Asian Journal of Convergence in Technology
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Green Computing: An Eco-friendly Technique
Get PDFGreen computing, the study and practice of efficient and ecofriendly computing resources Green computing i.e. green technology, is the environmentally sustainable to use of computers and devices. The principle behind energy efficient coding is to save power by getting software to make less use of the hardware, rather than continuing to run the same code on hardware that uses less power. It has also given utmost attention to minimization of e-waste and use of non-toxic materials in preparation of e-equipments. We use Green Computing because it- reduced energy usage from green computing techniques translates into lower carbon dioxide emissions, stemming from a reduction in the fossil fuel used in power plants and transportation. Conserving resources means less energy is required to produce, use, and dispose of products, saving energy and resources saves money. Green computing even includes changing government policy to encourage recycling and lowering energy use by individuals and businesses. In this paper focus on some aspects of green computing i.e . approaches and implementation
Performance Analysis and Comparison of Complex LMS, Sign LMS and RLS Algorithms for Speech Enhancement Application
Get PDFRecent developments in the area of adaptive signal processing have advanced massively due to increase in powerful and cost effective digital signal processors with low cost memory chips. The uses of speech processing system for voice communication and recognition task have become more and more common. These factors lead to promote the use of digital signal processing technology for implementation of emerging applications. The process to remove unwanted interference is common and occurs in many situations. The technique of adaptive filtering is a method by which signal enhancement or noise reduction can be accomplished. An adaptive filter self adjusts its transfer function according to an optimizing algorithm. In this paper we carried out the analysis and experimentation to study the existing adaptive filter algorithms and their application for speech enhancement. The paper describes Least Mean Square (LMS) algorithm and Recursive Least Square (RLS). The complex Least Mean Square (CLMS) algorithm and the modification in CLMS lead to Sign Least Mean Square (SLMS) algorithm. The Sign-Sign Least Mean Square algorithm (SSLMS) is also considered for comparison. Normalization operation is performed on the sample which leads to evolution of NLMS algorithm. The experimentation revels that LMS have fast convergence than RLS. The computational complexity of RLS is very high as compared to LMS
An Android Java Application for Evaluating Physico-chemical Properties of a Protein Sequence
Get PDFThe study describes several physicochemical properties of amino acids which can help to study biological functions, profiles and folding of proteins. The java based tool calculates seven different statistical parameters namely Isoelectric Point, Molecular Weight, Aliphatic index, GRAVY (Grand average of hydropathicity), Extinction Coefficient, Aromaticity Score and Instability index for fasta input protein sequence. The tool has the option to save the result in an auto generated filename and also finds the time required to calculate the result. The tool runs on android phones by using the JBlend application. The tool is available at https://usegalaxy.org/SequenceStatistics
A Survey of Co-Tier and Cross-Tier Interference Mitigation in Femtocell Network
Get PDFAs number of wireless devices connected to system increases, there are challenges to operators and researchers to provide high data rates and wide coverage with high services in indoor environment. To fulfill the high speed data streaming and good quality of service demands of mobile users at home, femtocell networks are deployed in indoor premises. But interference occurs among same tier or between different tiers in two tier architecture. In this paper, interference mitigation techniques in femtocell network are discusse
Simulation of central receiver solar thermal power plant with inclusion of storage tank.
Get PDFMathematical modeling is done for the external central receiver solar thermal power plant. Code is developed for the same and simulation for performance of plant is done by using Visual Basic. In this plant configuration, external receiver receives the incident solar radiation reflected by heliostats. Thermal losses are determined in the receiver and net thermal power from receiver is stored in storage tank. This stored thermal energy is further used to run the turbine. Here effect of inclusion of storage tank on electrical power generation is studied by simulation. Three days namely, cloudy day, winter day and summer day are studied for variation in thermal energy storage. Simulation is also done for the annual power generation with zero hours, eight hours and twelve hours of storage. Comparison is made between effect of increase of concentration ratio and utilization of thermal energy in power plant
Prediction of Respirable Particulate Matter (PM10) Concentration using Artificial Neural Network in Kota city
Get PDFRecent years concerns related with ambient air quality is prominent due to increments in the entropy and ozone layer depletion. Green house gas emission from the industries is the key contributing factor in the increase in carbon foot prints. The accurate prediction of hazardous gases in the environment can be beneficial information to initiate the corrective strategies for reduction in carbon foot prints. This paper presents a supervised learning based prediction engine for prediction of Respirable Suspended Particulate Matter (RSPM). “Supervised learning” takes a known set of input data and known responses to the data, and seeks to build a predictor model that generates reasonable predictions for the response of new data. Data of 2012,2013 and 2014 of an industrial area of Kota city is employed to train, test and validate four different topologies of the neural networks namely Feed Forward Neural Network (FFNN), Layer Recurrent Neural Network (LRNN),Nonlinear autoregressive Exogenous (NARX) and Radial Basis Function Neural Network (RBFN). A meaningful comparison between these topologies revealed that RBFN is a suitable topology for prediction engine. PM10 constitutes solid and liquid suspended particles having an aerodynamic diameter up to 10 µm (micro meter). It is a common pollutant among all sectors namely transports domestic, industries and manufacturing so it is the major common pollutant need to be taken under consideration in terms of air pollution. Most of the cities of India exceed PM10 levels according to the National ambient air quality standard (NAAQS). PM10 is responsible for heart and lungs diseases. To decrease the mortality rate due to these pollutant Effective countermeasures need to be taken. The precise prediction of pollutant needed to alert the population
Noise reduction in MEMS Accelerometer by using Kalman Filter
No full textA Kalman filter is designed and implemented for a MEMS capacitive accelerometer in order to filter out two major noise sources in the accelerometer, which are electronic noise and thermal mechanical noise (Brown noise). The dynamic modeling of the MEMS accelerometer is developed. A Kalman filter act as observer in system modeling and Simulation results Show that the Kalman filter based observer produces an excellent noise reduction, improve the performance of accelerometer which is used in many navigation and automobile application. Paper also discusses the noise sources present in the accelerometer
A Wireless Sensor Network Based Power Management for Intelligent Buildings
No full textThe proposed system aims the implementation of smart monitoring and controlled consumption at residential and commercial buildings. The rise in demand of power is increasing as compared to transmission capacity, due to increase in population growth also fuel and coal prices. The major challenge is to reduce the power consumption by optimizing the operation of several loads without causing any impact in the customer's comfort. Intelligent Power Management system is the combination of smart sensors and actuators. The development and design of an intelligent monitoring and controlling system for home, residential and commercial building appliances in real time system is implemented. The system implements the load prioritization and facilitates the real time monitoring of the connected loads based on the predefined maximum load value. The system also shut down all loads when there is no person available in the vicinity. It monitors electrical parameters like voltage and current and subsequently calculates the power consumption. A Visual Basic application is included in the system which will be controlling all activities of the system in user controlled mode (manual mode) or system controlled mode (intelligent mode). This will improvise the savings of the energy which will provide better efficiency and power management in the buildings
An Automatic Toll Collection, Vehicle Identification During Collision & Theft Detection using RFID
No full textAbstract—“Automatic Toll Collection, Vehicle Identification During Collision & Theft Detection using RFID” addresses the problems faced at the toll plaza and culprit identification during collision. The system also identifies the vehicles against which stolen cases are registered using RFID. The mobile application is used to create an account and register his RFID number at central database. When a vehicle with RFID tag arrives at toll plaza the Toll Collection Unit (TCU) classifies the vehicle as a passenger carrying vehicle or goods carrying vehicle based on its RFID Number. The goods carrying vehicle is weighed and if it is overloaded then charged with extra toll. The amount to be charged is then decided based on whether the vehicle is passenger carrying vehicle or goods carrying vehicle. RFID Number and amount to be charged is then passed to Central Server Unit (CSU) where a balance is deducted from user account after which CSU indicate TCU to allow the vehicle to pass. If the vehicle is identified as stolen vehicle by CSU based on RFID Number of vehicle, CSU will indicate TCU not to allow the vehicle to pass. In order to identify the culprit in hit and run case collision detection mechanism is implemented using vibration sensor. Theft Detection Mechanism is implemented to protect the vehicle from thief
A Novel Approach of Inhalt Based Video Recuperation System Using OCR and ASR Technologies
Get PDFNow a days Lecture videos are present methods for E-learning process. The degree of lecture video data on the (WWW)World Wide Web is growing very quickly. Therefore maximum appropriate technique for retrieving video within vast lecture video library is required. This technique will be very beneficial for the new and existing users to search related video within a short period of time. This paper shows a different method for inhalt based video searching for receiving correct outcomes. The main aim of the proposed system is to recover a video on the basis of its substances rather than retrieving video consulting to its title and meta data explanation in order to provide an correct for the examine query. For mining text data printed on slides we put on optical character recognition algorithm(OCR) and automatic speech recognition algorithm(ASR) to convert speaker’s speech into text