraulically fracturing these reservoirs are the absence of frac barriers, thinner shales and the increased presence of geological hazards. Induced vertical fractures sometimes extend to an underlying aquifer and become a conduit to the well. We have developed a low-concentration, low-viscosity and delayed-crosslink polymeric gel system as a water shutoff agent for hydraulically-fractured tight gas and shale reservoirs, where some fractures might connect to water rich zones. The system also is a significant improvement over traditional flowing gels for fracture water shutoff in conventional reservoirs because of these features. The gel uses high molecular weight hydrolyzed polyacrylamide (HPAM) at low polymer concentrations with a delayed organic crosslinker. This crosslinker is more environmentally benign and provides much longer gelation time and stronger final gels than comparable polymer loadings with chromium carboxylate crosslinkers at higher temperatures. The low viscosity system allows low-pressure extrusion of gelant into the narrow-aperture fractures present in unconventional gas reservoirs. The gelant can be pumped at low pressures due to lower polymer concentrations and delayed gelation point. This allows the potential to seal problem zones that are producing excess water even when the fractures conducting water have very narrow apertures. By impeding water production, the gel system developed here can effectively delay water loading thereby avoiding abandonment or installation of expensive equipment with increased operational costs, thus extending life and reserves of unconventional gas wells

Hybrid Boruvka - Johnson's Algorithm for Shortest Path Identification in Reconfigurable Microgrids

The concept of microgrid is implemented on a large scale in the present distribution system. Reconfiguration in microgrid predominantly occurs due to connection and disconnection of the distributed generators (DG) and loads. Due to frequent topology changes, conventional protection schemes may not be applicable in microgrid for efficient fault clearance. This paper proposes a Hybrid Borůvkas - Johnsons’s algorithm which detects the shortest path between the fault and the point of common coupling. This ensures that minimum portion of network disconnection occurs during fault clearance. This algorithm is tested and validated on 30-bus standard microgrid network

Impact of 2,4-D and Carbaryl on Growth, Pigment production and Nitrogen fixation of Anabena

Pesticides a class of new synthetic chemicals comprise herbicides, molluscicides, raticides, nematocides and insecticides have been constantly used in the fields to increase the crop production. Constant use of these chemicals tend to have a negative impact on soil microflora and the “ Beneficial nitrogen fixing organisms” face a challenge for survival in the soil habitat as they are exposed to these pesticides. Cyanobacteria are the most dominat primary producers amongst the photosynthetic microorganisms in the paddy field ecosystems by virtue of fixing both nitrogen as well as carbon dioxide. Anabena is a nitrogen fixing, heterocystous cyanobacterium used in paddy cultivation. Anabena was exposed to different concentrations of 2,4 – D and carbaryl and mixture of both for a period of 18 days.. Anabena exhibited a higher growth rate at low and high concentrations of 2,4 –D whereas it exhibited a lower growth rate in the presence of carbaryl and mixture of both. Since a drastic change was observed in growth rate, pigment and total nitrogen content in the presence of carbaryl and mixed pesticide solution, individual and combined effect of the above exerts a toxic effect on Anabena.Key words: Anabena, 2.4 –D , carbaryl, Nitrogen, chlorophyll 

Benchmarking medium voltage feeders using data envelopment analysis: a case study

Feeder performance evaluation is a key component in improving the power system network. Currently there is no proper method to find the performance of Medium Voltage Feeders (MVF) except the number of feeder failures. Performance benchmarking may be used to identify actual performance of feeders. The results of such benchmarking studies allow the organization to compare feeders with themselves and identify poorly performing feeders. This paper focuses on prominent benchmarking techniques used in international regulatory regime and analyses the applicability to MVFs. Data Envelopment Analysis (DEA) method is selected to analyze the MVFs. Correlation analysis and DEA analysis are carried out on different models and then the base model is selected for the analysis. The relative performance of the 32 MVFs of Western Province, Sri Lanka is evaluated using the DEA. Relative efficiency scores are identified for each feeder. Also the feeders are classified according to the sensitivity analysis. The results indicate that the DEA analysis may be conveniently employed to evaluate the performance of the MVFs. The evaluation is carried out once or twice a year with the MV distribution development plan in order to identify the performance of the feeders and to utilize the available limited resources efficiently

Research of Physical-Chemical and Ecological Characteristics of Ukkadam Lake Water Coimbatore District, Tamil Nadu, India

Degradation of lake water quality has been seen for many years, particularly in lakes close to urban areas with human activity. The goal of the current inquiry was to identify the various physical, chemical, and biological aspects of the surface water quality of several lakes in Coimbatore, India. The significance of the sampling points was considered when choosing them. Water samples were mostly taken from open wells in and around the Coimbatore district from the following sampling locations: Ukkadam Lake. The physical-chemical characteristics, such as total dissolved solids, pH, electrical conductivity, biochemical oxygen requirement, faeces coliforms, dissolved oxygen, and turbidity, Alkalinity, Sulphate, Nitrate, Phosphate, Chlorides. The findings indicated that lake water samples taken at several locations in and around Coimbatore city were above WHO criteria

STUDY OF DRUG COMPLIANCE AMONG DIABETIC PATIENTS

Diabetes is one of the most common ailments that the general population suffer in today’s world. Some are aware about their disturbing blood sugar levels and even understand the importance of appropriate control of the levels with the right medications. Some are aware and yet ignorant due to various causes. This study is aimed at evaluating the drug compliance among type 2 diabetes patients attending the review op of the department of Diabetology, KMCH. A study group of 100 patients attending the review OP were enrolled in the study. The compliance was assessed with the help of their diabetic OP records and a pretested questionnaire was used to further dig into the possible causes for non compliance. The study is broadly based on two main factors leading to non-compliance-causes for patients not getting medicines regularly and causes for patients not taking medicines regularly. These two factors were analyzed based on gender, age, duration of diabetes, co morbid illness, distance etc. The results have shown that 39% of the patients were not getting the medications regularly, out of which 33.3% did not get it due to sheer laziness,38.5% were forgetful and other serious illness hindered 28.2% of the patients from getting their medications. It was found that 55% of the patients took their medications regularly. Among those who took medications regularly,80.3% were regular and 15.4% were not regular in getting medications. Among  those who did not take medications regularly,66.7% claimed to be forgetful and 46.7% were non complaint as they did not have adequate knowledge about their medications.33.3% of the patients did not take it regularly as it gave them a feeling of wellbeing which tempted them to skip doses. Based on these significant data, we will be able to suggest ways and measures to improve the compliance on the treatment aspect. This would increase the desired therapeutic outcome and ultimately, on a broad aspect, it will reduce national health costs.Key words: drug compliance, therapeutic outcom