Low Cost Device for Charging Mobile Phone using Another Smartphone

Mobile has been and will always remain one of the best companions for any human being. Mobile phones are considered as the live example of the advancement in technology on a daily basis. This era is marked by our complete dependence on this technology. The growing technology has introduced mobile phone, which plays an important role in communication. Since mobile phones have been made to be with the user all day and to carry out all the basis and high-performance task as per the demand of the user, the batteries need to be charged multiple times during a day. This imposes a burden on the user to carry a power bank while travelling; at times it becomes difficult if the power bank battery also drains out. This paper presents a small technique which may reduce this problem. The major components of the design are a capacitor of 2200 μF at 5.63 V and LED 1.5 V. The experimental data shows that the charging level of a mobile battery of 2100 mAh can be enhanced from 10-19 % in 35 minutes by consuming only 10% of the total energy of the other smart phone of battery 4000 mAh. Another experimental data shows that the charging level of a mobile battery of 2000 mAh can be enhanced from 14-37 % in 60 minutes by consuming only 20% of the total energy of the other smart phone of battery 4000 mAh. This low cost and simple designed USB On-the-Go (OTG) extension can now replace the necessity of carrying a power bank while travelling, which is expensive as compared to the above proposed technique as well.Citation: Gupta, V., Aggarwal, V., Sharma, K., and Sharma, N. (2018). Low Cost Device for Charging Mobile Phone using Another Smartphone. Trends in Renewable Energy, 4, 77-82. DOI: 10.17737/tre.2018.4.3.005

Offline Handwriting Recognition Using Genetic Algorithm

In this paper, a new method for offline handwriting recognition is presented. A robust algorithm for handwriting segmentation has been described here with the help of which individual characters can be segmented from a word selected from a paragraph of handwritten text image which is given as input to the module. Then each of the segmented characters are converted into column vectors of 625 values that are later fed into the advanced neural network setup that has been designed in the form of text files. The networks has been designed with quadruple layered neural network with 625 input and 26 output neurons each corresponding to a character from a-z, the outputs of all the four networks is fed into the genetic algorithm which has been developed using the concepts of correlation, with the help of this the overall network is optimized with the help of genetic algorithm thus providing us with recognized outputs with great efficiency of 71%

Quantum-Inspired Evolutionary Algorithms for Neural Network Weight Distribution: A Classification Model for Parkinson\u27s Disease

Parkinson’s Disease is a degenerative neurological disorder with unknown origins, making it impossible to be cured or even diagnosed. The following article presents a Three-Layered Perceptron Neural Network model that is trained using a variety of evolutionary as well as quantum-inspired evolutionary algorithms for the classification of Parkinson\u27s Disease. Optimization algorithms such as Particle Swarm Optimization, Artificial Bee Colony Algorithm and Bat Algorithm are studied along with their quantum-inspired counter-parts in order to identify the best suited algorithm for Neural Network Weight Distribution. The results show that the quantum-inspired evolutionary algorithms perform better under the given circumstances, with qABC offering the highest accuracy of about 92.3%. The presented model can be used not only for disease diagnosis but is also likely to find its applications in various other fields as well

Urbanisation Effect on Hydrological Response: A Case Study of Asan River Watershed, India

Human being keeps on modifying the environment especially land use/land cover (LULC), in pursuance of excel, comfort and development. The subsequent impact of urbanization to the environment, especially land cover change, now occurs on scales that significantly affect hydrologic variations. The altering environment makes it necessary to understand and quantify various hydrological components for efficient water resource management. Therefore, in the present study, an attempt was  made to study the impact of LULC change on runoff generation potential. Asan River watershed, which lies in Dehradun, capital of newly created Uttarakhand State, India, is selected as study region. A huge industrialization is been taken place within this watershed immediately after declaration of state in year 2000. Initially, LULC change detection analysis was carried out by simple LULC class area difference between two years under consideration i.e. 2000 and 2010. The hydrological simulation using variable infiltration capacity macro-scale hydrological model depicted increase in runoff after urbanization took place. Keywords: Land use land cover change, Urbanization, Impact assessment, hydrological modeling, variable infiltration capacity model, runoff potentia

The effectiveness of MAE pre-pretraining for billion-scale pretraining

This paper revisits the standard pretrain-then-finetune paradigm used in computer vision for visual recognition tasks. Typically, state-of-the-art foundation models are pretrained using large scale (weakly) supervised datasets with billions of images. We introduce an additional pre-pretraining stage that is simple and uses the self-supervised MAE technique to initialize the model. While MAE has only been shown to scale with the size of models, we find that it scales with the size of the training dataset as well. Thus, our MAE-based pre-pretraining scales with both model and data size making it applicable for training foundation models. Pre-pretraining consistently improves both the model convergence and the downstream transfer performance across a range of model scales (millions to billions of parameters), and dataset sizes (millions to billions of images). We measure the effectiveness of pre-pretraining on 10 different visual recognition tasks spanning image classification, video recognition, object detection, low-shot classification and zero-shot recognition. Our largest model achieves new state-of-the-art results on iNaturalist-18 (91.3%), 1-shot ImageNet-1k (62.1%), and zero-shot transfer on Food-101 (96.2%). Our study reveals that model initialization plays a significant role, even for web-scale pretraining with billions of images

Gangotri glacier dynamics from multi-sensor SAR and optical data

The present study has analyzed dynamics of Gangotri glacier using multiple remote sensing (RS) datasets and ground based observations. Interferometric Synthetic Aperture Radar (InSAR) data pairs from European Remote Sensing satellite (ERS 1/2) tandem pair for spring of 1996, Sentinel-1 SAR pairs and Japanese's Advance Land Observation System (ALOS) PALSAR-2 SAR data for Spring of 2015 were used to derive glacier-surface velocity at seasonal time scale using Differential InSAR (DInSAR) techniques. Bi-static TanDEM-X (Experimental) data was used for the 1st time to estimate glacier surface elevation changes for a period of 22, 44, 88 days during summer of 2012 using InSAR techniques in this study. Annual glacier velocity was also estimated using temporal panchromatic data of LANDSAT-5 (30 m), LANDSAT-7/8 (15 m), Sentinel-2 (10 m) and Indian Remote Sensing Satellite IRS-1C/1D panchromatic (5 m) data during 1998–2019 with feature tracking approach. This study has estimated glacier surface velocity and surface elevation changes for the major parts of Gangotri glacier and its tributary glaciers using medium to high resolution optical and SAR datasets, at annual and seasonal time scale, which is an improvement over earlier studies, wherein snout based glacier recession or only main glacier velocities were reported. The velocity and slope were used to assess glacier-ice thickness distribution using Glabtop-2, slope dependent and laminar flow based methods over the Gangotri group of glaciers. The estimated ice thickness was estimated in the range of 58–550 m for the complete glacier while few small areas in middle &amp; upper regions carry higher thickness of about 607 m. The estimated glacier-ice thickness was found in the range of 58–67 m at the snout region. The estimation was validated using 2014 field measurements from Terrestrial Laser Scanner (TLS) for the first time and correlation was found to be 0.799 at snout of the glacier.</p

Constraints on cosmic strings using data from the first Advanced LIGO observing run

Cosmic strings are topological defects which can be formed in grand unified theory scale phase transitions in the early universe. They are also predicted to form in the context of string theory. The main mechanism for a network of Nambu-Goto cosmic strings to lose energy is through the production of loops and the subsequent emission of gravitational waves, thus offering an experimental signature for the existence of cosmic strings. Here we report on the analysis conducted to specifically search for gravitational-wave bursts from cosmic string loops in the data of Advanced LIGO 2015-2016 observing run (O1). No evidence of such signals was found in the data, and as a result we set upper limits on the cosmic string parameters for three recent loop distribution models. In this paper, we initially derive constraints on the string tension Gμ and the intercommutation probability, using not only the burst analysis performed on the O1 data set but also results from the previously published LIGO stochastic O1 analysis, pulsar timing arrays, cosmic microwave background and big-bang nucleosynthesis experiments. We show that these data sets are complementary in that they probe gravitational waves produced by cosmic string loops during very different epochs. Finally, we show that the data sets exclude large parts of the parameter space of the three loop distribution models we consider

Possible nitric oxide mechanism in the protective effect of hesperidin against ischemic reperfusion cerebral injury in rats

609-618Stroke is the third leading cause of death and disability around the globe. The aim of the present investigation was to evaluate the protective effect of hesperidin and its nitric oxide mechanism against cerebral ischemia reperfusion injury. Bilateral common carotid artery occlusion for 30 min followed by 24 h reperfusion was given to induce ischemia in rats. Animals were pretreated with hesperidin (50 and 100 mg/kg, po) for 7 days. Various behavioural tests, oxidative stress parameters, endogenous antioxidant system, antioxidant enzyme activity and mitochondrial enzyme complex (I, II, III and IV) dysfunctions in cortex and striatum were assessed subsequently. Hesperidin (50 and 100 mg/kg) significantly improved neurobehavioral alterations (neurological score, locomotor activity, resistance to lateral push and hanging wire latency), attenuated oxidative damage, restored antioxidant and mitochondrial complex enzyme activities in cortex and in striatum regions of the brain as compared to their respective controls. L-arginine (100 mg/kg) or L-NAME (10 mg/kg) pretreatment with lower dose of hesperidin (50 mg/kg) significantly reversed or potentiated its protective effect, respectively which was significant as compared to hesperidin (50 mg/kg). The results highlight the involvement of nitric oxide mechanism in the protective effect of hesperidin against ischemia reperfusion injury induced alterations

Expression of Neuron-Specific Enolase and S-100 in the Ileum and Ileocecal Junction in the Human Fetuses at Various Gestational Ages

Background and Objectives: The purpose of this study was to study the histogenesis and neuroanatomy of the human fetal ileum and ileocecal junction at various gestational ages (15, 18, 20, 28, and 32 weeks) using neuron-specific enolase (NSE) as a neuronal marker and S-100 as a glial marker for the enteric nervous system. Materials and Methods: For this study, five aborted normal fetuses were obtained from the fetal repository of Department of Anatomy. The ileocecal part of the small intestine of these fetuses was dissected, processed, and sectioned and stained with hematoxylin and eosin and cresyl violet. Immunohistochemistry was performed using antibodies to NSE and S-100 and observed under a BX61 Olympus microscope using a DP71 camera. Results: The myenteric and submucosal plexuses of terminal ileum and ileocecal junction show immunoreactivity for both NSE and S-100 by 20 weeks. The development of myenteric plexus is more advanced than submucosal plexus. The immature neurons at 15 weeks progressively mature with distinct cell processes at 32 weeks. The mature ileocecal junction is composed of two outer circular muscle layers and a single inner longitudinal muscle layer. At 32 weeks, ileocecal valve was visualized. Interpretation and Conclusions: Our study provides the morphological evidence of the immunoreactivity in the ganglion plexus and the development of ileum and ileocecal junction at different developmental stages. It also substantiates the concept of ileocecal junction being an intussusception of ileum into the cecum