Fingerprints are the most universal, unique and
persistent biometrics. The growing interest and eventually
the need for advanced security, privacy and user convenience
has put an access to fingerprint recognition, beyond the other
biometrics recognition systems. Despite the ingenious
methods improvised to increase the efficiency of detection in
growing identity frauds, the growing demands for fingerprint
as a biometric recognition system has quickly become
overwhelming. Major challenges coming in the way of a robust
fingerprint recognition system are the presence of noise, cuts,
wet or dry images, different pressure and skin conditions, etc.
The main objective of this paper is to review the extensive
research on fingerprint recognition over the last decades and
to address the present challenges. A comprehensive analysis
can be made from the tabular form of the presented summary
table using various techniques and features. Finally, the future
directions of fingerprint recognition are explored.
Highly Secured Bio-Metric Authentication Model with Palm Print IdentificationIJERA Editor
For securing personal identifications and highly secure identification problems, biometric technologies will
provide higher security with improved accuracy. This has become an emerging technology in recent years due to
the transaction frauds, security breaches and personal identification etc. The beauty of biometric technology is it
provides a unique code for each person and it can’t be copied or forged by others. To overcome the draw backs
of finger print identification systems, here in this paper we proposed a palm print based personal identification
system, which is a most promising and emerging research area in biometric identification systems due to its
uniqueness, scalability, faster execution speed and large area for extracting the features. It provides higher
security over finger print biometric systems with its rich features like wrinkles, continuous ridges, principal
lines, minutiae points, and singular points. The main aim of proposed palm print identification system is to
implement a system with higher accuracy and increased speed in identifying the palm prints of several users.
Here, in this we presented a highly secured palm print identification system with extraction of region of interest
(ROI) with morphological operation there by applying un-decimated bi-orthogonal wavelet (UDBW) transform
to extract the low level features of registered palm prints to calculate its feature vectors (FV) then after the
comparison is done by measuring the distance between registered palm feature vector and testing palm print
feature vector. Simulation results show that the proposed biometric identification system provides more
accuracy and reliable recognition rate
Bimodal Biometric System using Multiple Transformation Features of Fingerprin...IDES Editor
The biometric technology is used to identify
individuals effectively compared to existing traditional
methods. In this paper we propose Bimodal Biometric System
using Multiple Transformation features of Fingerprint and
Iris (BBMFI). The iris image is preprocessed to generate iris
template. The two level Discrete Wavelet Transformation
(DWT) is applied on iris template and Discrete Cosine
Transformation (DCT) is performed on second level low
frequency band to generate DCT coefficients which results in
features of iris. The fingerprint is preprocessed to obtain
Region of Interest (ROI) and segmented into four cells. Then
the DWT is applied on each cell to derive approximation band
and detailed bands. The Fast Fourier Transformation (FFT)
is applied on approximation band to compute absolute values
that results in features of fingerprint. The iris features and
fingerprint features are fused by concatenation to obtain final
set of features. The final feature vector of test and database
are compared using Euclidean distance matching. It is observed
that the values of Total Success Rate (TSR), False Rejection
Rate (FRR) and False Acceptance Rate (FAR) are improved in
the proposed system compared to existing algorithm.
FEATURE EXTRACTION METHODS FOR IRIS RECOGNITION SYSTEM: A SURVEYijcsit
Protection has become one of the biggest fields of study for several years, however the demand for this is growing exponentially mostly with rise in sensitive data. The quality of the research can differ slightly from any workstation to cloud, and though protection must be incredibly important all over. Throughout the past two decades, sufficient focus has been given to substantiation along with validation in the technology model. Identifying a legal person is increasingly become the difficult activity with the progression of time. Some attempts are introduced in that same respect, in particular by utilizing human movements such as fingerprints, facial recognition, palm scanning, retinal identification, DNA checking, breathing, speech checker, and so on. A number of methods for effective iris detection have indeed been suggested and researched. A general overview of current and state-of-the-art approaches to iris recognition is presented in this paper. In addition, significant advances in techniques, algorithms, qualified classifiers, datasets and methodologies for the extraction of features are also discussed.
Highly Secured Bio-Metric Authentication Model with Palm Print IdentificationIJERA Editor
For securing personal identifications and highly secure identification problems, biometric technologies will
provide higher security with improved accuracy. This has become an emerging technology in recent years due to
the transaction frauds, security breaches and personal identification etc. The beauty of biometric technology is it
provides a unique code for each person and it can’t be copied or forged by others. To overcome the draw backs
of finger print identification systems, here in this paper we proposed a palm print based personal identification
system, which is a most promising and emerging research area in biometric identification systems due to its
uniqueness, scalability, faster execution speed and large area for extracting the features. It provides higher
security over finger print biometric systems with its rich features like wrinkles, continuous ridges, principal
lines, minutiae points, and singular points. The main aim of proposed palm print identification system is to
implement a system with higher accuracy and increased speed in identifying the palm prints of several users.
Here, in this we presented a highly secured palm print identification system with extraction of region of interest
(ROI) with morphological operation there by applying un-decimated bi-orthogonal wavelet (UDBW) transform
to extract the low level features of registered palm prints to calculate its feature vectors (FV) then after the
comparison is done by measuring the distance between registered palm feature vector and testing palm print
feature vector. Simulation results show that the proposed biometric identification system provides more
accuracy and reliable recognition rate
Bimodal Biometric System using Multiple Transformation Features of Fingerprin...IDES Editor
The biometric technology is used to identify
individuals effectively compared to existing traditional
methods. In this paper we propose Bimodal Biometric System
using Multiple Transformation features of Fingerprint and
Iris (BBMFI). The iris image is preprocessed to generate iris
template. The two level Discrete Wavelet Transformation
(DWT) is applied on iris template and Discrete Cosine
Transformation (DCT) is performed on second level low
frequency band to generate DCT coefficients which results in
features of iris. The fingerprint is preprocessed to obtain
Region of Interest (ROI) and segmented into four cells. Then
the DWT is applied on each cell to derive approximation band
and detailed bands. The Fast Fourier Transformation (FFT)
is applied on approximation band to compute absolute values
that results in features of fingerprint. The iris features and
fingerprint features are fused by concatenation to obtain final
set of features. The final feature vector of test and database
are compared using Euclidean distance matching. It is observed
that the values of Total Success Rate (TSR), False Rejection
Rate (FRR) and False Acceptance Rate (FAR) are improved in
the proposed system compared to existing algorithm.
FEATURE EXTRACTION METHODS FOR IRIS RECOGNITION SYSTEM: A SURVEYijcsit
Protection has become one of the biggest fields of study for several years, however the demand for this is growing exponentially mostly with rise in sensitive data. The quality of the research can differ slightly from any workstation to cloud, and though protection must be incredibly important all over. Throughout the past two decades, sufficient focus has been given to substantiation along with validation in the technology model. Identifying a legal person is increasingly become the difficult activity with the progression of time. Some attempts are introduced in that same respect, in particular by utilizing human movements such as fingerprints, facial recognition, palm scanning, retinal identification, DNA checking, breathing, speech checker, and so on. A number of methods for effective iris detection have indeed been suggested and researched. A general overview of current and state-of-the-art approaches to iris recognition is presented in this paper. In addition, significant advances in techniques, algorithms, qualified classifiers, datasets and methodologies for the extraction of features are also discussed.
Fog computing based on face identification in internetummeHani43
It figures out the fog computing techniques basically used through internet.for the face regonisation in crime areas.and also used for the face detection and identification.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Biometric system works on behavioral and physiological biometric parameters to spot a person. Every fingerprint contains distinctive options and its recognizing system primarily works on native ridge feature local ridge endings, minutiae, core point, delta, etc. However, fingerprint pictures have poor quality thanks to variations in skin and impression conditions. In personal identification, fingerprint recognition is taken into account the foremost outstanding and reliable technique for matching with keep fingerprints within the information. Minutiae extraction is additional essential step in fingerprint matching. This paper provides plan regarding numerous feature extraction and matching algorithms for fingerprint recognition systems and to seek out that technique is additional reliable and secure.
Biometric Template Protection With Robust Semi – Blind Watermarking Using Ima...CSCJournals
This paper addresses a biometric watermarking technology sturdy towards image manipulations, like JPEG compression, image filtering, and additive noise. Application scenarios include information transmission between client and server, maintaining e-database and management of signatures through insecure distribution channels. Steps involved in this work are, a) generation of binary signature code for biometric, b) embedding of the binary signature to the host image using intrinsic local property, that ensures signature protection, c) host image is then made exposed to various attacks and d) signature is extracted and matched based on an empirical threshold to verify the robustness of proposed embedding method. Embedding relies on binary signature manipulating the lower order AC coefficients of Discrete Cosine Transformed sub-blocks of host image. In the prediction phase, DC values of the nearest neighbor DCT blocks is utilized to predict the AC coefficients of centre block. Surrounding DC values of a DCT blocks are adaptively weighed for AC coefficients prediction. Linear programming is used to calculate the weights with respect to the image content. Multiple times embedding of watermark ensures robustness against common signal processing operations (filtering, enhancement, rescaling etc.) and various attacks. The proposed algorithm is tested for 50 different types of host images and public data collection, DB3, FVC2002. FAR and FRR are compared with other methods to show the improvement.
HMM-Based Face Recognition System with SVD Parameterijtsrd
Today an increasing digital world, personal reliable authentication has become an important human Computer interface activity. It is very important to establish a persons identity. In today existing security mainly depends on passwords, swipe cards or token based approach and attitude to control access to physical and virtual spaces passport. Universal, such as methods, although very secure. Such as tokens, badges and access cards can be shared or stolen. Passwords and PIN numbers can be also stolen electronically. In addition, they cannot distinguish between authentic have access to or knowledge of the user and tokens. To make a system more secure and simple with the use of biometric authentication system such as face and hand gesture recognition for personal authentication. So in this paper, A Hidden Markov Model (HMM) based face recognition system using Singular Value Decomposition (SVD) is proposed. Neha Rana | Bhavna Pancholi"HMM-Based Face Recognition System with SVD Parameter" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd12938.pdf http://www.ijtsrd.com/engineering/electrical-engineering/12938/hmm-based-face-recognition-system-with-svd-parameter/neha-rana
Reduction of False Acceptance Rate Using Cross Validation for Fingerprint Rec...IJTET Journal
Abstract— In the field of biometric modality fingerprint is considered to be one of the most widely used method for individual identity. The fingerprint authentication is used in most application for security purpose. In the biometric systems, the input images are binarized and feature is extraction. The Minutiae matching in fingerprint identification is done by identifying the minutiae point of interest and their relationship. The validation testing in the proposed system using the method of K- fold cross validation by using two , a training set and test set of images to find the appropriate image that matches the input image ,increase the accuracy of recognition by reducing the false acceptance rate of the system.
Feature Level Fusion of Multibiometric Cryptosystem in Distributed SystemIJMER
ABSTRACT: Multibiometrics is the combination of one or more biometrics (e.g., Fingerprint, Iris, and Face). Researchers
are focusing on how to provide security to the system, the template which was generated from the biometric need to be
protected. The problems of unimodal biometrics are solved by multibiometrics. The main objective is to provide a security to
the biometric template by generating a secure sketch by making use of multibiometric cryptosystem and which is stored in a
database. Once the biometric template is stolen it becomes a serious issue for the security of the system and also for user
privacy. In the existing approach, feature level fusion is used to combine the features securely with well-known biometric
cryptosystems namely fuzzy vault and fuzzy commitment. The drawbacks of existing system include accuracy of the biometric
need to be improved and the noises in the biometrics also need to be reduced. The proposed work is to enhance the security
using multibiometric cryptosystem in distributed system applications like e-commerce transactions, e-banking and ATM.
Keywords: Biometric Cryptosystem, Error correcting code, Fingerprint, Iris, Multibiometrics, Unimodal biometrics.
Handwritten Signature Verification using Artificial Neural NetworkEditor IJMTER
This paper reviews various Signature Verification approaches; various feature sets,
various online databases and types of features. Processing on an online database, post extracting a
combination of global and local features onto a signature as an image, using MultiLayer Perceptron Feed
Forward Network alongwith Back Propogation Algorithm for training is proposed to classify a genuine
and forged (random, simple and skilled) offline signatures.
A Survey Based on Fingerprint Matching SystemIJTET Journal
Abstract — Fingerprint is one of the biometric features mostly used for identification and verification. Latent fingerprints are conventionally recovered coming in to existence of crime scenes and are analyzed with active databases of well-known fingerprints for finding criminals. A bulk of matching algorithms with distant uniqueness has been developed in modern years and the algorithms are depending up on minutiae features. The detection of accepted systems tries to find which fingerprint in a database matches the fingerprint needs the matching of its minutiae against the input fingerprint. Since the detection complexity are more minutiae of other fingerprints. Therefore, fingerprint matching system is a higher than verification and detection systems. This paper discussed about the various novel techniques like Minutia Cylinder Code (MCC) algorithm, Minutia score matching and Graphic Processing Unit (GPU). The feature extraction anywhere in the extracted features is sovereign of shift and rotation of the fingerprint. Meanwhile, the matching operation is performed much more easily and higher accuracy.
Performance Enhancement Of Multimodal Biometrics Using CryptosystemIJERA Editor
Multimodal biometrics means the unification of two or more uni modal biometrics so as to make the system more reliable and secure. Such systems promise better security. This study is a blend of iris and fingerprint recognition technique and their fusion at feature level. Our work comprises of two main sections: feature extraction of both modalities and fusing them before matching and finally application of an encryption technique to enhance the security of the fused template.
Biometrics Authentication of Fingerprint with Using Fingerprint Reader and Mi...TELKOMNIKA JOURNAL
The idea of security is as old as humanity itself. Between oldest methods of security were
included simple mechanical locks whose authentication element was the key. At first, a universal–simple
type, later unique for each lock. A long time had mechanical locks been the sole option for protection
against unauthorized access. The boom of biometrics has come in the 20th century, and especially in
recent years, biometrics is much expanded in the various areas of our life. Opposite of traditional security
methods such as passwords, access cards, and hardware keys, it offers many benefits. The main benefits
are the uniqueness and the impossibility of their loss. The main benefits are the uniqueness and the
impossibility of their loss. Therefore we focussed in this paper on the the design of low cost biometric
fingerprint system and subsequent implementation of this system in praxtise. Our main goal was to create
a system that is capable of recognizing fingerprints from a user and then processing them. The main part
of this system is the microcontroller Arduino Yun with an external interface to the scan of the fingerprint
with a name Adafruit R305 (special reader). This microcontroller communicates with the external database,
which ensures the exchange of data between Arduino Yun and user application. This application was
created for (currently) most widespread mobile operating system-Android.
Facial image classification and searching –a surveyZac Darcy
Recent developments in the area of image mining have shown the way for incredible growth in
extensively large and detailed image databases. The images which are available in these
databases, if checked, can endow with valuable information to the human users. As one of the
most successful applications of image analysis and understanding, fac
e recognition has
recently gained important attention particularly throughout the past many years. Though
tracking and recognizing face objects is a routine task, building such a system is still an active
research. Among several proposed face rec
ognition schemes, shape based approaches are
possibly the most promising ones. This paper provides an overview of various
classification and retrieval methods that were proposed earlier in literature. Also, this paper
provides a margina
l summary for future research and enhancements in face detection
Measuring memetic algorithm performance on image fingerprints datasetTELKOMNIKA JOURNAL
Personal identification has become one of the most important terms in our society regarding access control, crime and forensic identification, banking and also computer system. The fingerprint is the most used biometric feature caused by its unique, universality and stability. The fingerprint is widely used as a security feature for forensic recognition, building access, automatic teller machine (ATM) authentication or payment. Fingerprint recognition could be grouped in two various forms, verification and identification. Verification compares one on one fingerprint data. Identification is matching input fingerprint with data that saved in the database. In this paper, we measure the performance of the memetic algorithm to process the image fingerprints dataset. Before we run this algorithm, we divide our fingerprints into four groups according to its characteristics and make 15 specimens of data, do four partial tests and at the last of work we measure all computation time.
Advanced Authentication Scheme using Multimodal Biometric SchemeEditor IJCATR
Fingerprint recognition has attracted various researchers and achieved great success. But, fingerprint alone may not be able to meet the increasing demand of high accuracy in today‟s biometric system. The purpose of our paper is to inspect whether the integration of palmprint and fingerprint biometric can achieve performance that may not be possible using a single biometric technology. Pre-processing is done for fingerprint and palmprint images separately in order to remove any noise. The next step is feature extraction. Minutiae algorithm is used for fingerprint feature extraction and Local Binary pattern for palmprint. Wavelet fusion is applied in order to fuse the extracted features and Support Vector Machine is used for matching. The main highlight of the project is multimodal biometrics which will give a better security and accuracy comparing to unimodel system.
Fog computing based on face identification in internetummeHani43
It figures out the fog computing techniques basically used through internet.for the face regonisation in crime areas.and also used for the face detection and identification.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Biometric system works on behavioral and physiological biometric parameters to spot a person. Every fingerprint contains distinctive options and its recognizing system primarily works on native ridge feature local ridge endings, minutiae, core point, delta, etc. However, fingerprint pictures have poor quality thanks to variations in skin and impression conditions. In personal identification, fingerprint recognition is taken into account the foremost outstanding and reliable technique for matching with keep fingerprints within the information. Minutiae extraction is additional essential step in fingerprint matching. This paper provides plan regarding numerous feature extraction and matching algorithms for fingerprint recognition systems and to seek out that technique is additional reliable and secure.
Biometric Template Protection With Robust Semi – Blind Watermarking Using Ima...CSCJournals
This paper addresses a biometric watermarking technology sturdy towards image manipulations, like JPEG compression, image filtering, and additive noise. Application scenarios include information transmission between client and server, maintaining e-database and management of signatures through insecure distribution channels. Steps involved in this work are, a) generation of binary signature code for biometric, b) embedding of the binary signature to the host image using intrinsic local property, that ensures signature protection, c) host image is then made exposed to various attacks and d) signature is extracted and matched based on an empirical threshold to verify the robustness of proposed embedding method. Embedding relies on binary signature manipulating the lower order AC coefficients of Discrete Cosine Transformed sub-blocks of host image. In the prediction phase, DC values of the nearest neighbor DCT blocks is utilized to predict the AC coefficients of centre block. Surrounding DC values of a DCT blocks are adaptively weighed for AC coefficients prediction. Linear programming is used to calculate the weights with respect to the image content. Multiple times embedding of watermark ensures robustness against common signal processing operations (filtering, enhancement, rescaling etc.) and various attacks. The proposed algorithm is tested for 50 different types of host images and public data collection, DB3, FVC2002. FAR and FRR are compared with other methods to show the improvement.
HMM-Based Face Recognition System with SVD Parameterijtsrd
Today an increasing digital world, personal reliable authentication has become an important human Computer interface activity. It is very important to establish a persons identity. In today existing security mainly depends on passwords, swipe cards or token based approach and attitude to control access to physical and virtual spaces passport. Universal, such as methods, although very secure. Such as tokens, badges and access cards can be shared or stolen. Passwords and PIN numbers can be also stolen electronically. In addition, they cannot distinguish between authentic have access to or knowledge of the user and tokens. To make a system more secure and simple with the use of biometric authentication system such as face and hand gesture recognition for personal authentication. So in this paper, A Hidden Markov Model (HMM) based face recognition system using Singular Value Decomposition (SVD) is proposed. Neha Rana | Bhavna Pancholi"HMM-Based Face Recognition System with SVD Parameter" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd12938.pdf http://www.ijtsrd.com/engineering/electrical-engineering/12938/hmm-based-face-recognition-system-with-svd-parameter/neha-rana
Reduction of False Acceptance Rate Using Cross Validation for Fingerprint Rec...IJTET Journal
Abstract— In the field of biometric modality fingerprint is considered to be one of the most widely used method for individual identity. The fingerprint authentication is used in most application for security purpose. In the biometric systems, the input images are binarized and feature is extraction. The Minutiae matching in fingerprint identification is done by identifying the minutiae point of interest and their relationship. The validation testing in the proposed system using the method of K- fold cross validation by using two , a training set and test set of images to find the appropriate image that matches the input image ,increase the accuracy of recognition by reducing the false acceptance rate of the system.
Feature Level Fusion of Multibiometric Cryptosystem in Distributed SystemIJMER
ABSTRACT: Multibiometrics is the combination of one or more biometrics (e.g., Fingerprint, Iris, and Face). Researchers
are focusing on how to provide security to the system, the template which was generated from the biometric need to be
protected. The problems of unimodal biometrics are solved by multibiometrics. The main objective is to provide a security to
the biometric template by generating a secure sketch by making use of multibiometric cryptosystem and which is stored in a
database. Once the biometric template is stolen it becomes a serious issue for the security of the system and also for user
privacy. In the existing approach, feature level fusion is used to combine the features securely with well-known biometric
cryptosystems namely fuzzy vault and fuzzy commitment. The drawbacks of existing system include accuracy of the biometric
need to be improved and the noises in the biometrics also need to be reduced. The proposed work is to enhance the security
using multibiometric cryptosystem in distributed system applications like e-commerce transactions, e-banking and ATM.
Keywords: Biometric Cryptosystem, Error correcting code, Fingerprint, Iris, Multibiometrics, Unimodal biometrics.
Handwritten Signature Verification using Artificial Neural NetworkEditor IJMTER
This paper reviews various Signature Verification approaches; various feature sets,
various online databases and types of features. Processing on an online database, post extracting a
combination of global and local features onto a signature as an image, using MultiLayer Perceptron Feed
Forward Network alongwith Back Propogation Algorithm for training is proposed to classify a genuine
and forged (random, simple and skilled) offline signatures.
A Survey Based on Fingerprint Matching SystemIJTET Journal
Abstract — Fingerprint is one of the biometric features mostly used for identification and verification. Latent fingerprints are conventionally recovered coming in to existence of crime scenes and are analyzed with active databases of well-known fingerprints for finding criminals. A bulk of matching algorithms with distant uniqueness has been developed in modern years and the algorithms are depending up on minutiae features. The detection of accepted systems tries to find which fingerprint in a database matches the fingerprint needs the matching of its minutiae against the input fingerprint. Since the detection complexity are more minutiae of other fingerprints. Therefore, fingerprint matching system is a higher than verification and detection systems. This paper discussed about the various novel techniques like Minutia Cylinder Code (MCC) algorithm, Minutia score matching and Graphic Processing Unit (GPU). The feature extraction anywhere in the extracted features is sovereign of shift and rotation of the fingerprint. Meanwhile, the matching operation is performed much more easily and higher accuracy.
Performance Enhancement Of Multimodal Biometrics Using CryptosystemIJERA Editor
Multimodal biometrics means the unification of two or more uni modal biometrics so as to make the system more reliable and secure. Such systems promise better security. This study is a blend of iris and fingerprint recognition technique and their fusion at feature level. Our work comprises of two main sections: feature extraction of both modalities and fusing them before matching and finally application of an encryption technique to enhance the security of the fused template.
Biometrics Authentication of Fingerprint with Using Fingerprint Reader and Mi...TELKOMNIKA JOURNAL
The idea of security is as old as humanity itself. Between oldest methods of security were
included simple mechanical locks whose authentication element was the key. At first, a universal–simple
type, later unique for each lock. A long time had mechanical locks been the sole option for protection
against unauthorized access. The boom of biometrics has come in the 20th century, and especially in
recent years, biometrics is much expanded in the various areas of our life. Opposite of traditional security
methods such as passwords, access cards, and hardware keys, it offers many benefits. The main benefits
are the uniqueness and the impossibility of their loss. The main benefits are the uniqueness and the
impossibility of their loss. Therefore we focussed in this paper on the the design of low cost biometric
fingerprint system and subsequent implementation of this system in praxtise. Our main goal was to create
a system that is capable of recognizing fingerprints from a user and then processing them. The main part
of this system is the microcontroller Arduino Yun with an external interface to the scan of the fingerprint
with a name Adafruit R305 (special reader). This microcontroller communicates with the external database,
which ensures the exchange of data between Arduino Yun and user application. This application was
created for (currently) most widespread mobile operating system-Android.
Facial image classification and searching –a surveyZac Darcy
Recent developments in the area of image mining have shown the way for incredible growth in
extensively large and detailed image databases. The images which are available in these
databases, if checked, can endow with valuable information to the human users. As one of the
most successful applications of image analysis and understanding, fac
e recognition has
recently gained important attention particularly throughout the past many years. Though
tracking and recognizing face objects is a routine task, building such a system is still an active
research. Among several proposed face rec
ognition schemes, shape based approaches are
possibly the most promising ones. This paper provides an overview of various
classification and retrieval methods that were proposed earlier in literature. Also, this paper
provides a margina
l summary for future research and enhancements in face detection
Measuring memetic algorithm performance on image fingerprints datasetTELKOMNIKA JOURNAL
Personal identification has become one of the most important terms in our society regarding access control, crime and forensic identification, banking and also computer system. The fingerprint is the most used biometric feature caused by its unique, universality and stability. The fingerprint is widely used as a security feature for forensic recognition, building access, automatic teller machine (ATM) authentication or payment. Fingerprint recognition could be grouped in two various forms, verification and identification. Verification compares one on one fingerprint data. Identification is matching input fingerprint with data that saved in the database. In this paper, we measure the performance of the memetic algorithm to process the image fingerprints dataset. Before we run this algorithm, we divide our fingerprints into four groups according to its characteristics and make 15 specimens of data, do four partial tests and at the last of work we measure all computation time.
Advanced Authentication Scheme using Multimodal Biometric SchemeEditor IJCATR
Fingerprint recognition has attracted various researchers and achieved great success. But, fingerprint alone may not be able to meet the increasing demand of high accuracy in today‟s biometric system. The purpose of our paper is to inspect whether the integration of palmprint and fingerprint biometric can achieve performance that may not be possible using a single biometric technology. Pre-processing is done for fingerprint and palmprint images separately in order to remove any noise. The next step is feature extraction. Minutiae algorithm is used for fingerprint feature extraction and Local Binary pattern for palmprint. Wavelet fusion is applied in order to fuse the extracted features and Support Vector Machine is used for matching. The main highlight of the project is multimodal biometrics which will give a better security and accuracy comparing to unimodel system.
novel method of identifying fingerprint using minutiae matching in biometric ...INFOGAIN PUBLICATION
Fingerprint is one of the best apparatus to identify human because of its uniqueness, details information, hard to change and long-term indicators of human identity where there are several biometric feature that can be recycled to endorse the individuality. Identification of fingerprint is very important in forensic science, trace any part of human, collection of crime part and proof from a crime. This paper presents a new method of identifying fingerprint in biometrics security system. Fingerprint is one of the best example in biometric security because it can identify personal information and it is much secure than any other biometric identification system. The experimental result exhibits the performance of the proposed method.
Protection has become one of the biggest fields of study for several years, however the demand for this is
growing exponentially mostly with rise in sensitive data. The quality of the research can differ slightly from
any workstation to cloud, and though protection must be incredibly important all over. Throughout the past
two decades, sufficient focus has been given to substantiation along with validation in the technology
model. Identifying a legal person is increasingly become the difficult activity with the progression of time.
Some attempts are introduced in that same respect, in particular by utilizing human movements such as
fingerprints, facial recognition, palm scanning, retinal identification, DNA checking
Role of fuzzy in multimodal biometrics systemKishor Singh
Person identification is possible through the biometrics using their physiological and behavioral characteristics such
as face, ear, thumb print, voice, signature and key stock. Unimodal biometric systems face a range of problems, including noisy
data, intra-class versions, small liberty, non-university, spoof assaults, and unsustainable error rates. Some of these drawbacks
can be overcome by multimodal biometric technologies, which incorporate data from various information sources. In this paper
we work on multimodal biometric using three modalities face, ear and foot to find the optimal results using fuzzy fusion
mechanism and produces final identification decision via a fuzzy rules that enhance the quality of multimodalities biometric
system.
Pre-Processing Image Algorithm for Fingerprint Recognition and its Implementa...ijseajournal
Fingerprint recognition technology is becoming increasingly popular and widely used for many applications that require a high level of security. We can meet several types of sensors integrated in the fingerprint recognition system as well as several types of image processing algorithm in order to ensure
reliable and fast authentication of people. Embedded systems have a wide variety and the choice of a welldesigned
processor is one of the most important factors that directly affect the overall performance of the system. This paper introduces a preliminary treatment to the image in order to improve the quality, and then present a hardware implementation.
BIOMETRIC AND RFID TECHNOLOGY FUSSION: A SECURITY AND MONITORING MEASURES TO ...Henry Chukwuemeka Paul
This paper aims at evaluating, compare the RFID and Biometric technology and report result based on the performances in terms of various parameters that is analyzed. Currently, most schools and institutions do have difficulties to monitor their students’ security and attendance system using either RFID Card or biometrics alone, where the procedures are inefficient in monitoring the students’ security and managing their attendance. The application of RFID Card system as a school monitoring system to improve class attendance procedure, automatically monitor the interest group movements and increases their security. Using RFID makes it easier and faster to detect students’ attendance in a lecture class. In this system, the fingerprint recognition is also adopted to enhance the procedure of identifying authentication of student more securely and reliable for facilities management, gateway access and facilities control, it will also help the school management to provide visibility of assets and effective user tracking.
Feature Extraction and Gesture Recognition_978-81-962236-3-2.pdfTIRUMALAVASU3
Advanced man-machine interfaces may be built using gestural interfaces based on vision
technology, but size of pictures rather than specialized acquisition equipment. Segmentation of
the hand, tracking, and identification of the hand position are the three key issues (feature
extraction and classification). Since the first computer was invented in the modern age,
technology has impacted every aspect of our social and personal life, revolutionizing how we
live. A few examples are browsing the web, writing a message, playing a video game, or saving
and retrieving personal or business data.
The technique of turning raw data into numerical features that can be handled while keeping
the information in the original data set is known as feature extraction. Compared to using
machine learning on the raw data directly, it produces superior outcomes. It is possible to
extract features manually or automatically. Identification and description of the characteristics
that are pertinent to a particular situation are necessary for manual feature extraction, as is the
implementation of a method to extract those features. Having a solid grasp of the context or
domain may often aid in making judgements about which characteristics could be helpful.
Engineers and scientists have created feature extraction techniques for pictures, signals, and
text through many years of study. The mean of a signal's window is an illustration of a
straightforward characteristic. Automated feature extraction eliminates the need for human
involvement by automatically extracting features from signals or pictures using specialized
algorithms or deep networks. When you need to go from collecting raw data to creating
machine learning algorithms rapidly, this method may be quite helpful. An example of
automated feature extraction is wavelet scattering.
Feature Extraction and Gesture Recognition Book.pdfSAMREENFIZA3
Advanced man-machine interfaces may be built using gestural interfaces based on vision
technology, but size of pictures rather than specialized acquisition equipment. Segmentation of
the hand, tracking, and identification of the hand position are the three key issues (feature
extraction and classification). Since the first computer was invented in the modern age,
technology has impacted every aspect of our social and personal life, revolutionizing how we
live. A few examples are browsing the web, writing a message, playing a video game, or saving
and retrieving personal or business data.
The technique of turning raw data into numerical features that can be handled while keeping
the information in the original data set is known as feature extraction. Compared to using
machine learning on the raw data directly, it produces superior outcomes. It is possible to
extract features manually or automatically. Identification and description of the characteristics
that are pertinent to a particular situation are necessary for manual feature extraction, as is the
implementation of a method to extract those features. Having a solid grasp of the context or
domain may often aid in making judgements about which characteristics could be helpful.
Engineers and scientists have created feature extraction techniques for pictures, signals, and
text through many years of study. The mean of a signal's window is an illustration of a
straightforward characteristic. Automated feature extraction eliminates the need for human
involvement by automatically extracting features from signals or pictures using specialized
algorithms or deep networks. When you need to go from collecting raw data to creating
machine learning algorithms rapidly, this method may be quite helpful. An example of
automated feature extraction is wavelet scattering.
The initial layers of deep networks have essentially taken the position of feature extraction with
the rise of deep learning, albeit primarily for picture data. Prior to developing powerful
prediction models for signal and time-series applications, feature extraction continues to be the
first hurdle that demands a high level of knowledge. For this reason, among others, humancomputer interaction (HCI) has been regarded as a vibrant area of study in recent years. The
most popular input devices haven't changed much since they were first introduced, perhaps
because the current devices are still useful and efficient enough. However, it is also generally
known that with the steady release of new software and hardware in recent years, computers
have become more pervasive in daily life. The bulk of human-computer interaction (HCI) today
is based on mechanical devices such a keyboard, mouse, joystick, or game-pad, however due
to their capacity to perform a variety of tasks, a class of computational vision-based approaches
is gaining popularity in natural recognition of human motions.
LUIS: A L IGHT W EIGHT U SER I DENTIFICATION S CHEME FOR S MARTPHONES IJCI JOURNAL
Smartphone usage has reached its peak. There has be
en a tremendous growth in the number of people
migrating from PCs to smart phones. Numerous scenar
ios such as loss of a phone, phone theft etc., can
lead to unauthorized use of one’s own smartphone. T
his raises the concern for securing personal and
private data. This project proposes a light weight
two level user identification scheme to recognize a
nd
authenticate the mobile phone based on the device h
olding and usage patterns. To validate the proposed
scheme, an application is created which takes a ges
ture input characterized by time of swiping the scr
een,
finger pressure, phone movements and location of sw
ipe on the screen through X and Y co-ordinate. A
threshold based matching scheme performs classifica
tion to find the true owner. Results show that the
scheme was able to achieve 90% true positives and 1
0% false positives with a 0.5% of battery usage.
Similar to Various Mathematical and Geometrical Models for Fingerprints: A Survey (20)
Now-a-days, Internet has become an important part of human’s life, a person
can shop, invest, and perform all the banking task online. Almost, all the organizations have
their own website, where customer can perform all the task like shopping, they only have to
provide their credit card details. Online banking and e-commerce organizations have been
experiencing the increase in credit card transaction and other modes of on-line transaction.
Due to this credit card fraud becomes a very popular issue for credit card industry, it causes
many financial losses for customer and also for the organization. Many techniques like
Decision Tree, Neural Networks, Genetic Algorithm based on modern techniques like
Artificial Intelligence, Machine Learning, and Fuzzy Logic have been already developed for
credit card fraud detection. In this paper, an evolutionary Simulated Annealing algorithm is
used to train the Neural Networks for Credit Card fraud detection in real-time scenario.
This paper shows how this technique can be used for credit card fraud detection and
present all the detailed experimental results found when using this technique on real world
financial data (data are taken from UCI repository) to show the effectiveness of this
technique. The algorithm used in this paper are likely beneficial for the organizations and
for individual users in terms of cost and time efficiency. Still there are many cases which are
misclassified i.e. A genuine customer is classified as fraud customer or vise-versa.
Wireless sensor networks (WSN) have been widely used in various applications.
In these networks nodes collect data from the attached sensors and send their data to a base
station. However, nodes in WSN have limited power supply in form of battery so the nodes
are expected to minimize energy consumption in order to maximize the lifetime of WSN. A
number of techniques have been proposed in the literature to reduce the energy
consumption significantly. In this paper, we propose a new clustering based technique
which is a modification of the popular LEACH algorithm. In this technique, first cluster
heads are elected using the improved LEACH algorithm as usual, and then a cluster of
nodes is formed based on the distance between node and cluster head. Finally, data from
node is transferred to cluster head. Cluster heads forward data, after applying aggregation,
to the cluster head that is closer to it than sink in forward direction or directly to the sink.
This reduction in distance travelled improves the performance over LEACH algorithm
significantly.
The next generation wireless networks comprises of mobile users moving
between heterogeneous networks, using terminals with multiple access interfaces and
services. The most important issue in such environment is ABC (Always Best Connected) i.e.
allowing the best connectivity to applications anywhere at any time. For always best
connectivity requirement various vertical handover strategies for decision making have
been proposed. This paper provides an overview of the most interesting and recent
strategies.
This paper presents the design and performance comparison of a two stage
operational amplifier topology using CMOS and BiCMOS technology. This conventional op
amp circuit was designed by using RF model of BSIM3V3 in 0.6 μm CMOS technology and
0.35 μm BiCMOS technology. Both the op amp circuits were designed and simulated,
analyzed and performance parameters are compared. The performance parameters such as
gain, phase margin, CMRR, PSRR, power consumption etc achieved are compared. Finally,
we conclude the suitability of CMOS technology over BiCMOS technology for low power
RF design.
In Cognitive Radio Networks (CRN), Cooperative Spectrum Sensing (CSS) is
used to improve performance of spectrum sensing techniques used for detection of licensed
(Primary) user’s signal. In CSS, the spectrum sensing information from multiple unlicensed
(Secondary) users are combined to take final decision about presence of primary signal. The
mixing techniques used to generate final decision about presence of PU’s signal are also
called as Fusion techniques / rules. The fusion techniques are further classified as data
fusion and decision fusion techniques. In data fusion technique all the secondary users
(SUs) share their raw information of spectrum detection like detected energy or other
statistical information, while in decision fusion technique all the SUs take their local
decisions and share the decision by sending ‘0’ or ‘1’ corresponding to absence and presence
of PU’s signal respectively. The rules used in decision fusion techniques are OR rule, AND
rule and K-out-of-N rule. The CSS is further classified as distributed CSS and centralized
CSS. In distributed CSS all the SUs share the spectrum detection information with each
other and by mixing the shared information; all the SUs take final decision individually. In
centralized CSS all the SUs send their detected information to a secondary base station /
central unit which combines the shared information and takes final decision. The secondary
base station shares the final decision with all the SUs in the CRN. This paper covers
overview of information fusion methods used for CSS and analysis of decision fusion rules
with simulation results.
ZigBee has been developed to support lower data rates and low power consuming
applications. This paper targets to analyze various parameters of ZigBee physical (PHY).
Performance of ZigBee PHY is evaluated on the basis of energy consumption in
transmitting and receiving mode and throughput. Effect of variation in network size is
studied on these performance attributes. Some modulation schemes are also compared and
the best modulation scheme is suggested with tradeoffs between different performance
metrics.
This paper gives a brief idea of the moving objects tracking and its application.
In sport it is challenging to track and detect motion of players in video frames. Task
represents optical flow analysis to do motion detection and particle filter to track players
and taking consideration of regions with movement of players in sports video. Optical flow
vector calculation gives motion of players in video frame. This paper presents improved
Luacs Kanade algorithm explained for optical flow computation for large displacement and
more accuracy in motion estimation.
A rapid progress is seen in the field of robotics both in educational and industrial
automation sectors. The Robotics education in particular is gaining technological advances
and providing more learning opportunities. In automotive sector, there is a necessity and
demand to automate daily human activities by robot. With such an advancement and
demand for robotics, the realization of a popular computer game will help students to learn
and acquire skills in the field of robotics. The computer game such as Pacman offers
challenges on both software and hardware fronts. In software, it provides challenges in
developing algorithms for a robot to escape from the pool of attacking robots and to develop
algorithms for multiple ghost robots to attack the Pacman. On the hardware front, it
provides a challenge to integrate various systems to realize the game. This project aims to
demonstrate the pacman game in real world as well as in simulation. For simulation
purpose Player/Stage is used to develop single-client and multi-client architectures. The
multi- client architecture in player/stage uses one global simulation proxy to which all the
robot models are connected. This reduces the overhead to manage multiple robots proxy.
The single-client architecture enables only two robot models to connect to the simulation
proxy. Multi-client approach offers flexibility to add sensors to each port which will be used
distinctly by the client attached to the respective robot. The robots are named as Pacman
and Ghosts, which try to escape and attack respectively. Use of Network Camera has been
done to detect the global positions of the robots and data is shared through inter-process
communication.
In Content-Based Image Retrieval (CBIR) systems, the visual contents of the
images in the database are took out and represented by multi-dimensional characteristic
vectors. A well known CBIR system that retrieves images by unsupervised method known
as cluster based image retrieval system. For enhancing the performance and retrieval rate
of CBIR system, we fuse the visual contents of an image. Recently, we developed two
cluster-based CBIR systems by fusing the scores of two visual contents of an image. In this
paper, we analyzed the performance of the two recommended CBIR systems at different
levels of precision using images of varying sizes and resolutions. We also compared the
performance of the recommended systems with that of the other two existing CBIR systems
namely UFM and CLUE. Experimentally, we find that the recommended systems
outperform the other two existing systems and one recommended system also comparatively
performed better in every resolution of image.
Information Systems and Networks are subjected to electronic attacks. When
network attacks hit, organizations are thrown into crisis mode. From the IT department to
call centers, to the board room and beyond, all are fraught with danger until the situation is
under control. Traditional methods which are used to overcome these threats (e.g. firewall,
antivirus software, password protection etc.) do not provide complete security to the system.
This encourages the researchers to develop an Intrusion Detection System which is capable
of detecting and responding to such events. This review paper presents a comprehensive
study of Genetic Algorithm (GA) based Intrusion Detection System (IDS). It provides a
brief overview of rule-based IDS, elaborates the implementation issues of Genetic Algorithm
and also presents a comparative analysis of existing studies.
Step by step operations by which we make a group of objects in which attributes
of all the objects are nearly similar, known as clustering. So, a cluster is a collection of
objects that acquire nearly same attribute values. The property of an object in a cluster is
similar to other objects in same cluster but different with objects of other clusters.
Clustering is used in wide range of applications like pattern recognition, image processing,
data analysis, machine learning etc. Nowadays, more attention has been put on categorical
data rather than numerical data. Where, the range of numerical attributes organizes in a
class like small, medium, high, and so on. There is wide range of algorithm that used to
make clusters of given categorical data. Our approach is to enhance the working on well-
known clustering algorithm k-modes to improve accuracy of algorithm. We proposed a new
approach named “High Accuracy Clustering Algorithm for Categorical datasets”.
Brain tumor is a malformed growth of cells within brain which may be
cancerous or non-cancerous. The term ‘malformed’ indicates the existence of tumor. The
tumor may be benign or malignant and it needs medical support for further classification.
Brain tumor must be detected, diagnosed and evaluated in earliest stage. The medical
problems become grave if tumor is detected at the later stage. Out of various technologies
available for diagnosis of brain tumor, MRI is the preferred technology which enables the
diagnosis and evaluation of brain tumor. The current work presents various clustering
techniques that are employed to detect brain tumor. The classification involves classification
of images into normal and malformed (if detected the tumor). The algorithm deals with
steps such as preprocessing, segmentation, feature extraction and classification of MR brain
images. Finally, the confirmatory step is specifying the tumor area by technique called
region of interest.
A Proxy signature scheme enables a proxy signer to sign a message on behalf of
the original signer. In this paper, we propose ECDLP based solution for chen et. al [1]
scheme. We describe efficient and secure Proxy multi signature scheme that satisfy all the
proxy requirements and require only elliptic curve multiplication and elliptic curve addition
which needs less computation overhead compared to modular exponentiations also our
scheme is withstand against original signer forgery and public key substitution attack.
Water marking has been proposed as a method to enhance data security. Text
water marking requires extreme care when embedding additional data within the images
because the additional information must not affect the image quality. Digital water marking
is a method through which we can authenticate images, videos and even texts. Add text
water mark and image water mark to your photos or animated image, protect your
copyright avoid unauthorized use. Water marking functions are not only authentication, but
also protection for such documents against malicious intentions to change such documents
or even claim the rights of such documents. Water marking scheme that hides water
marking in method, not affect the image quality. In this paper method of hiding a data using
LSB replacement technique is proposed.
Today among various medium of data transmission or storage our sensitive data
are not secured with a third-party, that we used to take help of. Cryptography plays an
important role in securing our data from malicious attack. This paper present a partial
image encryption based on bit-planes permutation using Peter De Jong chaotic map for
secure image transmission and storage. The proposed partial image encryption is a raw data
encryption method where bits of some bit-planes are shuffled among other bit-planes based
on chaotic maps proposed by Peter De Jong. By using the chaotic behavior of the Peter De
Jong map the position of all the bit-planes are permuted. The result of the several
experimental, correlation analysis and sensitivity test shows that the proposed image
encryption scheme provides an efficient and secure way for real-time image encryption and
decryption.
This paper presents a survey of Dependency Analysis of Service Oriented
Architecture (SOA) based systems. SOA presents newer aspects of dependency analysis due
to its different architectural style and programming paradigm. This paper surveys the
previous work taken on dependency analysis of service oriented systems. This study shows
the strengths and weaknesses of current approaches and tools available for dependency
analysis task in context of SOA. The main motivation of this work is to summarize the
recent approaches in this field of research, identify major issue and challenges in
dependency analysis of SOA based systems and motivate further research on this topic.
In this paper, proposed a novel implementation of a Soft-Core system using
micro-blaze processor with virtex-5 FPGA. Till now Hard-Core processors are used in
FPGA processor cores. Hard cores are a fixed gate-level IP functions within the FPGA
fabrics. Now the proposed processor is Soft-Core Processor, this is a microprocessor fully
described in software, usually in an HDL. This can be implemented by using EDK tool. In
this paper, developed a system which is having a micro-blaze processor is the combination
of both hardware & Software. By using this system, user can control and communicate all
the peripherals which are in the supported board by using Xilinx platform to develop an
embedded system. Implementing of Soft-Core process system with different peripherals like
UART interface, SPA flash interface, SRAM interface has to be designed using Xilinx
Embedded Development Kit (EDK) tools.
The article presents a simple algorithm to construct minimum spanning tree and
to find shortest path between pair of vertices in a graph. Our illustration includes the proof
of termination. The complexity analysis and simulation results have also been included.
Wimax technology has reshaped the framework of broadband wireless internet
service. It provides the internet service to unconnected or detached areas such as east South
Africa, rural areas of America and Asia region. Full duplex helpers employed with one of
the relay stations selection and indexing method that is Randomized Distributed Space Time
are used to expand the coverage area of primary Wimax station. The basic problem was
identified at cell edge due to weather conditions (rain, fog), insertion of destruction because
of multiple paths in the same communication channel and due to interference created by
other users in that communication. It is impractical task for the receiver station to decode
the transmitted signal successfully at the cell edges, which increases the high packet loss and
retransmissions. But Wimax is a outstanding technology which is used for improving the
quality of internet service and also it offers various services like Voice over Internet
Protocol, Video conferencing and Multimedia broadcast etc where a little delay in packet
transmission can cause a big loss in the communication. Even setup and initialization of
another Wimax station nearer to each other is not a good alternate, where any mobile
station can easily handover to another base station if it gets a strong signal from other one.
But in rural areas, for few numbers of customers, installation of base station nearer to each
other is costlier task. In this review article, we present a scheme using R-DSTC technique to
choose and select helpers (relay nodes) randomly to expand the coverage area and help to
mobile station as a helper to provide secure communication with base station. In this work,
we use full duplex helpers for better utilization of bandwidth.
Radio Frequency identification (RFID) technology has become emerging
technique for tracking and items identification. Depend upon the function; various RFID
technologies could be used. Drawback of passive RFID technology, associated to the range
of reading tags and assurance in difficult environmental condition, puts boundaries on
performance in the real life situation [1]. To improve the range of reading tags and
assurance, we consider implementing active backscattering tag technology. For making
mobiles of multiple radio standards in 4G network; the Software Defined Radio (SDR)
technology is used. Restrictions in Existing RFID technologies and SDR technology, can be
eliminated by the development and implementation of the Software Defined Radio (SDR)
active backscattering tag compatible with the EPC global UHF Class 1 Generation 2 (Gen2)
RFID standard. Such technology can be used for many of applications and services.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.