104 research outputs found
A virtualização é uma ciência da nuvem na atualidade?
Introduction: The present research was conducted in 2017 at Raiganj University, India. Cloud Computing and virtualization are significant concepts in today’s computing and information technology world. Cloud Computing is helpful for creating eco-friendly atmospheres, in other words, complete and healthy sustainability. Academic programs in the field of virtualization and Cloud Computing are still rare. This study seeks to learn more about such affairs.
Methods: Cloud Computing is actually a kind of virtualization which ultimately helps create virtual platforms, thus it is useful to learn about various educational programs in the field, the methods of general search engine have been used with proper keywords and titles.
Result: Cloud Computing and its wider uses resulted in academic programs, centers and departments in many countries around the world. Cloud Computing forms a tool and mechanism of virtualization for complete scientific domain nowadays. Virtualization has become a field and an available study program in international universities and also in Indian academics.
Conclusions: This paper highlights several aspects of Cloud Computing from the beginning to growing nature as a field of study with academic and techno-managerial points of view.
Originality: In major indexing agencies, studies on Cloud Computing are rarely available in Indian context.
Limitation: The study concerned a specific area in India and used search methods conducted from July to September 2017. After that period, work has not been included and analyzed in the study.Introducción: el presente trabajo de investigación se llevó a cabo en el 2017 en la Universidad de Raiganj, India. La computación en nube y la virtualización son conceptos importantes en el mundo de la informática y la tecnología de la información actual. La computación en la nube es útil para crear atmósferas ecológicas, en otras palabras, una sostenibilidad completa y saludable. Los programas académicos en el campo de la virtualización y la computación en la nube aún son escasos. Este estudio busca aprender más sobre tales asuntos.
Métodos: la computación en la nube (Cloud Computing) es un tipo de virtualización que ayuda a crear plataformas virtuales, por lo que ahora es útil en diferentes estancias, y para aprender sobre programas educativos en el campo, los métodos de búsqueda general se han hecho con títulos y palabras clave adecuadas.
Resultado: la computación en la nube y sus usos más amplios dieron como resultado programas académicos, centros y departamentos en muchos países alrededor del mundo. La computación en la nube genera una herramienta y un mecanismo de virtualización para un dominio científico completo en la actualidad. La virtualización se ha convertido en un campo y un programa de estudio disponible en universidades internacionales y también entre académicos de la India.
Conclusiones: este documento destaca varios aspectos de la computación en la nube desde sus inicios, incluyendo su naturaleza en crecimiento como campo de estudio con puntos de vista académicos y tecno-gerenciales.
Originalidad: en las principales agencias de indexación, los estudios sobre computación en la nube raramente están disponibles en el contexto de la India.
Limitación: el estudio se refiere a un sector específico de India y se utilizaron métodos de búsqueda realizados entre julio y septiembre de 2017, no se incluye y analizan trabajos posteriores en este estudioIntrodução: esta pesquisa foi levada a cabo em 2017, na Universidade de Raiganj, na Índia. A computação na nuvem e a virtualização são conceitos importantes no mundo atual da informática e da tecnologia da informação. A computação na nuvem é útil para criar atmosferas ecológicas, em outras palavras, uma sustentabilidade completa e saudável. Os programas acadêmicos no campo da virtualização e da computação na nuvem ainda são escassos. Este estudo busca aprender mais sobre esses assuntos.Métodos: cloud computing é um tipo de virtualização que ajuda a criar plataformas virtuais, por isso, agora, é útil em diferentes áreas e para aprender sobre os programas educativos no campo, os métodos de busca geral têm sido utilizados com títulos e palavras-chave adequadas.Resultados: a computação na nuvem e os seus usos mais amplos deram como resultado programas acadêmicos, centros e departamentos em muitos países ao redor do mundo. A computação na nuvem gera uma ferramenta e um mecanismo de virtualização para um domínio científico completo na atualidade. A virtualização tornou-se um campo e um programa de estudo disponível em universidades internacionais e, também, entre acadêmicos da Índia.Conclusões: este documento destaca vários aspectos da computação na nuvem desde o princípio, inclusive a sua natureza em crescimento como campo de estudo com pontos de vista acadêmicos e tecnológicos gerenciais.Originalidade: nas principais agências de indexação, os estudos sobre computação na nuvem raramente estão disponíveis no contexto da Índia.Limitação: o estudo se refere a uma área específica na Índia e foram utilizados métodos de busca realizados entre julho e setembro de 2017, um trabalho posterior não foi incluído nem analisado no estud
Evaluation of analgesics use in orthopedic department at tertiary care hospital in Bareilly, Uttar Pradesh, India
Background: Analgesics including nonsteroidal anti-inflammatory drugs (NSAIDs) are commonly prescribed group of drugs in clinical practice for the management of pain and inflammation. This study was carried out to evaluate the prescribing pattern of analgesics in orthopedic in-patient department of tertiary care teaching hospital at Bareilly (Uttar Pradesh).Methods: This hospital based cross-sectional study was carried out for 3 months from March to May 2015. Collected data included age, sex, diagnosis and line of management during the study. The generic name and the average cost of treatment per patient were evaluated using Indian Drug Review, 2014. The prescribed drugs were assessed with respective National Model List of Essential Medicines (NLEM), 2011 and the rationality of prescriptions was determined using the World Health Organization indicators of drug utilization. The patients' details were recorded in a data collection form and results were analysed by descriptive statistics.Results: Out of 400 patients, 246 were male and 154 were female. The average number of analgesic per prescription was 1.48. In this study, 52.5% of patients had received single analgesic. Diclofenac was the most commonly prescribed analgesic (45.39%). During hospitalization, majority of the patients have received parenteral preparation. Gastro protective agents and antimicrobials were frequently prescribed along with analgesics. Out of 584 analgesics prescribed, 356 (60.96%) were from the NLEM, India. Furthermore, 276 (47.26%) analgesics were prescribed by generic name. The average cost of treatment per patient was 2050.70 INR. Utilization of analgesic in terms of defined daily dose/100 bed-days was 102.06.Conclusions: The percentages of analgesics prescribing from NLEM and the use of analgesic by generic name were found satisfactory
Spiking Activity of a LIF Neuron in Distributed Delay Framework
Evolution of membrane potential and spiking
activity for a single leaky integrate-and-fire (LIF) neuron in
distributed delay framework (DDF) is investigated. DDF provides
a mechanism to incorporate memory element in terms of delay
(kernel) function into a single neuron models. This investigation
includes LIF neuron model with two different kinds of delay kernel
functions, namely, gamma distributed delay kernel function and
hypo-exponential distributed delay kernel function. Evolution
of membrane potential for considered models is studied in terms
of stationary state probability distribution (SPD). Stationary
state probability distribution of membrane potential (SPDV)
for considered neuron models are found asymptotically similar
which is Gaussian distributed. In order to investigate the effect
of membrane potential delay, rate code scheme for neuronal
information processing is applied. Firing rate and Fano-factor
for considered neuron models are calculated and standard LIF
model is used for comparative study. It is noticed that distributed
delay increases the spiking activity of a neuron. Increase in
spiking activity of neuron in DDF is larger for hypo-exponential
distributed delay function than gamma distributed delay function.
Moreover, in case of hypo-exponential delay function, a LIF neuron
generates spikes with Fano-factor less than 1
An IoT Based Predictive Connected Car Maintenance Approach
Internet of Things (IoT) is fast emerging and becoming an almost basic necessity in general life. The concepts of using technology in our daily life is not new, but with the advancements in technology, the impact of technology in daily activities of a person can be seen in almost all the aspects of life. Today, all aspects of our daily life, be it health of a person, his location, movement, etc. can be monitored and analyzed using information captured from various connected devices. This paper discusses one such use case, which can be implemented by the automobile industry, using technological advancements in the areas of IoT and Analytics. ‘Connected Car’ is a terminology, often associated with cars and other passenger vehicles, which are capable of internet connectivity and sharing of various kinds of data with backend applications. The data being shared can be about the location and speed of the car, status of various parts/lubricants of the car, and if the car needs urgent service or not. Once data are transmitted to the backend services, various workflows can be created to take necessary actions, e.g. scheduling a service with the car service provider, or if large numbers of care are in the same location, then the traffic management system can take necessary action. ’Connected cars’ can also communicate with each other, and can send alerts to each other in certain scenarios like possible crash etc. This paper talks about how the concept of ‘connected cars’ can be used to perform ‘predictive car maintenance’. It also discusses how certain technology components, i.e., Eclipse Mosquito and Eclipse Paho can be used to implement a predictive connected car use case
A Novel Approach on Visual Question Answering by Parameter Prediction using Faster Region Based Convolutional Neural Network
Visual Question Answering (VQA) is a stimulating process in the field of Natural Language Processing (NLP) and Computer Vision (CV). In this process machine can find an answer to a natural language question which is related to an image. Question can be open-ended or multiple choice. Datasets of VQA contain mainly three components; questions, images and answers. Researchers overcome the VQA problem with deep learning based architecture that jointly combines both of two networks i.e. Convolution Neural Network (CNN) for visual (image) representation and Recurrent Neural Network (RNN) with Long Short Time Memory (LSTM) for textual (question) representation and trained the combined network end to end to generate the answer. Those models are able to answer the common and simple questions that are directly related to the image’s content. But different types of questions need different level of understanding to produce correct answers. To solve this problem, we use faster Region based-CNN (R-CNN) for extracting image features with an extra fully connected layer whose weights are dynamically obtained by LSTMs cell according to the question. We claim in this paper that a single R-CNN architecture can solve the problems related to VQA by modifying weights in the parameter prediction layer. Authors trained the network end to end by Stochastic Gradient Descent (SGD) using pretrained faster R-CNN and LSTM and tested it on benchmark datasets of VQA
Assessment of rainwater quality in industrial area of rural Panipat (Haryana), India
This study was conducted in Panipat industrial area for the evaluation rain water quality and indirectly the air pollution load created by industries in the vicinity. The rain water quality of first rain was assessed for the evaluation of air pollution load of region. Selected physico-chemical characteristics like temperature, pH (6.23-6.85), TDS (105-187 mg L-1), DO (4.2-5.6 mg L-1), Free CO2 (0.8 mg L-1), Pb (0.09 mg L-1), Fe (0.085-0.132 mg L-1), sulphate (121.2-131.8 mg L-1), silica (3.51-7.26 mg L-1), turbidity (11-19 NTU), total hardness (81-120 mg L-1), chloride (3.20-6.75 mg L-1), BOD (2-4 mg L-1), and COD (14-31 mg L-1) were detected for the evaluation of pollution load in rainwater. The present study revealed that the water quality of first rain was found highly polluted in comparison to second rain. The difference between first heavy rain and second rain was found significant and in favour of increasing air pollution in the industrial area. The trace amount of chloride, silica, lead, iron, sulphate, free carbon dioxide was found in first heavy rain of the region while in the second rain all these were found in very less quantity. The difference in the concentrations of pollutants in rainwater gives the basic idea about the air pollution load of the vicinity. In fact, this is a novel technique to monitor air pollution load of any particular area using rainwater quality monitoring
Nuevo marco para utilizar la minería de datos y reglas de asociación para la clasificación de la gravedad de accidentes de tráfico
Introduction: Traffic accidents are an undesirable burden on society. Every year around one million deaths and more than ten million injuries are reported due to traffic accidents. Hence, traffic accidents prevention measures must be taken to overcome the accident rate. Different countries have different geographical and environmental conditions and hence the accident factors diverge in each country. Traffic accident data analysis is very useful in revealing the factors that affect the accidents in different countries. This article was written in the year 2016 in the Institute of Technology & Science, Mohan Nagar, Ghaziabad, up, India.
Methology: We propose a framework to utilize association rule mining (arm) for the severity classification of traffic accidents data obtained from police records in Mujjafarnagar district, Uttarpradesh, India.
Results: The results certainly reveal some hidden factors which can be applied to understand the factors behind road accidentality in this region.
Conclusions: The framework enables us to find three clusters from the data set. Each cluster represents a type of accident severity, i.e. fatal, major injury and minor/no injury. The association rules exposed different factors that are associated with road accidents in each category. The information extracted provides important information which can be employed to adapt preventive measures to overcome the accident severity in Muzzafarnagar district.Introducción: los accidentes de tránsito son una carga indeseable para la sociedad. Cada año se reportan alrededor de un millón de muertes y más de diez millones de lesiones debido a accidentes de tráfico. Por lo tanto, se deben implementar medidas de prevención de accidentes de tráfico para superar la tasa de accidentalidad. Los países tienen diferentes condiciones geográficas y ambientales y, por ello, las variables que inciden varían en cada país. El análisis de los datos de accidentes de tráfico es muy útil para revelar los factores o variables que inciden en la accidentalidad en diferentes países. Este artículo fue escrito en el 2016 en el Instituto de Tecnología y Ciencia, Mohan Nagar, Ghaziabad, UP, India.
Metodología: proponemos un marco para utilizar la minería de datos y reglas de asociación (arm) para la clasificación de severidad de los datos de accidentes de tráfico obtenidos de registros policiales en eldistrito de Mujjafarnagar, Uttarpradesh, India
Resultados: los resultados revelan ciertamente algunos factores ocultos que se pueden aplicar para entender las variables detrás de la accidentalidad de tráfico en esta región.
Conclusiones: el marco permite establecer tres categorías en el conjunto de datos que representan el tipo de gravedad del accidente: fatal, lesiones graves, y lesiones menores o inexistentes. Las reglas de asociación expusieron diferentes factores relacionados con los accidentes de tráfico en cada categoría. Los datos extraídos proporcionan información importante que se puede emplear para adaptar las medidas preventivas para superar la gravedad de los accidentes de tráfico en el distrito de Muzzafarnagar
Impact of industrial effluents on ground water and soil quality in the vicinity of industrial area of Panipat city, India
The present paper is aimed towards the assessment of heavy metal contamination of agricultural soil due to irrigation with contaminated ground water affected by textile industrial effluents at Panipat city in India. Samples of ground water and irrigated soils from textile industrial area were analyzed for various heavy metals, viz. Mn, Ni, Fe, Cu, Cd, Pb and Zn, using Atomic Absorption Spectrophotometry. Metal transfer factors from ground water to irrigated agricultural soil and from soil to ground water were calculated for heavy metals. The findings deal with the distribution of heavy metals in ground water of industrial area and irrigated agricultural soil. Transfer factors for heavy metals from effluent to ground water were observed to be 0.436, 1.180, 6.461, 2.401, 2.790, 3.178 and 0.634 for Cd, Cu, Fe, Mn, Ni, Pb and Zn respectively. These were found to be very high from ground water to agriculture soil due to the natural shale value of heavy metals in soil system. Thus, untreated industrial effluents can cause an environmental threat to ground water resources and affects soil quality and agricultural plant productivity
Análisis comparativo sobre modelos de redes neuronales profundas para la detección de ciberbullying en redes sociales
Social media usage has been increased and it consists of both positive and negative effects. By considering the misusage of social media platforms by various cyberbullying methods like stalking, harassment there should be preventive methods to control these and to avoid mental stress. These extra words will expand the size of the vocabulary and influence the performance of the algorithm. Therefore, we come up with variant deep learning models like LSTM, BI-LSTM, RNN, BI-RNN, GRU, BI-GRU to detect cyberbullying in social media. These models are applied on Twitter, public comments data and performance were observed for these models and obtained improved accuracy of 90.4%.Introducción: el uso de las redes sociales se ha incrementado y tiene efectos tanto positivos como negativos. Al considerar el uso indebido de las plataformas de redes sociales a través de varios métodos de acoso cibernético, como el acecho y el acoso, debe haber métodos preventivos para controlarlos y evitar el estrés mental.Problema: estas palabras adicionales ampliarán el tamaño del vocabulario e influirán en el rendimiento del algoritmo.Objetivo: Detectar el ciberacoso en las redes sociales.Metodología: en este documento, presentamos variantes de modelos de aprendizaje profundo como la memoria a largo plazo (LSTM), memoria bidireccional a largo plazo (BI-LSTM), redes neuronales recurrentes (RNN), redes neuronales recurrentes bidireccionales (BI-RNN), unidad recurrente cerrada (GRU) y unidad recurrente cerrada bidireccional (BI-GRU) para detectar el ciberacoso en las redes sociales.Resultados: El mecanismo propuesto ha sido realizado, analizado e implementado sobre datos de Twitter con Accuracy, Precision, Recall y F-Score como medidas. Los modelos de aprendizaje profundo como LSTM, BI-LSTM, RNN, BI-RNN, GRU y BI-GRU se aplican en Twitter a los datos de comentarios públicos y se observó el rendimiento de estos modelos, obteniendo una precisión mejorada del 90,4 %.Conclusiones: Los resultados indican que el mecanismo propuesto es eficiente en comparación con los es-quemas del estado del arte.Originalidad: la aplicación de modelos de aprendizaje profundo para realizar un análisis comparativo de los datos de las redes sociales es el primer enfoque para detectar el ciberacoso.Restricciones: estos modelos se aplican solo en comentarios de datos textuales. El trabajo propio no se ha concentrado en datos multimedia como audio, video e imágenes
Conceptual Model for Smart Cities: Irrigation and Highway Lamps using IoT
Keeping in mind the need to preserve energy as well as utilize the available at its best the need was felt to develop a module that would be able to sort out the problem where resources such as water and electricity were wasted, in urban as well as rural area. Resource (electricity) was wasted as beside the point operation of Highway & High Mast Lamp; while wastage of water followed by improper trends and methodologies imparted for watering of city park, road side plantation and highway plantation. Thus as per Energy survey statistics of a City (Lucknow, India) it was found that major portion of resources (water and electricity) were being wasted due to negligent activities of officials who were in charge of resource management. So to facilitate energy saving trends and to completely modernize it to autonomous system, module below is proposed which incorporates modern technological peripheral and has its base ingrained in IoT (Internet of Things) which when put into consideration would result in large scale resource and energy saving.This developed module incorporates the peripherals such as Arduino, Texas Instruments ultra low power kits etc. in accordance with software technology including Lab View which help to monitor as well as control the various operation from the base station, located far away from the site. Lab View Interface interacts with all the module located at various city parks, subways and highway lighting modules. Later below in several section a detailed pattern and application frame has been put up
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