This lab report describes developing a program to perform string operations using suffix arrays. It includes 3 modules: 1) Finding the longest repeated substring, 2) Finding the longest common substring, and 3) Finding the longest palindrome in a string. The report provides code for building a suffix tree from a string and performing traversal to solve each problem. It also includes sample outputs and references.
BIDIRECTIONAL LONG SHORT-TERM MEMORY (BILSTM)WITH CONDITIONAL RANDOM FIELDS (...ijnlc
This study investigates the effectiveness of Knowledge Named Entity Recognition in Online Judges (OJs). OJs are lacking in the classification of topics and limited to the IDs only. Therefore a lot of time is consumed in finding programming problems more specifically in knowledge entities.A Bidirectional Long Short-Term Memory (BiLSTM) with Conditional Random Fields (CRF) model is applied for the recognition of knowledge named entities existing in the solution reports.For the test run, more than 2000 solution reports are crawled from the Online Judges and processed for the model output. The stability of the model is
also assessed with the higher F1 value. The results obtained through the proposed BiLSTM-CRF model are more effectual (F1: 98.96%) and efficient in lead-time.
Dimensionality Reduction and Feature Selection Methods for Script Identificat...ITIIIndustries
The goal of this research is to explore effects of dimensionality reduction and feature selection on the problem of script identification from images of printed documents. The kadjacent segment is ideal for this use due to its ability to capture visual patterns. We have used principle component analysis to reduce the size of our feature matrix to a handier size that can be trained easily, and experimented by including varying combinations of dimensions of the super feature set. A modular
approach in neural network was used to classify 7 languages – Arabic, Chinese, English, Japanese, Tamil, Thai and Korean.
EXTRACTIVE SUMMARIZATION WITH VERY DEEP PRETRAINED LANGUAGE MODELijaia
The document presents a new model for extractive text summarization that uses BERT (Bidirectional Encoder Representations from Transformers), a pretrained deep bidirectional transformer model, as the text encoder. The model consists of a BERT encoder and a sentence classifier. Sentences are encoded using BERT and classified as to whether they should be included in the summary. Evaluation on the CNN/Daily Mail corpus shows the model achieves state-of-the-art results comparable to other top models according to automatic metrics and human evaluation, making it the first work to apply BERT to text summarization.
Paper presentation for the final course Advanced Concept in Machine Learning.
The paper is @Topic Modeling using Topics from Many Domains, Lifelong Learning and Big Data"
http://jmlr.org/proceedings/papers/v32/chenf14.pdf
This document outlines the syllabus for Computer Science class XI. It covers 5 units:
1) Programming and Computational Thinking which focuses on Python programming, data structures, algorithms and debugging.
2) Computer Systems and Organization including basic computer architecture, software, data representation and cloud computing.
3) Data Management covering relational databases, SQL commands and NoSQL databases.
4) Society, Law and Ethics with a focus on cyber safety, appropriate social media usage and safely accessing the web.
5) Practical sessions including Python programs, SQL queries, a report file, viva and a semester project applying concepts learned.
IRJET - Speech to Speech Translation using Encoder Decoder ArchitectureIRJET Journal
This document summarizes a research paper on speech-to-speech translation using an encoder-decoder architecture. It describes a system that takes speech in one language as input, recognizes the speech to generate text, translates the text to another language, and synthesizes speech in the other language as output. The system consists of three main modules: speech recognition in the source language, text translation between languages, and speech generation in the target language. It aims to enable two-way translation between spoken sentences in different languages.
Somasundaram Rajarathinavelu has a Bachelor's degree in Electronics and Communication Engineering with a 7.2 CGPA. His undergraduate project involved implementing and analyzing a 32nm FinFET using a multiplier design. For his diploma project, he created a system to automatically display the station name and provide voice alerts for train passengers based on real-time GPS location data. He has skills in languages like Java, SQL, and Embedded C, as well as tools like Eclipse, MATLAB, and Xilinx. He is currently taking a course in Java, J2EE, and SQL and has experience in networking, .NET, and embedded systems.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
BIDIRECTIONAL LONG SHORT-TERM MEMORY (BILSTM)WITH CONDITIONAL RANDOM FIELDS (...ijnlc
This study investigates the effectiveness of Knowledge Named Entity Recognition in Online Judges (OJs). OJs are lacking in the classification of topics and limited to the IDs only. Therefore a lot of time is consumed in finding programming problems more specifically in knowledge entities.A Bidirectional Long Short-Term Memory (BiLSTM) with Conditional Random Fields (CRF) model is applied for the recognition of knowledge named entities existing in the solution reports.For the test run, more than 2000 solution reports are crawled from the Online Judges and processed for the model output. The stability of the model is
also assessed with the higher F1 value. The results obtained through the proposed BiLSTM-CRF model are more effectual (F1: 98.96%) and efficient in lead-time.
Dimensionality Reduction and Feature Selection Methods for Script Identificat...ITIIIndustries
The goal of this research is to explore effects of dimensionality reduction and feature selection on the problem of script identification from images of printed documents. The kadjacent segment is ideal for this use due to its ability to capture visual patterns. We have used principle component analysis to reduce the size of our feature matrix to a handier size that can be trained easily, and experimented by including varying combinations of dimensions of the super feature set. A modular
approach in neural network was used to classify 7 languages – Arabic, Chinese, English, Japanese, Tamil, Thai and Korean.
EXTRACTIVE SUMMARIZATION WITH VERY DEEP PRETRAINED LANGUAGE MODELijaia
The document presents a new model for extractive text summarization that uses BERT (Bidirectional Encoder Representations from Transformers), a pretrained deep bidirectional transformer model, as the text encoder. The model consists of a BERT encoder and a sentence classifier. Sentences are encoded using BERT and classified as to whether they should be included in the summary. Evaluation on the CNN/Daily Mail corpus shows the model achieves state-of-the-art results comparable to other top models according to automatic metrics and human evaluation, making it the first work to apply BERT to text summarization.
Paper presentation for the final course Advanced Concept in Machine Learning.
The paper is @Topic Modeling using Topics from Many Domains, Lifelong Learning and Big Data"
http://jmlr.org/proceedings/papers/v32/chenf14.pdf
This document outlines the syllabus for Computer Science class XI. It covers 5 units:
1) Programming and Computational Thinking which focuses on Python programming, data structures, algorithms and debugging.
2) Computer Systems and Organization including basic computer architecture, software, data representation and cloud computing.
3) Data Management covering relational databases, SQL commands and NoSQL databases.
4) Society, Law and Ethics with a focus on cyber safety, appropriate social media usage and safely accessing the web.
5) Practical sessions including Python programs, SQL queries, a report file, viva and a semester project applying concepts learned.
IRJET - Speech to Speech Translation using Encoder Decoder ArchitectureIRJET Journal
This document summarizes a research paper on speech-to-speech translation using an encoder-decoder architecture. It describes a system that takes speech in one language as input, recognizes the speech to generate text, translates the text to another language, and synthesizes speech in the other language as output. The system consists of three main modules: speech recognition in the source language, text translation between languages, and speech generation in the target language. It aims to enable two-way translation between spoken sentences in different languages.
Somasundaram Rajarathinavelu has a Bachelor's degree in Electronics and Communication Engineering with a 7.2 CGPA. His undergraduate project involved implementing and analyzing a 32nm FinFET using a multiplier design. For his diploma project, he created a system to automatically display the station name and provide voice alerts for train passengers based on real-time GPS location data. He has skills in languages like Java, SQL, and Embedded C, as well as tools like Eclipse, MATLAB, and Xilinx. He is currently taking a course in Java, J2EE, and SQL and has experience in networking, .NET, and embedded systems.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Bca(rev syll ii-sem) assignment for july 2012 and jan 2013 sessionnShripad Tawade
This document contains assignments for the second semester of the Bachelor of Computer Applications (BCA) program for the year 2012. It includes assignments for 6 courses - MCS-011 Problem Solving and Programming, MCS-012 Computer Organisation and Assembly Language Programming, MCS-013 Data Structure, MCS-015 Operating System, BCSL-021 Computer Oriented Statistical Techniques, and BCSL-022 Discrete Mathematics. The assignments provide questions to test students' understanding of the course content and must be submitted by October 15th for the July session or April 15th for the January session.
Name a naming mechanism for delay disruption tolerant networkIJCNCJournal
This paper presents the design and implementation of the naming mechanism (NAME), a resource
discovery and service location approach for Delay/Disruption-Tolerant Network (DTN). First discuss the
architecture of NAME mainly including Name Knowledge Base, Name Dissemination, Name Resolution
and Name-based Routing. In the design and implementation of NAME, we introduce the simple namespecifiers
to describe name, the name-tree for name storage and the efficient predicate-based routing
algorithm. Future work is finally discussed for completing NAME and providing APIs for abundant
applications.
The evaluation performance of letter-based technique on text steganography sy...journalBEEI
Steganography is a part of information hiding in covering the hidden message in any medium such as text, image, audio, video and others. This paper concerns about the implementation of steganography in text domain called text steganography. It intends to concentrate on letter-based technique as one of the representative techniques in text steganography. This paper displays some techniques of letter-based that is integrated in one system technique displayeed in a logical and physical design. The integrated system is evaluated using some parameter that is used in order to discover the performance in term of capacity after embedding process and the time consuming in the development process. This paper is anticipated to contribute in describing the implementation of the techniques in one system and to display the performance some parameter evaluation.
Classification of Health Forum Messages using Deep LearningSejal Naidu
This document discusses using deep learning models to classify health forum messages into 7 categories. It explores using word2vec and doc2vec to create feature vectors from text, and then feeding these into deep neural network (DNN), convolutional neural network (CNN), and long short-term memory (LSTM) models for classification. The CNN achieved the best results, with an accuracy of 50%. The document concludes that performance could be improved by handling medical terms not in the training dictionary.
Digital Watermarking through Embedding of Encrypted and Arithmetically Compre...IJNSA Journal
In this paper, we have encrypted a text to an array of data bits through arithmetic coding technique. For this, we have assigned a unique range for both, a number of characters and groups using those. Using unique range we may assign range only 10 characters. If we want to encrypt a large number of characters, then every character has to assign a range with their group range of hundred, thousand and so on. Long textual message which have to encrypt, is subdivided into a number of groups with few characters. Then the group of characters is encrypted into floating point numbers concurrently to their group range by using arithmetic coding, where they are automatically compressed. Depending on key, the data bits from text are placed to some suitable nonlinear pixel and bit positions about the image. In the proposed technique, the key length and the number of characters for any encryption process is both variable
Arabic named entity recognition using deep learning approachIJECEIAES
Most of the Arabic Named Entity Recognition (NER) systems depend massively on external resources and handmade feature engineering to achieve state-of-the-art results. To overcome such limitations, we proposed, in this paper, to use deep learning approach to tackle the Arabic NER task. We introduced a neural network architecture based on bidirectional Long Short-Term Memory (LSTM) and Conditional Random Fields (CRF) and experimented with various commonly used hyperparameters to assess their effect on the overall performance of our system. Our model gets two sources of information about words as input: pre-trained word embeddings and character-based representations and eliminated the need for any task-specific knowledge or feature engineering. We obtained state-of-the-art result on the standard ANERcorp corpus with an F1 score of 90.6%.
Performance Comparison of Automatic Speaker Recognition using Vector Quantiza...CSCJournals
This document compares the performance of three automatic speaker recognition methods using vector quantization for feature extraction and codebook generation: LBG, KFCG, and KMCG. It finds that KMCG achieves the highest accuracy for both text-dependent and text-independent identification, with accuracy increasing as the number of feature vectors increases. KFCG also performs well with consistent results. While LBG achieves good accuracy, its performance decreases as more feature vectors are used. KFCG and KMCG are also faster algorithms than LBG since they only require simple comparisons rather than Euclidean distance calculations.
This document summarizes a research paper that evaluates and compares neural network and hidden Markov model classifiers for handwritten word recognition. It begins by introducing the topic of handwritten word recognition and defining the problem. It then provides background on common approaches, including segmentation-based and segmentation-free. The methodology section outlines the proposed system, which uses both a neural network classifier based on multilayer perceptron trained with backpropagation, and a hidden Markov model classifier with two states. It describes training both classifiers on data and then using them to recognize input words by comparing their scores. The paper aims to take advantage of both classifiers by combining their results.
Fundamentals of Computer Organization(FCO)2610004_wefjune2012mubbishekh
This document outlines the course objectives, prerequisites, contents, reference books, and accomplishments for the "Fundamentals of Computer Organization" course. The course aims to teach students the elements of computer organization and architecture, as well as the basic hardware operation of digital computers. Over 11 units and 53 lectures, topics include basic computer components, number systems, Boolean algebra, logic gates, memory, buses, and the Intel 8086 architecture. Reference materials include the textbooks "Digital Computer Fundamentals" and "Microprocessor 8086 – Architecture, Programming and Interfacing". Upon completing the course, students will have knowledge of computer organization and architecture, and understand the actual working and organization of digital computer systems.
ESR11 Hoang Cuong - EXPERT Summer School - Malaga 2015RIILP
This document presents a method for latent domain word alignment to improve alignment accuracy when training on heterogeneous corpora containing data from different domains. It proposes adding a latent domain layer to the standard hidden Markov alignment model to condition alignment probabilities on the domain. The model is trained using an EM algorithm with partial domain supervision from seed samples. Experimental results show the latent domain model improves over a baseline by disentangling domain-specific translation relationships and alignment probabilities, achieving higher precision, recall and lower alignment error rates.
The document presents an ensemble model for chunking natural language text that combines a transformer model (RoBERTa) with a bidirectional LSTM and CNN model. The authors train these models on common chunking datasets like CoNLL 2000 and English Penn Treebank. They find that by using an ensemble of the transformer and RNN-CNN models, which compensate for each other's weaknesses, they are able to achieve state-of-the-art results on chunking, with an F1 score of 97.3% on CoNLL 2000, exceeding previous work. The transformer model provides attention-based contextual embeddings while the RNN-CNN model uses custom embeddings including POS tags to improve accuracy on tags that the transformer model struggles with.
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
or
Call us at : 08263069601
Full Communication in a Wireless Sensor Network by Merging Blocks of a Key Pr...cscpconf
Wireless Sensor Networks (WSN) are constraint by the limited resources available to its
constituting sensors. Thus the use of public-key cryptographyduring message exchange gets
forbidden. One has to invoke symmetric key techniques. This leads to key distribution in the
sensors which in itself is a major challenge. Again due to resource constraints, Key
Predistrubution (KPD) methods are preferred to other distribution techniques. It requires
predistribution of keys in nodes prior to deployment and establishing immediately once
deployed. However there are certain weaknesses in various existing KPD schemes. For
instance, often it is not guaranteed that any given pair of nodes communicate directly. This
leads one to revert to multi-hop communication involving intermediate sensor nodes resulting
in increased cost of communication. In this work a key predistribution technique using ReedSolomon
codes is considered which is faced with the above weakness. The authors suggests a
novel technique of merging certain number of sensors into blocks ensuring that the blocks
have full connectivity amongst themselves. Here the blocks are chosen in such a way that it
ensures no intra-node communication. Further this approach improves both time and space
complexity of the system
This paper presents machine translation based on machine learning, which learns the semantically
correct corpus. The machine learning process based on Quantum Neural Network (QNN) is used to
recognizing the corpus pattern in realistic way. It translates on the basis of knowledge gained during
learning by entering pair of sentences from source to target language. By taking help of this training data
it translates the given text. own text.The paper consist study of a machine translation system which
converts source language to target language using quantum neural network. Rather than comparing
words semantically QNN compares numerical tags which is faster and accurate. In this tagger tags the
part of sentences discretely which helps to map bilingual sentences.
This document summarizes key object oriented concepts in C++ across two chapters.
Chapter 1 discusses object oriented concepts like encapsulation, polymorphism, inheritance and their differences. It also lists advantages of OOP like reusability and security through data hiding.
Chapter 2 provides an overview of C++ tokens, data types, variables, constants, operators and basic statements. It describes keywords, identifiers, user-defined types like structures and enumerations. Storage classes, pointers, arrays and derived types are also covered.
The document comprehensively covers fundamental concepts to understand object oriented programming using C++.
This document summarizes an algorithm to detect algorithm names in computer science research papers. It involves converting PDFs to text, performing named entity recognition to extract noun phrases, filtering entities to remove author names and locations, and using a word2vec model trained on computer science papers to classify extracted tokens as true algorithm names or noisy data by comparing their similarity to known positives and negatives. The top similar words are used to label each token as a true or false positive for an algorithm name.
A New Key Agreement Protocol Using BDP and CSP in Non Commutative GroupsEswar Publications
The available key agreement schemes using number theoretic, elliptic curves etc are common for cryptanalysts and associated security is vulnerable. This vulnerability further increases when we talk about modern efficient computers. So there is a need of providing new mechanism for key agreement with different properties so intruders get surprised and communication scenarios becomes stronger than before. In this paper, we propose a key agreement protocol which works in a non commutative group. We prove that our protocol meets the desired security attributes under the assumption that Conjugacy Search Problem and Decomposition Problem are hard in non commutative groups.
The document provides an overview of MPEG-4, a standard that offers both advanced audio and video codecs as well as tools for combining multimedia such as audio, video, graphics and interactivity. It was developed through an open international process to select the best technologies. MPEG-4 codecs like AVC and AAC provide high compression efficiency, having been adopted for HDTV, mobile video, and digital music. Its rich media tools allow interactive experiences combining different media types.
This document provides an overview of service information (SI) in digital video broadcasting (DVB) systems, including sections like the network information section (NIT), service description section (SDT), bouquet association section (BAT), program association section (PAT), conditional access section (CAT), transport stream description section (TSDT), event information section (EIT), and running status section (RST). It includes syntax diagrams and details for each section, such as table IDs, section lengths, descriptors, and other fields. It also provides the PID and refresh interval requirements for each table type.
H.120 was the first digital video coding standard developed in 1984. H.261 in the late 1980s was the first widespread success and established the modern structure for video compression that is still used today. MPEG-1 and MPEG-2/H.262 built upon H.261 with improvements like bidirectional prediction and half-pixel motion compensation. H.263 further enhanced compression performance and is now dominant for videoconferencing, adding features such as overlapped block motion compensation.
The document discusses DCT/IDCT concepts and applications. It provides an introduction to DCT and IDCT, explaining that they are used widely in video and audio compression. It describes the DCT and IDCT functions and how they work to transform signals between spatial and frequency domains. Examples of one-dimensional and two-dimensional DCT/IDCT equations are also given. Finally, common applications of DCT/IDCT compression techniques are listed, such as in DVD players, cable TV, graphics cards, and medical imaging systems.
This document contains information and forms related to the UGC National Eligibility Test for Junior Research Fellowship and Eligibility for Lectureship that will take place on June 28, 2009. It includes an application form to apply for the exam, instructions on filling out the form, an attendance slip for the exam day, and an admission card with exam details. The forms request information such as educational qualifications, exam subject and center, and contact details.
Bca(rev syll ii-sem) assignment for july 2012 and jan 2013 sessionnShripad Tawade
This document contains assignments for the second semester of the Bachelor of Computer Applications (BCA) program for the year 2012. It includes assignments for 6 courses - MCS-011 Problem Solving and Programming, MCS-012 Computer Organisation and Assembly Language Programming, MCS-013 Data Structure, MCS-015 Operating System, BCSL-021 Computer Oriented Statistical Techniques, and BCSL-022 Discrete Mathematics. The assignments provide questions to test students' understanding of the course content and must be submitted by October 15th for the July session or April 15th for the January session.
Name a naming mechanism for delay disruption tolerant networkIJCNCJournal
This paper presents the design and implementation of the naming mechanism (NAME), a resource
discovery and service location approach for Delay/Disruption-Tolerant Network (DTN). First discuss the
architecture of NAME mainly including Name Knowledge Base, Name Dissemination, Name Resolution
and Name-based Routing. In the design and implementation of NAME, we introduce the simple namespecifiers
to describe name, the name-tree for name storage and the efficient predicate-based routing
algorithm. Future work is finally discussed for completing NAME and providing APIs for abundant
applications.
The evaluation performance of letter-based technique on text steganography sy...journalBEEI
Steganography is a part of information hiding in covering the hidden message in any medium such as text, image, audio, video and others. This paper concerns about the implementation of steganography in text domain called text steganography. It intends to concentrate on letter-based technique as one of the representative techniques in text steganography. This paper displays some techniques of letter-based that is integrated in one system technique displayeed in a logical and physical design. The integrated system is evaluated using some parameter that is used in order to discover the performance in term of capacity after embedding process and the time consuming in the development process. This paper is anticipated to contribute in describing the implementation of the techniques in one system and to display the performance some parameter evaluation.
Classification of Health Forum Messages using Deep LearningSejal Naidu
This document discusses using deep learning models to classify health forum messages into 7 categories. It explores using word2vec and doc2vec to create feature vectors from text, and then feeding these into deep neural network (DNN), convolutional neural network (CNN), and long short-term memory (LSTM) models for classification. The CNN achieved the best results, with an accuracy of 50%. The document concludes that performance could be improved by handling medical terms not in the training dictionary.
Digital Watermarking through Embedding of Encrypted and Arithmetically Compre...IJNSA Journal
In this paper, we have encrypted a text to an array of data bits through arithmetic coding technique. For this, we have assigned a unique range for both, a number of characters and groups using those. Using unique range we may assign range only 10 characters. If we want to encrypt a large number of characters, then every character has to assign a range with their group range of hundred, thousand and so on. Long textual message which have to encrypt, is subdivided into a number of groups with few characters. Then the group of characters is encrypted into floating point numbers concurrently to their group range by using arithmetic coding, where they are automatically compressed. Depending on key, the data bits from text are placed to some suitable nonlinear pixel and bit positions about the image. In the proposed technique, the key length and the number of characters for any encryption process is both variable
Arabic named entity recognition using deep learning approachIJECEIAES
Most of the Arabic Named Entity Recognition (NER) systems depend massively on external resources and handmade feature engineering to achieve state-of-the-art results. To overcome such limitations, we proposed, in this paper, to use deep learning approach to tackle the Arabic NER task. We introduced a neural network architecture based on bidirectional Long Short-Term Memory (LSTM) and Conditional Random Fields (CRF) and experimented with various commonly used hyperparameters to assess their effect on the overall performance of our system. Our model gets two sources of information about words as input: pre-trained word embeddings and character-based representations and eliminated the need for any task-specific knowledge or feature engineering. We obtained state-of-the-art result on the standard ANERcorp corpus with an F1 score of 90.6%.
Performance Comparison of Automatic Speaker Recognition using Vector Quantiza...CSCJournals
This document compares the performance of three automatic speaker recognition methods using vector quantization for feature extraction and codebook generation: LBG, KFCG, and KMCG. It finds that KMCG achieves the highest accuracy for both text-dependent and text-independent identification, with accuracy increasing as the number of feature vectors increases. KFCG also performs well with consistent results. While LBG achieves good accuracy, its performance decreases as more feature vectors are used. KFCG and KMCG are also faster algorithms than LBG since they only require simple comparisons rather than Euclidean distance calculations.
This document summarizes a research paper that evaluates and compares neural network and hidden Markov model classifiers for handwritten word recognition. It begins by introducing the topic of handwritten word recognition and defining the problem. It then provides background on common approaches, including segmentation-based and segmentation-free. The methodology section outlines the proposed system, which uses both a neural network classifier based on multilayer perceptron trained with backpropagation, and a hidden Markov model classifier with two states. It describes training both classifiers on data and then using them to recognize input words by comparing their scores. The paper aims to take advantage of both classifiers by combining their results.
Fundamentals of Computer Organization(FCO)2610004_wefjune2012mubbishekh
This document outlines the course objectives, prerequisites, contents, reference books, and accomplishments for the "Fundamentals of Computer Organization" course. The course aims to teach students the elements of computer organization and architecture, as well as the basic hardware operation of digital computers. Over 11 units and 53 lectures, topics include basic computer components, number systems, Boolean algebra, logic gates, memory, buses, and the Intel 8086 architecture. Reference materials include the textbooks "Digital Computer Fundamentals" and "Microprocessor 8086 – Architecture, Programming and Interfacing". Upon completing the course, students will have knowledge of computer organization and architecture, and understand the actual working and organization of digital computer systems.
ESR11 Hoang Cuong - EXPERT Summer School - Malaga 2015RIILP
This document presents a method for latent domain word alignment to improve alignment accuracy when training on heterogeneous corpora containing data from different domains. It proposes adding a latent domain layer to the standard hidden Markov alignment model to condition alignment probabilities on the domain. The model is trained using an EM algorithm with partial domain supervision from seed samples. Experimental results show the latent domain model improves over a baseline by disentangling domain-specific translation relationships and alignment probabilities, achieving higher precision, recall and lower alignment error rates.
The document presents an ensemble model for chunking natural language text that combines a transformer model (RoBERTa) with a bidirectional LSTM and CNN model. The authors train these models on common chunking datasets like CoNLL 2000 and English Penn Treebank. They find that by using an ensemble of the transformer and RNN-CNN models, which compensate for each other's weaknesses, they are able to achieve state-of-the-art results on chunking, with an F1 score of 97.3% on CoNLL 2000, exceeding previous work. The transformer model provides attention-based contextual embeddings while the RNN-CNN model uses custom embeddings including POS tags to improve accuracy on tags that the transformer model struggles with.
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
or
Call us at : 08263069601
Full Communication in a Wireless Sensor Network by Merging Blocks of a Key Pr...cscpconf
Wireless Sensor Networks (WSN) are constraint by the limited resources available to its
constituting sensors. Thus the use of public-key cryptographyduring message exchange gets
forbidden. One has to invoke symmetric key techniques. This leads to key distribution in the
sensors which in itself is a major challenge. Again due to resource constraints, Key
Predistrubution (KPD) methods are preferred to other distribution techniques. It requires
predistribution of keys in nodes prior to deployment and establishing immediately once
deployed. However there are certain weaknesses in various existing KPD schemes. For
instance, often it is not guaranteed that any given pair of nodes communicate directly. This
leads one to revert to multi-hop communication involving intermediate sensor nodes resulting
in increased cost of communication. In this work a key predistribution technique using ReedSolomon
codes is considered which is faced with the above weakness. The authors suggests a
novel technique of merging certain number of sensors into blocks ensuring that the blocks
have full connectivity amongst themselves. Here the blocks are chosen in such a way that it
ensures no intra-node communication. Further this approach improves both time and space
complexity of the system
This paper presents machine translation based on machine learning, which learns the semantically
correct corpus. The machine learning process based on Quantum Neural Network (QNN) is used to
recognizing the corpus pattern in realistic way. It translates on the basis of knowledge gained during
learning by entering pair of sentences from source to target language. By taking help of this training data
it translates the given text. own text.The paper consist study of a machine translation system which
converts source language to target language using quantum neural network. Rather than comparing
words semantically QNN compares numerical tags which is faster and accurate. In this tagger tags the
part of sentences discretely which helps to map bilingual sentences.
This document summarizes key object oriented concepts in C++ across two chapters.
Chapter 1 discusses object oriented concepts like encapsulation, polymorphism, inheritance and their differences. It also lists advantages of OOP like reusability and security through data hiding.
Chapter 2 provides an overview of C++ tokens, data types, variables, constants, operators and basic statements. It describes keywords, identifiers, user-defined types like structures and enumerations. Storage classes, pointers, arrays and derived types are also covered.
The document comprehensively covers fundamental concepts to understand object oriented programming using C++.
This document summarizes an algorithm to detect algorithm names in computer science research papers. It involves converting PDFs to text, performing named entity recognition to extract noun phrases, filtering entities to remove author names and locations, and using a word2vec model trained on computer science papers to classify extracted tokens as true algorithm names or noisy data by comparing their similarity to known positives and negatives. The top similar words are used to label each token as a true or false positive for an algorithm name.
A New Key Agreement Protocol Using BDP and CSP in Non Commutative GroupsEswar Publications
The available key agreement schemes using number theoretic, elliptic curves etc are common for cryptanalysts and associated security is vulnerable. This vulnerability further increases when we talk about modern efficient computers. So there is a need of providing new mechanism for key agreement with different properties so intruders get surprised and communication scenarios becomes stronger than before. In this paper, we propose a key agreement protocol which works in a non commutative group. We prove that our protocol meets the desired security attributes under the assumption that Conjugacy Search Problem and Decomposition Problem are hard in non commutative groups.
The document provides an overview of MPEG-4, a standard that offers both advanced audio and video codecs as well as tools for combining multimedia such as audio, video, graphics and interactivity. It was developed through an open international process to select the best technologies. MPEG-4 codecs like AVC and AAC provide high compression efficiency, having been adopted for HDTV, mobile video, and digital music. Its rich media tools allow interactive experiences combining different media types.
This document provides an overview of service information (SI) in digital video broadcasting (DVB) systems, including sections like the network information section (NIT), service description section (SDT), bouquet association section (BAT), program association section (PAT), conditional access section (CAT), transport stream description section (TSDT), event information section (EIT), and running status section (RST). It includes syntax diagrams and details for each section, such as table IDs, section lengths, descriptors, and other fields. It also provides the PID and refresh interval requirements for each table type.
H.120 was the first digital video coding standard developed in 1984. H.261 in the late 1980s was the first widespread success and established the modern structure for video compression that is still used today. MPEG-1 and MPEG-2/H.262 built upon H.261 with improvements like bidirectional prediction and half-pixel motion compensation. H.263 further enhanced compression performance and is now dominant for videoconferencing, adding features such as overlapped block motion compensation.
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This document contains information and forms related to the UGC National Eligibility Test for Junior Research Fellowship and Eligibility for Lectureship that will take place on June 28, 2009. It includes an application form to apply for the exam, instructions on filling out the form, an attendance slip for the exam day, and an admission card with exam details. The forms request information such as educational qualifications, exam subject and center, and contact details.
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The STi7167 is an integrated system-on-chip that combines a configurable DVB-T or DVB-C demodulator with STB decoding and display functions. It provides advanced HD and SD video decoding, audio decoding, graphics processing, and connectivity options. The chip is targeted at low-cost HD and SD set-top boxes for cable, terrestrial, and hybrid IP/broadcast networks.
Mobile data traffic is growing year to year. Mobile operators are facing a different situation from voice legacy business. The growth of data traffic is not as high as one of revenue. They need to lower cost of Mbps to survive otherwise they will collapse.
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This third part of Linux internals talks about Thread programming and using various synchronization mechanisms like mutex and semaphores. These constructs helps users to write efficient programs in Linux environment
The document discusses process management in Linux, including scheduling, context switching, and real-time systems. It defines process scheduling as determining which ready process moves to the running state, with the goal of keeping the CPU busy and minimizing response times. Context switching is described as storing the state of a process when it stops running so the CPU can restore another process's state when it starts running. CPU scheduling decisions occur when a process changes state, such as from running to waiting. Real-time systems must meet strict deadlines, and the document discusses soft and hard real-time systems as well as differences between general purpose, real-time, and embedded operating systems.
A Project Based Lab Report On AMUZING JOKEDaniel Wachtel
The document describes a project report on checking if letters from two names can be rearranged to form the original names. It begins with contact information for the students and supervisor. It then includes a certificate confirming the project work, acknowledgements, an abstract describing the hashing algorithm used, and an index of sections. It discusses the aims, advantages and disadvantages of the project. It provides a data flow diagram and algorithms for each module. It also describes the software, hardware, implementation, integration and system testing done for the project. The conclusion summarizes that the program checks if letters can be rearranged to form the original names using arrays and by hashing letters based on their ASCII values.
This document describes Divyanshu Kumar's class 12 investigatory project on a bank management system created using C++. The project uses object-oriented programming concepts like classes, objects, inheritance and polymorphism to develop a program to manage bank accounts stored in a binary file. The program allows users to perform operations like creating new accounts, depositing and withdrawing amounts, checking balances and listing all accounts. The source code and outputs of the program are included along with an index and acknowledgements section.
This document provides an overview of object-oriented programming (OOP) including:
- The history and key concepts of OOP like classes, objects, inheritance, polymorphism, and encapsulation.
- Popular OOP languages like C++, Java, and Python.
- Differences between procedural and OOP like top-down design and modularity.
The document provides an introduction to object oriented programming (OOP) compared to procedural programming. It discusses key concepts in OOP like objects, classes, attributes, methods, encapsulation. Objects contain attributes (data) and methods (behaviors). Classes are templates that define common attributes and methods for a set of objects. Encapsulation involves hiding class data and implementation details through access modifiers like private and public. Examples are provided to demonstrate how to define classes and create objects in C++ code.
Information security and programming language s CIJRES Journal
The secure language s C and operating system created by using the language give the full
protection from harmful programs and ciber-attacks. We give more detailed syntax of s C . The syntax inherits
the syntax of C++ but we remove operators that violet security of a computer and we remove all superfluous
operators and functions. In particular, we remove pointers to protect codes of programs from changing by
pointers. We add logic-mathematics language. So it is enough to formulate a mathematical problem by the
language and a computer creates needed program. The compiler of s C provides continuous part of memory to
codes and continuous part of memory to data. The code area is protected from changing by any other code. The
data area has access only to its program and is protected from wrong addressing of any part of the data. The
designer of the system ( s C and its operating system) has a server that provides a variety of services including
unlimited access to Internet. The server provides protection against cyber-attacks such as DDOS by disabling
sources of cyber-attacks up to by disabling non-users of the system since software of users is protected from
harmful programs. The server collects information from all sites on Internet. This information is provided to
users through their operating systems. These systems process information coming from Internet in accordance
with the standards of s C .
This document provides an overview of object-oriented programming (OOP) and C++. It discusses key concepts in OOP like classes, objects, inheritance, polymorphism and encapsulation. It then covers the history and development of OOP languages, with Simula 67 being an early language. C++ is presented as building on C with object-oriented features. The document defines common C++ elements like data types, operators, streams and functions. It provides examples of C++ programs and concepts like structures, call by reference, and function overloading.
Sahil Grover is a final year undergraduate student studying Computer Science and Engineering at IIT Kanpur. He has a strong academic record and has received several awards and honors. His skills include proficiency in languages like C++, JavaScript, Python, and tools like Git. He has experience with projects involving machine learning, compilers, and operating systems. He also has extensive achievements in competitive programming competitions.
vtu data structures lab manual bcs304 pdfLPSChandana
The document contains a preface and index for a lab manual on data structures. It discusses how C programming offers facilities to group data into convenient packages called data structures. The preface emphasizes abstract concepts of data structures and how they are useful for problem solving using structures like queues, arrays, linked lists, stacks, trees and graphs. The index lists 11 programs to be developed related to various data structure operations and applications including strings, stacks, queues, linked lists, polynomials and more.
The document describes an open machine translation service called OpenTranslator that was developed as a master's thesis. OpenTranslator uses the state-of-the-art Transformer neural network model to translate between English and Italian. It provides both a web interface and REST APIs to access the translation model. The goal of OpenTranslator is to offer free and open access to machine translation through these interfaces and by making the training data and user feedback publicly available.
This document discusses designing procedural instructions for user manuals. It focuses specifically on circuit diagrams. There are several challenges with complex machine instructions, including multiple components, subassemblies shown from different angles. The author proposes using pictorial and schematic styles of circuit diagrams to improve understanding. A case study examines how readers comprehend process versus outcome graphics and text-graphic coordination for circuit assembly instructions. The study assessed comprehension of sequences and subassemblies through matching tasks.
Object Oriented Programming For Engineering Students as well as for B.Tech -IT. Covers Almost All From The Basics.
For more:
Google Search:: Prabhaharan Ellaiyan
Computational physics uses numerical analysis and simulations to solve problems in physics that cannot be solved analytically. It bridges theoretical and experimental physics by supplementing both. Computational physics approximates solutions to problems by writing them as finite mathematical operations and using computers to perform those operations and compute approximated solutions. It is important for fields like fluid dynamics, quantum mechanics, particle physics, astrophysics, and geophysics. Common programming languages used include Fortran, C/C++, MATLAB, Mathematica, and Maple.
This document outlines the objectives and topics covered in the course EC8393 - Fundamentals of Data Structures in C. The course aims to teach students about linear and non-linear data structures and their applications using the C programming language. Key topics include implementing various data structure operations in C, choosing appropriate data structures, and modifying existing or designing new data structures for applications. Assessment includes continuous internal assessments, a university exam, and a minimum 80% attendance requirement.
This document contains information about the Object Oriented Programming laboratory course for the Department of Information Technology at Kamaraj College of Engineering and Technology in Madurai, India. It includes the vision and mission statements of the institute and department, program educational objectives, program outcomes, course syllabus, outcomes, and a course plan. The course aims to develop software skills in Java programming, teach concepts like classes, packages, interfaces, exceptions, and help students build applications using files, generics, events, and threads. It is a 2 credit course conducted over 60 periods in the third semester for the 2017 regulation batch of the B.Tech Information Technology program.
Modularity is the degree to which a system's components can be separated and recombined. Modular programming separates a program into independent, interchangeable modules that contain everything needed to execute one aspect of functionality. This allows for less code, easier collaboration, and easier identification and fixing of errors. A queue is a first-in, first-out data structure that can be implemented using a linked list. The advantages of a linked representation over a linear representation for trees include easier insertion and deletion without data movement and flexibility in memory allocation.
This document discusses abstraction in C++. It defines abstraction as representing crucial features without including unnecessary details. There are two types of abstraction in C++ - data abstraction, which hides data information, and control abstraction, which hides implementation information. Abstract classes can be used to provide structure without implementation. The document provides an example program using an abstract class and discusses applications like increased reusability and security from hiding details. Potential downsides of abstraction are discussed, like reduced performance from extra handling of abstraction.
This document discusses abstraction in C++. It defines abstraction as representing crucial features without including unnecessary details. There are two types of abstraction in C++ - data abstraction, which hides data information, and control abstraction, which hides implementation information. Abstract classes provide structure without implementation and allow for dynamic binding. The document presents an example program using an abstraction class and discusses applications like increased reusability and security. It notes that while abstractions are generally good, they can impact performance by slowing code and increasing code size.
1. The document presents a project to develop a browser plugin that visually represents knowledge articles from sources like Wikipedia as connected graph nodes. This helps users easily understand topics by showing the main keywords and their relationships.
2. The project aims to implement an interactive e-learning tool that displays a graphical view of document content as nodes linked by their semantic relationships.
3. The algorithm extracts keywords from articles and calculates weights based on frequency to determine the most prominent nodes and links to display at different depths of the graph.
IRJET- Natural Language Query ProcessingIRJET Journal
The document discusses the development of a natural language query processing system that allows users to retrieve data from a database using simple English statements rather than SQL queries. It proposes a system that takes an English query as input, analyzes it to extract keywords, uses those keywords to generate an equivalent SQL query, executes the SQL query on the database, and returns the results to the user. The system is meant to make accessing database information easier for non-technical users by allowing them to use natural language instead of SQL.
Simple Blockchain Eco System for medical data managementsvrohith 9
The blockchain is one of the most ingenious inventions. It changed traditional approach to the transactions that are made between computers virtually, Blockchain allows digital format of information to travel across the world without being tampered, was originally made for bitcoin exchanges which were a virtual currency that was circulated by open source developers and certain hosting companies. Since it is secure and incorruptible digital ledger, we made our project to store all the transactions based on custom SHA-256 and Base64 encoding methods, since blockchain is based on the peer-to-peer network the other mediums never know the hashed content. The database updates are shared across the network and so it resists from single point failure, being controlled by certain authority, Overriding of data.
A mini project on designing a DATABASE for Library management system using mySQLsvrohith 9
It keeps track of all the information about the books in the library, their cost, status and total number of books available in the Library. The user will find it easy in this automated system rather than using the manual writing system. The system contains a database where all the information will be stored safely.
~> All the data types and variables,
~> test SQL-QUERIES
~> database is in the above document
A Computers Architecture project on Barrel shifterssvrohith 9
A Barrel Shifter is a logic component that perform shift or rotate operations. Barrel shifters are applicable for digital signal processors and processors, here we designed 16-bit barrel shifter using 2X1 MUXs in Logisim simulation
A Measurements Project on Light Detection sensorsvrohith 9
The main aim of this project is to saving system with LDR this is to save the power. We want to save power automatically instead of doing manual. So it’s easy to cost effectiveness. This saved power can be used in some other cases. So in villages, towns etc. we can design intelligent systems for the usage of light or we can also use this to reduce the electricity bill of our home. This project can also be used for security of the houses, banks, etc.
A Software Engineering Project on Cyber cafe managementsvrohith 9
Cyber Café Management is a complete package developed for management of systems in a cyber café. This project is intended to be used in a Cyber Café. All cyber cafes have some basic needs likeable to control the systems that are being rented to the customers and are charged on timely basis.
The present project presented in:-
1. Use case diagram
2. Sequence diagram
3. Activity diagram
4. Class diagram
This document contains a case study on pollution from pesticides and chemicals on plants. It begins with an introduction that defines pesticides and discusses how while they can protect plants from pests, they also pose risks to humans, animals, and the environment. The case study objectives are to discuss the effects of pesticide pollution on plants and the environment, conclude with advantages and disadvantages, and provide suggestions. It focuses on the impacts of pesticide use and potential alternatives.
This document discusses using MATLAB to solve differential equations related to electric circuits. It begins by explaining some advantages of MATLAB, such as its use of matrices, vectorized operations, and graphical output capabilities. It then provides an example of using MATLAB to solve the first order differential equation iR+Ldi/dt=E(t), which models an LCR circuit. The document also discusses solving second order differential equations manually and with MATLAB code. It provides an example of solving the second order equation d2q/dt2+10dq/dt+250q=0 both manually and using MATLAB code.
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Predictably Improve Your B2B Tech Company's Performance by Leveraging DataKiwi Creative
Harness the power of AI-backed reports, benchmarking and data analysis to predict trends and detect anomalies in your marketing efforts.
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The Modern Marketing Reckoner (MMR) is a comprehensive resource packed with POVs from 60+ industry leaders on how AI is transforming the 4 key pillars of marketing – product, place, price and promotions.
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Discover the potential of real-time streaming in the context of GenAI as we delve into the intricacies of Apache NiFi and its capabilities. Learn how this tool can significantly simplify the data engineering workflow for GenAI applications, allowing you to focus on the creative aspects rather than the technical complexities. I will guide you through practical examples and use cases, showing the impact of automation on prompt building. From data ingestion to transformation and delivery, witness how Apache NiFi streamlines the entire pipeline, ensuring a smooth and hassle-free experience.
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Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
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1. PROJECT BASED LAB REPORT
On
FUNCTIONS OF STRING USING SUFFIX ARRAY
Submitted in partial fulfilment of the
Requirements for the award of the Degree of
Bachelor of Technology
In
Computer Science & Engineering
By
S.V.Rohith
(150031000)
P.Iswarya
(150030684)
K.Sri sai krishna
(150030496)
Under the esteem guidance of
Sir, G.Swain
2. DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING
(DST-FIST Sponsored Department)
K L University
Green Fields, Vaddeswaram, Guntur District-522 502
2015-2016
This is to certify that this project based lab report entitled “String functions using Suffix
array” is a bonafide work done by the team.
S.V.Rohith (150031000)
P.Iswarya (150030684)
K.Sri sai krishna (150030496)
In partial fulfilment of the requirement for the award of degree in BACHELOR OF
TECHNOLOGY in Computer Science and Engineering during the academic year 2015-
2016.
Faculty in charge Head of the Department
CERTIFICATE
3. K L University
DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING
(DST-FIST Sponsored Department)
We hereby declare that this project based lab report entitled “String functions using Suffix
arrays” has been prepared by us in partial fulfilment of the requirement for the award of degree
“BACHELOR OF TECHNOLOGY in COMPUTER SCIENCE AND ENGINEERING”
during the academic year 2015-2016.
I also declare that this project based lab report is of our own effort and it has not been
submitted to any other university for the award of any degree.
Date: 18/04/16 S.V.Rohith (150031000)
Place: Vaddeswaram P.Iswarya (150030684)
K.Sri sai Krishna (150030382)
DECLARATION
4. ACKNOWLEDGEMENTS
My sincere thanks to G.Swain in the Lab for their outstanding support throughout the project
for the successful completion of the work
We express our gratitude to Dr.V.Srikanth, Head of the Department for Computer Science
and Engineering for providing us with adequate facilities, ways and means by which we are
able to complete this term paper work.
We would like to place on record the deep sense of gratitude to the honourable Vice Chancellor,
K L University for providing the necessary facilities to carry the concluded term paper work.
Last but not the least, we thank all Teaching and Non-Teaching Staff of our department and
especially my classmates and my friends for their support in the completion of our term paper
work.
S.V.Rohith (150031000)
P.Iswarya (150030684)
K.Sri sai Krishna (150030382)
5. TABLE OF CONTENTS
Content Pg. No
1. Introduction and Description 1
1.1 Module 1: Longest repeated sub-string 3
1.2 Module 2: Longest common substring 4
1.3 Module 3: Longest palindrome of a string 5
2. Basic requirements and development of the program. 7
3. Longest repeated sub-string 8
3.1. Code of the module
3.2. outputs and reference frames
4. Longest common substring
14
13
4.1. Code of the module
4.2. outputs and reference frames
5. Longest palindrome in a string. 18
4.1. Code of the module
4.2. outputs and reference frames
6. References 20
6.
7. Page | 1
1.INTRODUCTION
Advanced data structures is a part of c-
language. C is a structured, high level machine independent language. C is converted to a lower
language which was understood by the compiler. It allows the software developers to develop
programs without worrying about the hardware plat forms where there will be implemented.
The c language comes from the ALGOL which gives the concept structured programming to
the computer science community. It was introduced early in 1960’s.
After, MARTIN RICHARDS DEVELOPED a language known as BCPL in 1967 for this in
1970’s ken Thompson created a language from BCPL and he called as “B” both BCPL and B
are types less system programming languages. After finding ALGOL BCPL, AND B then from
this c is evolved from that at BELL LABORATORIES in 1972 by “DENIS RITCHE”. C
language uses many concepts from these and added the concept of data type because it was
developed along with a UNIX operating system. UNIX is nothing but a most popular network
operating system is used today and the heart of the internet data super high way. C-language is
robust language because c-supports richest of operators and burden functions this consist of
many operators, operands, key words, special characters, many characters.
Features of c-programming:-
It is a structural programming language with fundamental flow control
construction.
It is highly portable. The program written on one computer can run on another
computer also without any modification or with a slight modification.
It contains 32 keywords.
It is simple and versatile programming language.
It is richest than all programs.
Dynamic memory allocation is possible in ‘c’.
Structures
We have seen that arrays can be used to represent a group of data items that
belongs to same data type. If we want to represent a collectionof data items of different
data types using a single name, then we cannot use an array. C supports a constructed
data type known as Structure, which is a method for packing data of different data types.
A structure is a convenient tool for handling a group of logically related data items.
Structures help to organize complex data in a more meaningful way. It is a powerful
concept that we may often need to Use in our program design.
8. Page | 2
Definition:
A group of data items that belongs to different data types is known as Structure.
‘Struct’ : It is a keyword and is used to declare a Structure.
Declaration of structure:
struct struct_name
{
Data item-1;
Data item-2;
…………
…………
Data item-n;
};
Declaration of structure variable:
struct struct_name identifier;
(or)
struct struct_name dentifier-1,identifier-2,.......,identifier-n;
(Access operator):
It is used to access the data items of a structure with the help of structure variable.
Syntax:
struct_variable. Data item;
This includes all the declaration of data variables.
Includes print statements.
Dynamic memory allocation
9. Page | 3
SUFFIX ARRAY
In computer science, a suffix array is a
sorted array of all suffixes of a string. It is a data structure used, among others, in full text
indices, data compression algorithms and within the field of bioinformatics.
Suffix arrays were introduced by Manber & Myers (1990) as a simple, space efficient
alternative to suffix trees. They have independently been discovered by Gaston Gonnet in 1987
under the name PAT array (Gonnet, Baeza-Yates & Snider 1992).
Task is to Build a Suffix Array and perform the following operations on the obtained Suffix
Array.
Name of the
Module
Function
Number
Functions to be discharged
SUFFIX
ARRAY
#1. Finding the longest repeated substring
#2. Finding the longest common substring
#3. Finding the longest palindrome in a string
The Title of the Program is to develop a program which deals with the combination of
structures, arrays, and other functions. This program could do some operations on arrays such
as insertion, deletion, sorting, searching, update, retrieve, merging, append, and exit.
By implementing this program we can execute the string related operations. To
do this analysis manually it takes a lot of time and patience but by implementing this program
using a high level language like C it becomes much easier. But before going to make final
solution for the problem, the problem must be analysed.
First of all the basic information regarding the program which consists of
complex numbers. This program is solved by using several methods like one can solve this
program using user defined functions concept, loops conditions, go to statements. In this
abstract we used the concept of functions, while loop, for loop, switch case and if condition’s
which helps to execute the problem much easier .The following steps are followed while
implementing the given program using if and while loop.
10. Page | 4
The input is entered i.e., the value of choice (the menu no) select the particular menu.
Next it goes to particular menu and then go to the particular function.
It prints the resultant value which came from the execution.
Longest Repeated Substring
In computer science, the longest repeated
substring problem is the problem of finding the longest substring of a string that occurs at least
twice. This problem can be solved in linear time and space by building a suffix tree for the
string, and finding the deepest internal node in the tree. Depth is measured by the number of
characters traversed from the root. The string spelled by the edges from the root to such a node
is a longest repeated substring. The problem of finding the longest substring with at least k
occurrences can be solved by first pre-processing the tree to count the number of leaf
descendants for each internal node, and then finding the deepest node with at least k leaf
descendants that have no children. In the figure with the string "ATCGATCGA$", the longest
repeated substring is "ATCGA", and repeats twice.
11. Page | 5
Longest Common Substring
In computer science, the longest common substring problem
is to find the longest string (or strings) that is a substring (or are substrings) of two or more
strings. The longest common substring of the strings "ABABC", "BABCA" and "ABCBA" is
string "ABC" of length 3. Other common substrings are "A", "AB", "B", "BA", "BC" and "C".
Longest Palindrome in a String
In computer science, the longest
palindromic substring or longest symmetric factor problem is the problem of finding a
maximum-length contiguous substring of a given string that is also a palindrome. For example,
the longest palindromic substring of "bananas" is "anana". The longest palindromic substring
is not guaranteed to be unique; for example, in the string "abracadabra", there is no palindromic
substring with length greater than three, but there are two palindromic substrings with length
three, namely, "aca" and "ada". In some applications it may be necessary to return all maximal
palindromic substrings (that is, all substrings that are themselves palindromes and cannot be
12. Page | 6
extended to larger palindromic substrings) rather than returning only one substring or returning
the maximum length of a palindromic substring.
Manacher (1975) found a linear time algorithm for listing all the palindromes that appear at the
start of a given string. However, as observed e.g., by Apostolico, Breslauer & Galil (1995), the
same algorithm can also be used to find all maximal palindromic substrings anywhere within
the input string, again in linear time. Therefore, it provides a linear time solution to the longest
palindromic substring problem. Alternative linear time solutions were provided by Jeuring
(1994), and by Gusfield (1997), who described a solution based on suffix trees. Efficient
parallel algorithms are also known for the problem.
13. Page | 7
2.Requirements and Development
SOFTWARE REQUIREMENTS:
• This application is developed in Microsoft windows Xp or later operating system.
• This Phonebook application is coded and made using the following compilers:
1. Code::blocks.
2. Turbo c.
3. Dos Box
HARDWARE REQUIREMENTS:
• The Application size is 38Kb and the size of the code is 5Kb required by the hard disk.
• RAM: minimum 256MB.
• Some basic components like mouse, keyboard, Display monitor…
14. Page | 8
3.Longest repeated sub-string
Algorithm:
1. Start the basic: including the header files
2. Declaring required number of structure variable and pointer variable.
3. *start,*end interval specifies the edge, by which the node is connected to its
parent node. Each edge will connect two nodes, one parent and one child, and
(start, end) interval of a given edge will be stored in the child node
4. leaf nodes, it stores the index of suffix for the path from root to leaf.
5. Take an input variable string and pointer to root node.
6. activeEdge is represented as input string character index.
7. For root node, suffixLink will be set to NULL For internal nodes, suffixLink
will be set to root by default in current extension and may change in next
extension
8. suffixIndex will be set to -1 by default and actual suffix index will be set later
for eaves at the end of all phases
9. activePoint change for walk down (APCFWD) using Skip/Count Trick (Trick
1). If activeLength is greater than current edge length, set next internal node as
activeNode and adjust activeEdge and activeLength accordingly to represent
same activePoint.
10.Now the module going to perform the required operation of finding the longest
repeated string is performed.
11.Displaying the appropriate output
12.Exit the program.
CODING AND EXECUTION
#include<stdio.h>
#include<string.h>
#include<stdlib.h>
#define MAX_CHAR 256
structSuffixTreeNode {
structSuffixTreeNode *children[MAX_CHAR];
18. Page | 12
}
int main(intargc,char *argv[])
{
strcpy(text,"ABCDEFG$");
buildSuffixTree();
getLongestRepeatedSubstring();
freeSuffixTreeByPostOrder(root);
strcpy(text,"ATCGATCGA$");
buildSuffixTree();
getLongestRepeatedSubstring();
freeSuffixTreeByPostOrder(root);
strcpy(text,"pqrpqpqabab$");
buildSuffixTree();
getLongestRepeatedSubstring();
freeSuffixTreeByPostOrder(root);
return 0;
}
Since the input is already made in the program the output is executed in the following way:
19. Page | 13
4.Longest common substring
Algorithm:
1. Start the basic: including the header files
2. Declaring required number of structure variable and pointer variable.
3. *start,*end interval specifies the edge, by which the node is connected to its
parent node. Each edge will connect two nodes, one parent and one child, and
(start, end) interval of a given edge will be stored in the child node
4. leaf nodes, it stores the index of suffix for the path from root to leaf.
5. Take an input variable string and pointer to root node.
6. activeEdge is represented as input string character index.
7. For root node, suffixLink will be set to NULL For internal nodes, suffixLink
will be set to root by default in current extension and may change in next
extension
8. suffixIndex will be set to -1 by default and actual suffix index will be set later
for eaves at the end of all phases
9. activePoint change for walk down (APCFWD) using Skip/Count Trick (Trick
1). If activeLength is greater than current edge length, set next internal node as
activeNode and adjust activeEdge and activeLength accordingly to represent
same activePoint.
10.Now the module going to perform the required operation of finding the longest
common string is performed.
11.Displaying the appropriate output
12.Exit the program.
CODING AND EXECUTION
#include<stdio.h>
#include<string.h>
#include<stdlib.h>
#define MAX_CHAR 256
structSuffixTreeNode {
20. Page | 14
structSuffixTreeNode *children[MAX_CHAR];
structSuffixTreeNode *suffixLink;
int start,suffixIndex;
int *end;
};
typedef structSuffixTreeNode Node;
char text[100];
Node *root=NULL;
Node *lastNewNode=NULL;
Node *activeNode=NULL;
int activeEdge=-1,activeLength=0,remainingSuffixCount=0,leafEnd=-1;
int *rootEnd=NULL;
int *splitEnd=NULL;
int size=-1,size1=0;
Node *newNode(int start,int*end) {
Node *node=(Node*)malloc(sizeof(Node));
int i;
for(i=0;i<MAX_CHAR;i++)
node->children[i]=NULL;
node->suffixLink=root;
node->start=start;
node->end=end;
node->suffixIndex=-1;
return node;
}
int edgeLength(Node *n){
if(n==root)
return 0;
return *(n->end)-(n->start)+1;
}
int walkDown(Node *currNode){
if(activeLength>=edgeLength(currNode)){
activeEdge+=edgeLength(currNode);
activeLength-=edgeLength(currNode);
activeNode=currNode;
return 1;
}
return 0;
}
void extendSuffixTree(int pos){
leafEnd=pos;
remainingSuffixCount++;
lastNewNode=NULL;
while(remainingSuffixCount>0){
if(activeLength==0)
activeEdge=pos;
if(activeNode->children[text[activeEdge]]==NULL){
activeNode->children[text[activeEdge]]=newNode(pos,&leafEnd);
if(lastNewNode!=NULL){
lastNewNode->suffixLink=activeNode;
lastNewNode=NULL;
}
}
23. Page | 17
int k,maxHeight=0,substringStartIndex=0;
doTraversal(root,0,&maxHeight,&substringStartIndex);
for(k=0;k<maxHeight;k++)
printf("%c",text[k+substringStartIndex]);
if(k==0)
printf("No common substring");
else
printf(", of length: %d",maxHeight);
printf("n");
}
int main(intargc,char *argv[]){
size1=6;
printf("Longest Common Substringin abcde and fghie is:");
strcpy(text,"abcde#fghie$"); buildSuffixTree();
getLongestCommonSubstring();
freeSuffixTreeByPostOrder(root);
size1=6;
printf("Longest Common Substringin pqrst and uvwxyz is:");
strcpy(text, "pqrst#uvwxyz$"); buildSuffixTree();
getLongestCommonSubstring();
freeSuffixTreeByPostOrder(root);
return 0;
}
Since the input is already made in the program the output is executed in the following way:
24. Page | 18
5.Longest palindrome in a string
Algorithm:
1. Start the basic: including the header files
2. Declaring required number of structure variable and pointer variable.
3. *start,*end interval specifies the edge, by which the node is connected to its
parent node. Each edge will connect two nodes, one parent and one child, and
(start, end) interval of a given edge will be stored in the child node
4. leaf nodes, it stores the index of suffix for the path from root to leaf.
5. Take an input variable string and pointer to root node.
6. activeEdge is represented as input string character index.
7. For root node, suffixLink will be set to NULL For internal nodes, suffixLink
will be set to root by default in current extension and may change in next
extension
8. suffixIndex will be set to -1 by default and actual suffix index will be set later
for eaves at the end of all phases
9. activePoint change for walk down (APCFWD) using Skip/Count Trick (Trick
1). If activeLength is greater than current edge length, set next internal node as
activeNode and adjust activeEdge and activeLength accordingly to represent
same activePoint.
10.Now the module going to perform the required operation of finding the longest
palindrome in a string is performed.
11.Displaying the appropriate output
12.Exit the program.
CODING AND EXECUTION
#include <stdio.h>
#include <string.h>
voidprintSubStr(char*str,intlow,inthigh){
inti;
for(i=low;i<=high;++i)
printf("%c",str[i]);
}
intlongestPalSubstr(char*str){
intmaxLength=1;
intstart=0,len=strlen(str),i,low,high;
for(i=1;i<len;++i){
26. Page | 20
6. REFERENCES
We checked out the most available content that we can find from the internet
and used in our project.
https://en.wikipedia.org/wiki/Suffix_array
https://en.wikipedia.org/wiki/Longest_common_substring_problem
https://en.wikipedia.org/wiki/Longest_palindromic_substring
https://en.wikipedia.org/wiki/Longest_palindromic_substring
http://www.geeksforgeeks.org/suffix-tree-application-1-substring-
check/
http://www.geeksforgeeks.org/suffix-tree-application-6-longest-
palindromic-substring/
http://www.geeksforgeeks.org/suffix-tree-application-3-longest-
repeated-substring/