Volume 10 | Issue 6 |

 Abstract

A simple and efficient algorithm is proposed for solving the economic dispatch problem of power systems with valve point discontinuities employing a particle swarm optimization-based approach. Evolutionary methods such as GA and PSO are known to perform better than conventional gradient-based optimization methods for nonconvex optimization problems. The performance of the proposed method has been compared with Real coded genetic algorithm (RGA) results for validation. The effectiveness of the algorithm has been tested on a test system having three generating units.

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 Keywords

ELD,PSO,Valve point loading effect

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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atheism as crime, cat as metaphor of free will, religion as existence, humanism as religion

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

User,Event Management, Events, Admin

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This project deals with various types of hazards identification & finding a risk assessment (HIRA) and identifying best safety practices on conveyors including conveyor guarding, hazardous energy isolation and visual inspection procedures for industries that utilize conveyor systems. The safe working operation of conveyors needs to identify the hazards, assess the associated risks and bring the risks to tolerable level on a continuous basis. Each year, physical contact with machines and powered equipment accounts for a significant number of life-altering injuries and fatalities. A number of these incidents involve conveyor systems. The majority of these incidents occur during maintenance activities with conveyors still in operation and danger zones unprotected. A risk assessment is an important step in protecting the conveyors and humans from such conditions. It helps us to focus on the risks that really have the potential to cause harm. Risk classification by probability and severity can be performed by using a risk assessment class. Then risk level is assigned to each hazard for identifying required Preventive measures to minimize the risk or eliminate the Hazard. Preventive measures should be implemented in order for work on or near conveyors to be performed safely. Right from the design stage, worker exposure to hazards should be controlled by reducing the frequency of conveyor clean-ups, conveyor maintenance, removal of jams, etc. This project to best safety practices suggests possible preventive measures, but it is by no means exhaustive. In many situations, hazards must be analysed before any preventive measures are implemented.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

hazards, risk assessment, safety practices, conveyors, safe guards

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Stock market investment which is one of the most complex and difficult and risky business to do. Stock market is very uncertain because the prices of stocks keep fluctuating every time. This paper is based on the demand for stock market price prediction and the problems it faces now a days. We compared and analyzed various types of neural network prediction methods and finally selected LSTM (long short-term memory) neural network for predicting stock price. Historical information is very important to investors for making investment decisions. Past studies have used opening price and closing price as key new predicators of financial markets, but extreme maxima and minima may provide additional information about future price behavior. Its main principle is to discover the role of time series through analyzing the historical information of the stock market, and to deeply explore its internal rules through the selective memory advanced deep learning function of LSTM neural network model, so as to achieve the prediction of stock price trend.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Stock Price, LSTM, Deep Learning

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This project presents about the method of optimizing energy from the renewable energy resources (RES) like solar and wind energy and it is used for the home appliances and EV (Electric vehicle) load. The energy produced from RES. The voltage produced from RES is boosted by an dc-dc boost converter and inverted to a maximum point using an dc-ac Inverter. There are two types of batteries are used in the system one is used to store energy produced from RES, and another one is used for battery energy management system (BEMS), which stores the excess energy produced, from the RES given to the loads (home appliances) and also given for the EV load. Arduino microcontroller plays a major role of controlling the system. LCD display is used to display the voltage produced from solar and wind separately and percentage of battery voltage, and energy distributed to the EV load. IOT (internet of things) is deployed to show the outputs shown in the LCD display can be showed from anywhere using our mobile phones.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Renewable energy resource, Energy optimization, energy management.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study was conducted on 729 teachers working in Government Primary schools in District Bilaspur, Himachal Pradesh. The aim of study was to assess the effect of ego strength and self actualization on burn out. The standardized questionnaires were used to assess the ego strength, self actualization and burn out of the Teachers. The findings reveals that the mean/average scores of ego strength, self actualization and burn out of teachers were 19.72, 156.12 and 54.93(Emotional exhaustion = 26.61, Depersonalization=13.28 and Personal accomplishment=21.04) and there was no significant difference between male and female teachers as well as teachers belonging to rural and urban background on ego strength, self actualization and burn out(Emotional exhaustion, Depersonalization and Personal accomplishment). Results also reveals that there was a negative and significant relationship between ego strength and burn out (-.336**) as well as its components (-.354** with emotional exhaustion, -.199** with depersonalization and -.299** with personal accomplishment) and results also further reveals that there was a negative and significant relationship between self actualization and burn out (-.145*) as well as its components (-.135* with emotional exhaustion, -.111* with depersonalization and -.128* with personal accomplishment). The results of multiple regression analyses reveals that ego strength and self actualization were considered for the prediction of 13.6% emotional exhaustion, 4.9% depersonalization and 10% personal accomplishment and 12.6% overall burn out.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Ego Strength, Self Actualization, Burnout, Emotional exhaustion, Depersonalization and Personal accomplishment

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This project mainly focused on foreign currency exchange rate prediction and we have used 2 neural networks which are used in times series prediction such as Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU). Combining these two neural networks, we also used the Facebook Prophet time series algorithm. So all these algorithms make the hybrid model such that it will be more convenient to forecast the prediction of the currency rates than in previous models.

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 Keywords

LSTM, GRU, Prophet, Datasets, Forex trading

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid increment in internet usage has also resulted in bulk generation of text data . Therefore, investigation of new techniques for automatic classification of textual content is needed as manually managing unstructured text is challenging. The main objective of text classification is to train a model such that it should place an unseen text into correct category. In this study, text classification was performed using the Doc2vec word embedding method on the Turkish Text Classification 3600 (TTC-3600) dataset consisting of Turkish news texts and the BBC-News dataset consisting of English news texts. As the classification method, deep learning- based CNN and traditional machine learning classification methods Gauss Naive Bayes (GNB), Random Forest (RF), Naive Bayes (NB) and Support Vector Machine (SVM) are used. In the proposed model, the highest result was obtained as 94.17% in the Turkish dataset and 96.41% in the English dataset in the classification made with CNN.

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 Keywords

Turkish Text Classification, Support Vector Machine, Naive Bayes, Random Forest, Gauss Naive Bayes.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The present work involves waste plastic-recycling-regeneration-and-utilization. In this process the waste plastic is recycled and converted as fuel. The waste plastic has to be recycled because it is non-disposable and has a series impact on environmental hazard. To overcome this effect, the work has to be focused to reduce the major issue of waste plastics by converting them into usable products such as fuel. As a feasible solution for plastic recycling, the pyrolysis is one of the process of transforming waste plastic into fuels. The synthesis of fuel using pyrolysis involves in degradation of the polymeric materials by heating them in the absence of oxygen and in the presence of a catalyst. In this process, different oil samples are produced using different catalyst under different reaction conditions from waste plastics. The synthesized oil samples are subjected to a parametric study based on the oil yield, selectivity of the oil, fuel properties, and reaction temperature. The performance analysis is based on chemical compositions of waste plastics and generated oil samples. These results obtained are to decrease the plastic waste and high calorific value of fuel which is obtained from the waste plastics by high heat combustion process. The fuel synthesis procedure based on selection of raw material, pre-treatment, pyrolysis-process, analysis, testing, filtration and purification.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Plastic waste, Pyrolysis, Fuel synthesis, Hydrocarbons

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Creative Commons Attribution 4.0 and The Open Definition