LTNCS Conference-2017 | IJIRST

National Conference on "Latest Trends in Networking and Cyber Security" 17 March, 2017

We are pleased to invite you to attend/participate in the  National Conference LTNCS-2017 will be held on 17th March 2017, organized by Computer Engineering Department of SAL INSTITUTE OF TECHNOLOGY AND ENGINEERING RESEARCH, Ahmedabad.

LTNCS-2017 aims to gather technocrats from different states of India on a common platform to promote research activities in all fields of Networking and Cyber Security. LTNCS-2017 adhere different Technical Topics as under.

         1). Cybercrime

         2). Distributed Network

         3). Forensic & Cyber Security with Cloud

         4). Security issues with big data

         5). Ethical hacking

              We would like to invite research papers based on original research work from Researchers, Academicians, Faculty Members and Students in various innovative areas of Networking and Cyber Security.
              All submitted papers will be peer-reviewed by renowned experts. The reviewed papers will be published in one of the reputed technical journal namely IJIRST “International Journal for Innovative Research in Science & Technology” having impact factor 3.559.
              With the same, we take this opportunity to invite you all to participate in this conference and share your innovative ideas and research. We shall appreciate your participation in the conference and confirmation for the same at the earliest.

We request you to forward this information to your faculty colleagues, research scholars and students for contributing research papers for LTNCS-2017.

For more information about the conference kindly contact us

Website:            http://conference.ijirst.org/

Email:               ltncs2017@gmail.com

Facebook:         https://www.facebook.com/LTNCS2017/

Contact No:      9998843943, 8128989597

#IJIRST Journal: Dynamic Clustering in Wireless Sensor Networks Based on the Data Traffic Flow and the Node Residual Battery Life Computation

Paper Title:- Dynamic Clustering in Wireless Sensor Networks Basedon the Data Traffic Flow and the Node Residual Battery Life Computation

Author Name:- Sachin Sharma, Professor (Dr.) K C Roy, Professor (Dr.) Dinesh Goyal

Department of Computer Science and Engineering 

Suresh Gyan Vihar University, Jagatpura

Abstract:- Wireless Sensor Networks forms the core of the infrastructural facilities and amenities that constitutes a major part of modern living. Wireless Sensor Networks founds tremendous applications in domains such as theft alarms, wildlife monitoring, radiation/pressure/light/heat sensor networks and the list is endless. It constitutes the core part of the modern Internet of Things (IoT) that will revolutionize the modern living. The Iot specifies a scenario in which the devices can communicate with each other using the internet over a flexible framework and can be programmed to perform specific actions based on the programming customization made by the users. For example, a refrigerator is runs out of milk or bread can email the requirement to the dairy that can entertain the mail and ship a delivery of the same to the location of the refrigerator. As sensor nodes are battery powered, there is a critical aspect to same battery power. This is possible only by avoiding the in-network communication as much as possible. A fraction of communication overhead can be reduced through clustering. In this paper, an approach for dynamic clustering is proposed based on the varying traffic loads to various PAN coordinators so as to maximize the battery life and therefore the network lifetime.

Keywords:- Wireless sensor network, Clustering Protocols, Battery Life etc.

I.    Clustering in Wireless Sensor Networks

Clustering forms, the backbone towards the persistence of sensor nodes towards sensing data in such a way that a single lithium ion battery can work even for one and a half year continuously. This is because of the reduction in in-network communication to the central node through the creation of clusters in such a way that all the node in the cluster transmit the data to the cluster head and the cluster head is responsible to transmit the data to the central node. The senario is expressed in the following figures.

Fig. 1: Wireless Sensor Network without clustering

Fig. 2: Wireless Sensor Network with clustering and Data Aggregation

       The individual collections shown in figure 1.2 are known as clusters and the nodes that belongs to a particular cluster sends the data only to the cluster head. Thus, reducing the data transmission over long distance from the individual nodes to the central computer. In the clustered approach, the nodes transmit the data to the cluster head over a relatively very short distance, thus, conserving the battery life and enhancing the network lifetime.

II.    Dynamic Clustering over the WirelessSensor Network

Consider a network of N nodes and a static number set initially k as the total number of cluster over the network. Thus, on an average, there are N/k in each cluster. Also, consider a rectangular plane of dimension aXa over which the sensor nodes are (approximately evenly) speeded.

      As state previously, there are k clusters each having (N/k)-1 nodes as ordinary sensing nodes and a Cluster head that hold the responsibility of aggregating data from each of the (N/k)-1 nodes. Also assume that each packet senses the medium and sends the data packet to the cluster head in specified TDMA frame.

      Considering the first order radio energy dissipation model, let the energy consumption per bit in the transmission circuitry be E_t and the energy consumption per bit in the processing circuitry be E_p. Let there be B bits in a TDMA packet. Considering the initial energy level in the battery be E, one can approximate the residual battery life after N rounds.

    Let Me be the number of rounds after which the leader election takes place and a message is broadcasted to all the other nodes in the cluster regarding the node which is elected as the leader so that all the nodes may transmit the data to the specific node. The specified node then aggregates the data from all the nodes in its cluster and transmit the data to the central computer.

      It is important to note that the leader election process is an overhead and is incurred only to manage the network traffic. Rapidly electing new heads and consequently broadcasting the message to all other nodes in the network induce an overhead which is to be avoided. On the other hand, it is also important to note that the node which is elected as the cluster head depletes its energy very frequently as it has to perform all the data aggregation processing all be itself for all the nodes in the network. Thus, frequent leader election leads to an evenly consumption of battery power in all the nodes of the cluster. If no election of leader takes place, then the node which handles the task of leader will soon run out of the battery.

     In addition to the depltion of the battery in the normal rounds during the data gathering, the leader will deplete the energy

E = E_broad*n*[(N/k)-1]

in view of broadcasting the message, where n is the number of bits in the broadcasted message, and all the nodes depletes an amount of energy equals to

E = n*E_p

in view of the reception of the message regarding the leader of the cluster.

      Let p be the average number of packets that are transmitted by any node and let the length of each packet be l. For implementation, the case study of Zigbee radio sensors is considered in which the underlying operating system is tiny OS having packet size of l=114 bytes.

The important points to analyze in the scenario is:

For More Information Click Here

A Time Domain Reference-Algorithm for Shunt Active Power Filters

A Time Domain Reference-Algorithm for Shunt Active Power Filters

Author Name:- Prof. Sumita D Chakrabortty

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

Performance of WRF (ARW) over River Basins in Odisha, India During Flood Season 2014

Paper Title:- Performanceof WRF (ARW) over River Basins in Odisha, India During Flood Season 2014

Author Name:- Sumant Kr. Diwakar

India Meteorological Department, New Delhi, India

Abstract:- Operational Weather Research & Forecasting – Advanced Research WRF in short WRF (ARW) 9 km x 9 km Model (IMD) based rainfall forecast of India Meteorological Department (IMD) is utilized to compute rainfall forecast over River basins in Odisha during Flood season 2014. The performance of the WRF Model at the sub-basin level is studied in detail. It is observed that the IMD’s WRF (ARW) day1, day2, day3 correct forecast range lies in between 31-47 %, 37-43%, and 28-47% respectively during the flood season 2014.

Keywords: GIS; WRF (ARW); IMD; Flood 2014; Odisha     

I.      Introduction

Forecast during the monsoon season river sub-basin wise in India is difficult task for meteorologist to give rainfall forecast where the country have large spatial and temporal variations. India Meteorological Department (IMD) through its Flood Meteorological Offices (FMO) is issuing Quantitative Precipitation Forecast (QPF) sub-basin wise for all Flood prone river basins in India (IMD, 1994). There are 10 FMOs all over India spread in the flood prone river basins and FMO Bhubaneswar, Odisha is one of them. The Categories in which QPF are issued are as follows

Rainfall (in mm)

0

1-10

11-25

26-50

51-100

>100

    

    Odisha is an Indian state on the subcontinent’s east coast, by the Bay of Bengal. It is located between the parallels of 17.49’ N and 22.34’ N Latitudes and meridians of 81.27’ E and 87.29’ E Longitudes. It is surrounded by the Indian states of West Bengal to the north-east and in the east, Jharkhand to the north, Chhattisgarh to the west and north-west and Andhra Pradesh to the south. Bhubaneswar is the capital of Odisha.

     Odisha is the 9^th largest state by area in India and the 11^th largest by population. Odisha has a coastline about 480 km long. The narrow, level coastal strip including the Mahanadi river delta supports the bulk of the population. On the basis of homogeneity, continuity and physiographical characteristics, Odisha has been divided into five major morphological regions. The Odisha Coastal Plain in the east, the Middle Mountainous and Highlands Region, the Central Plateaus, the western rolling uplands and the major flood plains.     

A.      River System

The river system of Odisha comprises the Mahanadi, Brahmani, Baitarani, Subarnarekha, Vamasadhara, Burhabalanga, Rushikulya, Nagavali, Indravati, Kolab, Bahuda, Jambhira and other tributaries and distributaries.

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Performance Assessment for Students using Different Defuzzification Techniques

Paper Title:- 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. 

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Dynamic Power Reduction in NOC by Encoding Techniques #IJIRST Journal

Paper Title:- Dynamic Power Reduction in NOC by Encoding Techniques

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.

For more information go on below link.

http://ijirst.org/Article.php?manuscript=IJIRSTV2I4033

Design and Modeling of Drum Handling Equipment #IJIRST Journal

Title: Designand Modeling of Drum Handling Equipment

Abstract:- This paper presents the use of drum handling equipment in the industries to reduce worker for drum handling. Material handling effect on human studied in this paper. Also study different material handling equipment used in industries.

Keywords: Industries, Material Handlings, Material Handling Hazards

I.       Introduction

In many industries raw material and finished product handled in 210Lit. Drum. They handle drum manually. In work place drum transported, lifted, Loaded, tilted etc. manually. Handling heavy load manually takes more time, also it is hazards and risky. In small pharmaceutical company around 25 different type of raw material use. It is in liquid form which is taken out from 210lit. Drum by loading on horizontal stand. Company requires effective material handling equipment to solve material handling problem.  

Manual drum handling equipment is used to do various function like transport, tilting, lifting, loading, unloading etc. In small industries or work shop drum barrel is handled manually which takes more time and more worker. Handling drum manually without using any equipment is hazards.           

Manual handling is transporting or supporting of a load by one or more workers. It includes the following activities: lifting, holding, putting down, pushing, pulling, carrying or moving of a load.1 The load can be an animate (people or animals) or inanimate (boxes, tools etc.) object.

Manual handling occurs in almost all working environments (factories, warehouses, building sites, farms, hospitals, offices etc.). It can include lifting boxes at a packaging line, handling construction materials, pushing carts, handling patients in hospitals, and cleaning. 

II.       Concept

In this, following objectives are to be carried out –

1.  To minimize worker for Drum transporting, loading, unloading, lifting and tilting process.
2.  To study material handling equipment for Drum handling.
3.  To study the lifting and loading effect on human.
4.   To study the ergonomic of material handling.
5.  To Design modified drum tilting mechanism.
6.  To fabricate prototype model.
7.  Testing and conclusion.

This paper is published in our journal and for more information CLICK Here

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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

ijirst.org

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

ijirst.org

This paper is published in our journal for more information go on above link.

IJIRST Journal

Top Rated International Journal  Recommended By Most of University

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Modeling of Student’s Performance Evaluation

Abstract:- We proposed a Fuzzy Model System (FMS) for student performance evaluation. A suitable fuzzy inference mechanism has been discussed in the paper. We mentioned how fuzzy principal can be applying in student performance prediction. This model can be useful for educational organization, educators, teachers, and students also. We proposed this model especially for first year students who need some extraordinary monitoring to their performance. Modeling based on the past academic result and on some information they earlier submitted for admission purposes.

Keywords: Fuzzy Logic, Membership Functions, Academic Evaluation

I.       Introduction

Success rate of any Educational Institute or Organization may depend upon the prior evaluation of student’s performance. They use different method for student’s performance evaluation usually any educational organization use grading system on the basis of academic performance especially higher education. We can involve other key points to evaluating student performance such as communication skill, marketing skill, leadership skill etc.

Performance evaluation can provide information. Information generated by evaluation can be helpful for students, teachers, educators etc. to take decisions.[6] In corporate field employers highly concern about all mentioned skill. If an educational institute involve other than academic performance for evaluation then it will be beneficial for students as well as organization also.

A.      Traditional Evaluation Method

Traditionally student’s performance evaluate done by academic performance like class assignment, model exams, Yearly etc. This Primary technique involves either numerical value like 6.0 to 8.0 which may call grade point average or 60% to 80% i.e average percentage. Some organization also using linguistic terms like pass, fail, supply for performance evaluation. Such kind of evaluation scheme depends upon criteria which are decided by experienced evaluators. So that evaluation may be approximate.

The objective of this paper is to present a model .which may be very useful for teachers, organization and students also. It helps to better understanding weak points which acts as a barrier in student’s progress.

B.      Method Used

Fuzzy logic can be described by fuzzy set. It provide reasonable method / technique through input and output process fig[1].Fuzzy set can be defined by class of object, there is no strident margins for object[1].A fuzzy set formed by combination of linguistic variable using linguistic modifier.

Linguistic Modifier is link to numerical value and linguistic variable [2]. In our work linguistic variable is performance and linguistic modifiers are good, very good, excellent, and outstanding.

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