Showing posts with label top indian journal. Show all posts
Showing posts with label top indian journal. Show all posts

Tuesday, April 9, 2019

IJIRST : Research Paper : Call For Paper : 2019


Call for Papers | Vol. 5 Issue 11 - April #2k19
Last date of Paper submission 25th March '19 
for More Info or Query Cont. us: 07405046536
Email us: ijirst.journal@gmail.com
Submit your Paper @ http://www.IJIRST.org


Wednesday, September 27, 2017

Call for Paper for October-2017

IJIRST : International Journal for Innovative Research in Science & Technology

#IJIRST Journal: Call for paper
Volume 4 Issue 5 October 2017
Impact Factor: 4.371

For more details : http://ijirst.org/

Wednesday, February 24, 2016

#IJIRST Journal:- "National Conference(V-IMPACT-2016)" on Innovations in Micro-electronics, Signal Processing and Communication Technologies

"National Conference(V-IMPACT-2016)" 

on Innovations in Micro-electronics, Signal Processing and Communication Technologies

In association with

VIT Campus is organizing a conference on 'Innovations in Micro-Electronics, Signal Processing and Communication Technologies'. This conference is fifth in succession to conferences held in years 2012, 2013, 2014 and 2015. The aim of the conference is to review the recent advancement in understanding the science and technology, facilitate exchange of new ideas and explore emerging directions both in basic sciences and technological applications of Electronics, Signal Processing Communication. Recently, scientific activities are on surge on the MEMS, VLSI, DSP and Communication. So the increase in the research activities and the consequent enthusiasm is on rise day by day. 

The new fields such as CAD, VLSI and MATLAB are at the horizon highlighting many important issues involved in the preparation and applications of these useful Systems & Fields. These topics which constitute the frontiers of devices and technology are expected to lead to the development of new systems and new technologies. 

The Conference is intended to bring theorists, experimentalists and experts on a common platform and foster inter disciplinary research. The thrust of the conference will be to facilitate emergence of collaborations between the participants. The informal atmosphere that will prevail is expected to facilitate interactions between young researchers and experts which will be particularly useful for graduate/ research students. We invite you all to participate, deliver talks, present your work and make this event a great success.



VIVEKANANDA INSTITUTE OF TECHNOLOGY

Sisyawas, NRI Road, Jagatpura, Jaipur-303012

Publication Partner:
Website:- www.ijirst.org






Wednesday, December 9, 2015

Paper Title:- Development of ANN and AFIS Models for Age Predictionof in-Service Transformer Oil Samples


Author Name:- Mohammad Aslam Ansari 

Department of Electrical Engineering 

Abstract:- Power transformer is one of the most important and expensive equipment in electrical network. The transformer oil is a very important component of power transformers. It has twin functions of cooling as well as insulation. The oil properties like viscosity, specific gravity, flash point, oxidation stability, total acid number, breakdown voltage, dissipation factor, volume resistivity and dielectric constant suffer a change with respect to time. Hence it is necessary that the oil condition be monitored regularly to predict, if possible, the remaining lifetime of the transformer oil, from time to time. Six properties such as moisture content, resistivity, tan delta, interfacial tension and flash point have been considered. The data for the six properties with respect to age, in days, has been taken from literature, whereby samples of ten working power transformers of 16 to 20 MVA installed at different substations in Punjab, India have been considered. This paper aims at developing ANN and ANFIS models for predicting the age of in-service transformer oil samples. Both the the models use the six properties as inputs and age as target. ANN (Artificial Neural Network) model uses a multi-layer feedforward network employing back propagation algorithm, and ANFIS (Adaptive Neuro Fuzzy Inference System) model is based on Sugeno model. The two models have been simulated for estimating the age of unknown transformer oil samples taken from generator transformers of Anpara Thermal Power Project in state of U.P. India. A comparative analysis of the two models has been made whereby ANFIS model has been found to yield better results than ANN model.     

Keywords: ANN, ANFIS, Power Transformer, Regression, Performance, Backpropagation Algorithm   

I.         Introduction

Power transformer is one of the most important constituent of electrical power system. The transformer oil, a very important ingredient of power transformers, acts as a heat transfer fluid and also serves the purpose of electrical insulation. Its insulating property is subjected to the degradation because of the ageing, high temperature, electrical stress and other chemical reactions. Hence it is necessary that the oil condition be monitored regularly. This will help to predict, if possible, the in-service period or remaining lifetime of the transformer oil, from time to time.
       There are several characteristics which can be measured to assess the present condition of the oil. The main oil characteristics are broadly classified as physical, chemical and electrical characteristics; some of these are viscosity, specific gravity, flash point, oxidation stability, total acid number, breakdown voltage, dissipation factor, volume resistivity and dielectric constant. There exists a co-relation among some of the oil properties and suffer a change in their values with respect to time [2]. This variation of oil properties with respect to time has been utilised to develop the two models as said earlier
      The training data for the proposed work have been obtained from literature, whereby ten working transforms of 16 to 20 MVA, 66/11 KV installed at different substations in the state of Punjab, India have been considered. The six properties of transformer oil such as breakdown voltage (BDV), moisture, resistivity, tan delta, interfacial tension and flash point have been considered as inputs and age as target. Test data have been taken from generator transformers of 250 MVA, 15.75kV/400kV from Anpara Thermal Power Project in state of U. P., India.

II.     “Ann” and “Anfis” methods

It is known that classical models need linear data for their processing, therefore models like ANN and ANFIS that are based on soft computing techniques, play an important role for solving these kinds of non-linear problems.
        Neural networks exhibit characteristics such as mapping capabilities or pattern association, generalization, robustness, fault tolerance, parallel and high speed processing. Neural networks can be trained with known examples of a problem to acquire knowledge about it. Once trained successfully, the network can be put to effective use in solving unknown or untrained instances of the problem. ANN model which uses multilayer feed forward network is based on back propagation (BP) learning algorithm of neural network. Backpropagation gives very good answers when presented with inputs never seen before. This property of generalization makes it possible to train a network on giving set of input-target pairs and get good output.
         ANFIS stands for Adaptive Neural Fuzzy Inference System. Using a given input/output data set, the toolbox function ANFIS constructs a fuzzy inference system (FIS) whose membership function parameters are tuned (adjusted) using either a backpropagation algorithm alone, or in combination with a least squares type of method. This allows the fuzzy systems to learn from the data they are modelling. These techniques provide a method for the fuzzy modeling procedure to learn information about a data set, in order to compute the membership function parameters that best allow the associated fuzzy inference system to track the given input/output data. This learning method works similarly to that of neural networks.

III.       Development of ann model

The proposed ANN model uses “Levenburg-Marquardt (trainlm) algorithm which is independent of learning rate, hence by simply changing the number of neurons in hidden layer, training and testing error could be reduced. A total of 700 data sets obtained from literature [2] were arranged in tabular form and used for training the neural network. The model uses a simple two layer network, one hidden layer and one output layer. Input layer comprises of six neurons, one for the each input, while the output layer has a single neuron for a single output, the age of oil sample.
         It has been found that network architecture that uses 20 neurons in hidden layer gave the best performance with a regression of 0.999 and mean square error (MSE) of 83.0 ( data is non –normalized, so error looks large ) . The training continued for 184 iterations with training functions logsig in hidden layer and purelin in output layer respectively.

For More Information Click Here

Monday, December 7, 2015

A Time Domain Reference-Algorithm for Shunt Active Power Filters



Abstract:- The aim of this paper is to identify an optimum control strategy of three-phase shunt active filters to minimize the total harmonic distortion factor of the supply current Power Quality (PQ) is an important measure of an electrical power system. The term PQ means to maintain purely sinusoidal current wave form in phase with a purely sinusoidal voltage wave form. The power generated at the generating station is purely sinusoidal in nature. The deteriorating quality of electric power is mainly because of current and voltage harmonics due to wide spread application of static power electronics converters, zero and negative sequence components originated by the use of single phase and unbalanced loads, reactive power, voltage sag, voltage swell, flicker, voltage interruption etc. The simulation and the experimental results of the shunt active filter, along with the estimated value of reduction in rating, show that the shunt filtering system is quite effective in compensating for the harmonics and reactive power, in addition to being cost-effective.   

Keywords: Shunt voltage inverter APF, Time domain, instantaneous active power, carrier based PWM, Control strategy etc.

I.     Introduction

The wide use of power devices (based on semi-conductor switches) in power electronic appliances (diode and thyristor rectifiers, electronic starters, UPS and HVDC systems, arc furnaces, etc…) induces the appearance of the dangerous phenomenon of harmonic currents flow in the electrical feeder networks, producing distortions in the current/voltage waveforms. As a result, harmful consequences occur: equipment overheating, malfunction of solid-state material, interferences with telecommunication systems, etc... Damping harmonics devices must be investigated when the distortion rate exceeds the thresholds fixed by the ICE 61000 and IEEE 519 standards. For a long time, tuned LC and high pass shunt passive filters were adopted as a viable harmonics cancellation solution.

II.    Shunt active filtering algorithms

The control algorithm used to generate the reference compensation signals for the active power filter determines its effectiveness. The control scheme derives the compensation signals using voltage and/or current signals sensed from the system. The control algorithm may be based on frequency domain techniques or time domain techniques. In frequency domain, the compensation signals are computed using Fourier analysis of the input voltage/current signals. In time domain, the instantaneous values of the compensation voltages/currents are derived from the sensed values of input signals. There are a large number of control algorithms in time domain such as the instantaneous PQ algorithm, synchronous detection algorithm, synchronous reference frame algorithm and DC bus voltage algorithm. The instantaneous PQ algorithm by Akagi  is based on Park’s transformation of input voltage and current signals from which instantaneous active and reactive powers are calculated to arrive at the compensation signals. This scheme is most widely used because of its fast dynamic response but gives inaccurate results under distorted and asymmetrical source conditions.

For  More Information Click Here

Friday, November 20, 2015

Performance Assessment for Students using Different Defuzzification Techniques


Author Name:- Anjana Pradeep, Jeena Thomas

Department of Computer Science & Engineering

Abstract:- The aim of this study is to evaluate the performance of students using a fuzzy expert system. The fuzzy process is based solely on the principle of taking non-precise inputs on the factors affecting the performance of students and subjecting them to fuzzy arithmetic to obtain a crisp value of the performance. The system classifies each student's performance by considering various factors using fuzzy logic. Aimed at improving the performance of fuzzy system, several defuzzification methods other than the built methods in MATLAB have been devised in this system for producing more accurate and quantifiable result.  This study provides comparison and in depth examination of various defuzzification techniques like Weighted Average Formula (WAF), WAF-max method and Quality Method (QM). A new defuzzification method named as Max-QM which is extended from Quality method that falls within the general framework is also given and commented upon in this study.      

Keywords: Fuzzy logic, Fuzzy Expert System, Defuzzification, Weighted Average Formula, Quality Method 

I.   Introduction

An expert system is a software program that can be used to solve complex reasoning tasks that usually require a (human) expert. In other words, an expert system should help a novice, or partly experienced, problem solver, to match acknowledged experts in the particular domain of problem solving that the system is designed to assist. To be more specific, expert systems are generally conceptualized as shown in Fig 1. The user makes an interaction through the interface system and the system questions the user through the same interface in order to obtain the vital information upon which a decision is to be made. Behind this interface, there are two other sub-systems viz. the knowledge base, which is made up of all the domain-specific knowledge that human experts use when solving that category of problems and the inference engine, a system that performs the necessary reasoning and uses knowledge from the knowledge base in order to come to a judgment with respect to the problem modelled [1].
     Expert system has been playing a major role in many disciplines such as in medicines, assist physician in diagnosis of diseases, in agriculture for crop management, insect control, in space technology and  in power systems for fault diagnosis[5]. Some expert systems have been developed to replace human experts and to aid humans. The use of an expert system is increasing day by day in today’s world [40]. Expert systems are becoming an integral part of engineering education and even other courses like accounting and management are also accepting them as a better way of teaching[4].Another feature that makes expert system more demanding for students is its ability to adaptively adjust the training for each particular student on the bases of individual students learning pace. This feature can be used more effectively in teaching engineering students. It should be able to monitor student’s progress and make a decision about the next step in training.

Fig. 1: Expert system structure
        The few expert systems available in the market present a lot of opportunities for the students who desire more spotlight and time to learn the subjects. Some expert systems present an interactive and friendly environment for students which encourage them to study and adopt a more practical approach towards learning. The expert systems can also act as an assistor or substitute for the teacher. Expert systems focus on each student individually and also keep track of their learning pace. This behavior of an expert system provides autonomous learning procedure for both student and teacher, where teachers act as mentor and students can judge their own performance. Expert system is not only beneficial for the students but also for the teachers which help them guiding students in a better way.
        The integration of fuzzy logic with an expert system enhances its capability and is called a fuzzy expert system, as it is useful for solving real world problems which do not require a precise solution. So, there is a need to develop a fuzzy expert system as it can handle imprecise data efficiently and reduces the manual working while enhancing the use of expert system[40].

      There are various factors inside and outside college that results in poor quality of academic performance of students[2,3]. To determine all the influencing factors in a single effort is a complex and difficult task. It necessitates a lot of resources and time for an educator to identify all these factors first and then plan the classroom activities and approaches of teaching and learning. It also requires appropriate training, organizational planning and skills to conduct such studies for determining the contributing factors inside and outside college. This process of identification of determinants must be given full attention and priority so that the teachers may be able to develop instructional strategies for making sure that all the students be provided with the opportunities to attain at their fullest potential in learning and performance.  By using suitable statistical package it was found that communication, learning facilities, proper guidance and family stress were the factors that affect the student performance. Communication, learning facilities and proper guidance showed a positive impact on student performance and family stress showed a negative impact on student performance. It is indicated that communication is more important factor that affect the student performance than learning facilities and proper guidance [3].

      In this research article seven most important factors are included which affect the students’ performance. These are personal factors, college environment, family factors, and university factors, teaching factors, attendance and marks obtained by students. All these factors are scaled and ranked based on the various sub-factors that are further divided from the base factors. In this study the students’ marks have been focused and not solely on social, economic, and cultural features.  To evaluate students’ performance, fuzzy expert system has been developed by considering all the seven factors as inputs to the system. This system has been developed by taking the data of students collected from St. Josephs College of Engineering and Technology, Palai affiliated to M.G University.

II.   Literature review

In recent years, many researchers worked on the applications of fuzzy logic and fuzzy sets in educational assessments and grading systems. Biswas[25] presented two methods for evaluating  students’ answer scripts using fuzzy sets and a matching function: a fuzzy evaluation method (FEM) and a generalized fuzzy evaluation method. He used fuzzy set theory in student evaluation and found that it is potentially finer than awarding grades or numbers when evaluating answer scripts. He also highlighted that the importance of education system should be to provide students with the evaluation reports regarding their test/examination as sufficient as possible with unavoidable error as small as possible so as to make evaluation system more transparent and fairer to students.

          Chen and Lee [26] presented two methods for applying fuzzy sets to overcome the problem of giving two different fuzzy marks to students with the same total score which could arise from Biswas’ method. Their methods perform calculations much faster and complicated matching operations were not required. Echauz and Vachtsevanos [27] proposed a fuzzy logic system for translating traditional scores into letter-grades. Law [28] built a fuzzy structure model with its algorithm to aggregate different test scores in order to produce a single score for individual students in an educational grading system. A method to build the membership functions (MFs) of several linguistic values with different weights was also proposed in this paper. 

         Wilson, Karr, and Freeman [29] presented an automatic grading system based on fuzzy rules and genetic algorithms. To assess the outcomes of student-centered learning using the evaluation of their peers and lecturer, a new fuzzy set approach was proposed by Ma and Zhou[30] .Wang and Chen [31] proposed a method for evaluating students answer scripts using fuzzy numbers associated with degree of confidence. They have considered degree of confidence of evaluator when awarding satisfaction level to questions of student answer scripts. Weon and Kim [32] developed an evaluation strategy based on fuzzy MFs. They pointed out that the system for students’ achievement evaluation should consider the three important factors of the questions: the difficulty, the importance, and the complexity. They used singleton functions to describe the factors of each question reflecting only the individual effect of the three factors and not the collective effect.
            Bai and Chen [34] pointed out that the difficulty factor is a very subjective parameter and may cause an argument concerning fairness in evaluation. Bai and Chen [33] proposed a method for automatically constructing grade membership functions of fuzzy rules for students’ evaluation. Bai and Chen [34] proposed a method for applying fuzzy MFs and fuzzy rules for the same purpose. To solve the subjectivity of the difficulty factor in Weon and Kim’s method [32], they obtained the level of difficulty as a function of the accuracy of the student’s answer script and the time consumed to answer the questions. However, their method still has the subjectivity problem, since the results in scores and ranks are heavily dependent on the values of several weights which are determined by the subjective knowledge of domain experts.

             In paper[35], a fuzzy logic evaluation system considering the importance, the difficulty, and the complexity of questions based on Mamdani’s[36] fuzzy inference and center of gravity (COG) defuzzification is proposed as an alternative to Bai and Chen’s method [34]. The transparency and objective nature of the fuzzy logic system makes it easy to understand and explain the results of evaluation, and thus to persuade students who are skeptical or not satisfied with the evaluation results. Li and Chen [37] proposed a method for automatically generating the weights for several attributes with fuzzy reasoning capability. Chiang and Lin [38] presented a method for applying the fuzzy set theory to teaching assessment. Chang and Sun [39] presented a method for fuzzy assessment of learning performance of junior high school students. From the previous studies, it can be found that fuzzy numbers, fuzzy sets, fuzzy rules, and fuzzy logic systems have been used for various educational grading systems. 

For more Information CLICK HERE

Tuesday, September 29, 2015

Study on the Ductile Characteristics of Hybrid Ferrocement Slab #IJIRST Journal


Department of Civil Engineering

Poojya Doddappa Appa college of Engineering, Kalaburagi – 585102, Karnataka, India

Abstract:- This paper presents the ductile characteristics of hybrid Ferro cement slab incorporating polypropylene fibres and GFRP sheet. A total of 9 slab have been tested under two point flexural loading. The size of the slab is 1000 mm(length) x1000 mm(width) x 60 mm(thickness). The parameters studied in this investigation includes the number of weld mesh layers, polypropylene fibres i.e (0.3%) and GFRP sheet. from the studies, it is observed that the load carrying capacity and deformation. The stiffness of the specimens with zero layer weld mesh is lower than that of the specimens with two layers and three layers bundled. Further, there is reduction in number of cracks with increase in fibre content.

Keyword:- Ferrocement Slabs, GFRP Wrapping, Fibre Reinforcement, Ductility Factors, Crack Pattern

I.       Introduction

The development of new technology in the material science is progressing rapidly. In recent two or three decades, a lot research was carried out throughout globe for how to improve the performance of concrete in terms of strength and durability qualities. consequently concrete has no longer remained as a construction material. A new material consisting of wire meshes and cement mortar called ferrocement. it is one of the construction materials which may be able to fill the need for building light structures. ferrocement composite consist of cement-sand mortar and single or multi-layers of steel wire mesh to produce elements of small thickness having high durability, and when properly shaped it has high strength and rigidity. These thin elements can be shaped to produce structural members such as folded plates, flanged beams, wall pane,. etc for use in the construction of cheap structures. Ferro cement elements are generally more ductile when compared to conventional reinforced concrete elements but post peak portion of load- deflection curve in bending test of Ferro cement elements reveals that failure occur  either due to mortar failure in compression or due to failure of extreme layers of mesh.  From the above discussions, it can be noted that, research work out on the ductile behavior of hybrid ferrocement slab with fibre. The present Investigation is aimed at to investigate the ductile behavior of hybrid ferrocement slabs with and without Considering the effect of fibres.  Compared with the conventional reinforced concrete, ferrocement is reinforced in two directions; therefore, it has homogenous-isotropic properties in two directions. Benefiting from its usual high reinforcement ratio, ferrocement generally has a high tensile strength and a high modulus of rupture. In addition, since the specific surface of reinforcement in ferrocement is one to two orders of magnitude higher than that of reinforced concrete, larger bond forces develop with the matrix resulting in average crack spacing and width more than one order of magnitude smaller than in conventional reinforced concrete (Shah and Naaman 1997, Guerra et al 1978). Other appealing features of ferrocement include ease of prefabrication and low cost in maintenance and repair. Based on the abovementioned advantages, the typical applications of ferrocement are water tanks, boats, housing wall panel, roof, formwork and sunscreen (Nimityongskul et al 1980 and Kadir 1997).. Ferrocement over the years have gained respect in terms of its superior performance and versatility. Ferrocement is a form of reinforced concrete using closely spaced multiple layers of mesh and/or small diameter rods completely infiltrated with, or encapsulated in, mortar. In 1940 Pier Luigi Nervy, an Italian engineer, architect and contractor, used ferrocement first for the construction of aircraft hangars, boats and buildings and a variety of other structures. It is a very durable, cheap and versatile material.

II.       Experimental investigation

The experimental investigation consists of testing of nine hybrid ferrocement slabs. the Variables Considered In The Study(I) Numbers Of Welded Square Mesh Reinforcement.(ii) Percentage of polypropylene fibres in mortar.(iii) Number of GFRP layer wrapping. The details of experimental studies including characterization are presented below.

A.      Materials Used

The materials that are used in this experiment are cement, steel fiber, fine aggregate, super plasticizer and water.

1)     Cement:

OPC 53 grade cement from a single batch has been used throughout the course of the project work, properties of cement are shown in table 2.

2)     Fine aggregates:

Only fine aggregate is used in Ferrocement the aggregate consists of well graded fine aggregate (sand)   that   passes   a   4.75  mm   sieve.  and   since   salt-free   source   is recommended, sand should preferably be selected from river-beds and be free from  organic  or  other  deleterious  matter. Good amount of consistency and compactibility is achieved by using a  well- graded, rounded, natural sand having a maximum top size about one-third of the small opening in the reinforcing mesh to ensure proper penetration. The moisture content of the aggregate should be considered in the calculation of required water.

3)     Super plasticizer:

Super plasticizer used in the present investigation is FOSROC CONPLAST SP430. and the details of super plasticizer is given  in table.1.

4)     Polypropylene Fiber:

Having specific gravity 0.90 -0.91 gm/cm3 because of its low specific gravity ,polypropylene yields the greatest volume of fibre for a given weight. This yield means that the polypropylene fibre provides good and bulk cover, while being lighter in weight. Polypropylene is lightest of all fibres and is lighter than water. It is 34% lighter than polyester and 20% lighter than nylon.

5)     Water:

Potable water was used in the present investigation for both casting and curing. the  water  used  for  mixing  cement  mortar  should  be  fresh, cleanand fit for construction purposes; the water of pH equal or greater than 7 and free from organic matter—silt, oil, sugar, chloride and acidic material.

For more information go on below link.

Thursday, September 24, 2015

Applications and Challenges of Human Activity Recognition using Sensors in a Smart Environment #IJIRST Journal


Department of Computer Science and Engineering

St. Joseph’s College of Engineering and Technology, Palai, Kerala, India

Abstract:- We are currently using smart phone sensors to detect physical activities. The sensors which are currently being used are accelerometer, gyroscope, barometer, etc. Recently, smart phones, equipped with a rich set of sensors, are explored as alternative platforms for human activity recognition. Automatic recognition of physical activities – commonly referred to as human activity recognition (HAR) – has emerged as a key research area in human-computer interaction (HCI) and mobile and ubiquitous computing. One goal of activity recognition is to provide information on a user’s behavior that allows computing systems to proactively assist users with their tasks. Human activity recognition requires running classification algorithms, originating from statistical machine learning techniques. Mostly, supervised or semi-supervised learning techniques are utilized and such techniques rely on labeled data, i.e., associated with a specific class or activity. In most of the cases, the user is required to label the activities and this, in turn, increases the burden on the user. Hence, user- independent training and activity recognition are required to foster the use of human activity recognition systems where the system can use the training data from other users in classifying the activities of a new subject.

Keyword:- Human Activity Recognition

I.       Introduction

Mobile phones or smart phones are rapidly becoming the central computer and communication device in people’s lives. Smart phones, equipped with a rich set of sensors, are explored as an alternative platform for human activity recognition in the ubiquitous computing domain. Today’s Smartphone not only serves as the key computing and communication mobile device of choice, but it  also comes with a rich set of embedded sensors [1], such as an accelerometer, digital compass, gyroscope, GPS, microphone, and camera. Collectively, these sensors are enabling new applications across a wide variety of domains, such as healthcare, social networks, safety, environmental monitoring, and transportation, and give rise to a new area of research called mobile phone sensing. Human activity recognition systems using different sensing modalities, such as cameras or wearable inertial sensors, have been an active field of research. Besides the inclusion of sensors, such as accelerometer, compass, gyroscope, proximity, light, GPS, microphone, camera, the ubiquity, and unobtrusiveness of the phones and the availability of different wireless interfaces, such as WI-Fi, 3G and Bluetooth, make them an attractive platform for human activity recognition. The current research in activity monitoring and reasoning has mainly targeted elderly people, or sportsmen and patients with chronic conditions.
The percentage of elderly people in today’s societies keep on growing. As a consequence, the problem of supporting older adults in loss of cognitive autonomy who wish to continue living independently in their home as opposed to being forced to live in a hospital. Smart environments have been developed in order to provide support to the elderly people or people with risk factors who wish to continue living independently in their homes, as opposed to live in an institutional care. In order to be a smart environment, the house should be able to detect what the occupant is doing in terms of one’s daily activities. It should also be able to detect possible emergency situations. Furthermore, once such a system is completed and fully operational, it should be able to detect anomalies or deviations in the occupant’s routine, which could indicate a decline in his abilities. In order to obtain accurate results, as much information as possible must be retrieved from the environment, enabling the system to locate and track the supervised person in each moment, to detect the position of the limbs and the objects the person interacts or has the intention to interact with. Sometimes, details like gaze direction or hand gestures [1] can provide important information in the process of analyzing the human activity. Thus, the supervised person must be located in a smart environment, equipped with devices such as sensors, multiple view cameras or speakers.

For more information go on below link.


Tuesday, September 22, 2015

Dynamic Power Reduction in NOC by Encoding Techniques #IJIRST Journal


Abstract:- As technology improve the size will be reduced, and the power dissipated by the links of a network-on-chip (NoC) is starts to participate with the power dissipate by the other element of communication system, for example the routers and the network interfaces (NIs). We design an set of data encoding technique by different schemes to decrease the power dissipation by an links of NoC, which optimizing the on-chip communication system not only in terms of performance but also in terms of power. The idea presented in this paper is base on encoding the packets before they are inserted in to the network in such a way as to minimize both the switching action and the coupling-switching action in the NoC’s link which represent the main factor of power dissipation. These schemes were universal and transparent with respect to the construct NoC fabric that means this application will not require any change in the router and link of architecture. These will be carried in both artificial and real traffic scenario. These effective of the proposed scheme will tolerate to save the energy consumption and power dissipation without changing the performance degradation and with less area consumption in the NI.  

Keywords: switching action, encoding, network-on-chip (NoC), low power, router, Network interfaces (NIs)

I.       Introduction

Moving towards silicon technology node to the next results faster and more efficient gates but slower because there is a more power hungry wires. More than 50% of total dynamic power is dissipate in interconnection in current processor, and this was expected to increase more over in the next several years. Global interconnect length does not scale with smaller transistors and local wires. Chip size remains relatively constant because the chip function continues for instance the RC delay increases exponentially. The RC delay in a 1-mm worldwide wire at the smallest pitch is superior to the intrinsic delay of a two-input NAND fan-out. If the raw computation horsepower seems to be un-limited, thanks to the ability of instance more core’s in a single silicon chip, scalable issue occur, due to making an efficient and reliable communication among the increasing number of core’s, become the real problem. The NOC invent is documented as the most feasible way to tackle with scalable and variability issue that characterize the ultra-deep sub-micron-meter.
Now a days in the on-chip communication issue is relevant, in some of the case more relevant than commutating related issue. The communication sub-system more and more impacts the usual designed objective, and also includes cost (i.e., area of silicon), performances, dissipation of power, consumption of energy and reliability. As technology improves the size is reducing and more fraction of total power is budget of the complex in more core of the system-on-chip (SoC) this is because of communication sub-system.
Here we attentation on the technique aim to minimize power dissipation by a network link. The power dissipation in the network is relevant as that dissipation by NIs, routers and it is giving that ordinary to increase the technology scale. We are representing the set of encoding schemes for data which is in binary formate, and it is operated at flit level, and an end-to-end basis, this allows us to minimize the switching action and coupling switching action at the link of an direction is traverse by a packet. This encoding schemes, were transparent by respect to router execution, and they are presented, discussed in both algorithmic-level and architectural level, it is assessed via the simulation in the artificial, real traffic scenario. These analysis gives an different aspects, metrics design, it include area of silicon, energy consumption and dissipation of power. From the results we can conclude that with these proposed encoding schemes that power will save and also energy will be save without changing any major degradation in the performance in the NIs.

II.       Motivation and Related work

The accessibility of chips is growing every year. In next few years, the accessibility of cores with 1000 cores is foreseen. Since the focus of this paper is to decrease the power dissipation by link which decreases the dynamic power, here we are going review the works in the area and link power reduction. Also these will include some technique. They are, use of shielding to  increase line-to-line space and repeater insertion. So above technique have large area consumption. One method is the data encoding technique, its mainly focus is to reduce the link power. The encoding technique’s is categorize in to two group. In 1st group we are going to decrease the power by the self-switching action of the each bus line and avoid the dissipation of power by coupling switching action.
These work concentrate on the different component of the inter connection network such as NIs, router, and link. Because these will reduce power dissipation by an link, in this paper, we are going to brief the review some works in the region of link power reduction. These include the technique that make use of shielding, which increase line-to-line space and repeater inserted. They all increases the silicon chip area. These encode scheme is an additional technique that is employed to reduce dissipation of power in link. The data encoding technique has been classified in to two class. In the first class, encoding technique concentrate on reducing the power due to self-switching action of separate bus line while ignoring an power dissipation due to their coupling-switching action. In these class, bus invert (BI) and INC-XOR have been proposed for these case that casual random data pattern is transmitte through the lines. On the other hand, gray code, T0, working-zone encoding, and T0-XOR were suggest for the case of correlation data pattern. Application particular approach have also been proposed
This class of encoding will not be appropriate to be applied in the deep sub-micron meter technological node where the coupling capacitance constitute an most important part of the total inter-connect capacitance. This will cause the power consumption due to the coupling-switching action to become a big fraction of the total power consumption in the links, that making the aforementioned techniques, which ignore such contributions, inefficient. The works in the second class concentrate on reducing power dissipation through the reducing the coupling-switching action. Among these schemes, the switching action is reduced by using many additional control lines. For example, the data bus width grows from 32 to 55. The techniques proposed in have a smaller number of control lines but the complexity of their decoding logic is high. The technique described as follows: first, the data are both odd inverted and even inverted, and afterwards transmission is perform using these kind of inversion which reduce more switching action. The coupling switching action it is reduced, this is compared with another, so we use a simple decoder although achieving a higher activity reduction.
The scheme presented is to reduce the coupling switching action. In this method, encoder count the number of Type I (Table I) transitions with a weighting coefficient of one and the number of Type II transitions with the weighting coefficient of two. If the number is larger than half of the link width, the inversion will be performed. In addition to the complex encoder, the method only works on the patterns whose full inversion leads to the link power reduction while not considering the patterns whose full inversions may lead to high link power consumption. So the link power reduction achieved through this technique is not as large as it could be. This scheme was also based on the hop-by-hop technique.

In another coding technique presented in, bunches of four bits are encoded with five bits. The encoded bits were isolated using shielding wires such that the occurrence of the patterns “101” and “010” were prevented. This way, no simultaneous Type II transitions in two adjacent pair bits are induced. This technique effectively reduces the coupling switching activity. Although the technique reduces the power consumption considerably, it increases the data transfer time, and, hence, the link energy consumption. This is due to the fact that for each four bits, six bits are transmitted which increases the communication traffic. This technique was also based on the hop-by-hop approach.
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Tuesday, September 15, 2015

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Friday, September 11, 2015

A Novel High Resolution Adaptive Beam Forming Algorithm for High Convergence

Abstract: This paper introduces a new robust four way LMS and variable step size NLMS beam forming algorithm to reduce interference in a smart antenna system. This algorithm is able to resolve signals arriving from narrowband sources propagating plane waves close to the array end fire. The results of previously used adaptive algorithm have the fixed step size NLMS will result in a trade-off issue between convergence rate and steady-state MSE of NLMS algorithm. This issue is solved by using four way LMS and VSSNLMS which will improve the efficiency of the convergence point. The proposed algorithm implemented reduces the mean square error (MSE) and shows faster convergence rate when compared to the conventional NLMS.
Keywords: Adaptive Antenna, Beamforming, Means Square Error (MSE), Convergence

I.   Introduction

A.      Introduction

In today’s world numbers of mobile users are increasing day by day, hence it is necessary to serve such a huge market of mobile users with high QOS even though the spectrum is limited. This becomes a major challenging problem for the service providers to solve. A major limitation in capacity and performance is co-channel interference caused by the increasing number of users and the multipath fading and delay spread. Research efforts investigating effective technologies to mitigate such effects have been going on and among these methods Adaptive antenna employment is the most promising technology. This project works on Adaptive Antenna which ensures high capacity providing with the same Quality of Service(QOS).In a normal scenario currently the mobile towers employ parabolic dish or a horn antenna but this suffers if the SNR is low the signals have to be repeatedly retransmitted from mobile station to base station. The use of Adaptive Antenna considers an array of antennas in which the antenna will receive the delayed versions of the electromagnetic wave and adds them to achieve high SNR.

B.      Problem Statement

In the earlier antenna radiation was directed based on frequency or time, Therefore spectrum was not utilized efficiently because as the number of users increases the quality of service decreases. Hence, in this work a solution to use the Adaptive antenna frameworks have been proposed and used as an efficient means to meet the quickly expanding the  traffic volume. This issue of Technology has discusses the importance of various advanced antenna schemes for improving the same amount of spectrum and provides service to the large amount of mobile users is deduced. This is done by separating the users with respect to direction.

II.                Adaptive antenna

Adaptive antenna is the one which adapts itself to pick the user signal in any direction without user intervention , basically it undergoes through a two phase process:
-         Direction detection Estimation (DDE) using a suitable algorithm and sensor data.
-         Beam forming which forms a beam in the desired direction and nulls in the interference direction.
Direction Detection Estimation (DDE) methods are used to detect the incoming wave and the other signals which arrive from different parts of the space can be processed to extract different type of data including direction desired incoming signal falling on the antenna array.

Beam forming is a process of forming the Main beam in the desired direction and nulls in the direction of jammers direction. The block diagram is shown in  Figure1 shows an adaptive antenna structure with N antenna elements, DDE blocks, Adaptive signal processor algorithms to make adaptive antenna system smart, where incoming signal is processed by beam forming algorithms the figure also shows main beam formed in the direction of desired signal and nulls in the jammers direction.
Fig. 1: Adaptive Antenna
http://ijirst.org/Article.php?manuscript=IJIRSTV2I3036
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Wednesday, September 9, 2015

Validation of Failure of Beater Shaft of Double Roller Ginning Machine using Mathematical Failure Analysis Approach

Abstract:- A cotton gin is a machine that quickly and easily separates cotton fibers from their seeds, allowing for much greater productivity than manual cotton separation. The fibers are processed into clothing or other cotton goods, and any undamaged seeds may be used to grow more cotton or to produce cottonseed oil and meal. The cotton gin is a machine used to separate cotton fibers from the seed. The double roller ginning machine consists of various parts such as beater shaft, leather roller, moving knife, fixed knife, feeder, etc.         During the ginning operation the shaft fails at certain location. The actual failure position of shaft shown in fig no A was studied and the failure analysis using theories of failure was used to identify and validate the place or point of failure.

Keywords: Ginning machine, beater shaft, theories of failure, SFD, BMD, failure analysis

I.       Introduction

Ginning, in its strictest sense, refers to the process of separating cotton fibers from the seeds. The cotton gin has as its principal function the conversion of a field crop into a salable commodity. Thus, it is the bridge between cotton production and cotton manufacturing.  Ginning is the first and most important mechanical process by which seed cotton is separated into lint (fiber) and seed and machine used for this separation is called as gin. It consists of two spirally grooved leather roller pressed against a fixed knife, are made to rotate at about 90-120 rpm. Two moving blades combined with seed grids constitutes a central assembly known as beater which oscillates by means of a crank or eccentric shaft, close to the fixed knife. When the seed cotton is fed to the machine in action, fibers adhere to the rough surface of the roller are carried in between the fixed knife and roller in such a way that the fibers are partially gripped between them. The oscillating knife beats the seed and separates the fibers. This process is repeated for number of times and due to push-pull-hit action the fibers are separated from the seed, carried forward on the roller and dropped out of machine. The ginned seeds drop down through the grid which is oscillating along with beater.

Fig. 1: Double Roller Gin machine

The beater assembly is the innermost and major part of the double roller gin and is sandwiched symmetrically between the stationary knives as shown in fig.  It is composite unit consisting of moving knives and seed grids situated on the either side of the beater shaft. It has anchor shaped cross section and its axle is situated 100cm above ground and 15cm from each roller. Beater trough with perforations having concave edge with radius of 565cm and angle of 144 degree between two arms is provided to stop unginned cotton to fall down into seed chute.

http://ijirst.org/Article.php?manuscript=IJIRSTV2I3052
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