AES-Based Encoding and Decoding Images using MATLAB
A Novel Technique of Sign Language Recognition System using Machine Learning for Differently Abled Person
Implementation of Machine Learning Techniques for Depression in Text Messages: A Survey
A Study of Ransomware Attacks on Windows Platform
Techniques of Migration in Live Virtual Machine and its Challenges
Efficient Agent Based Priority Scheduling and LoadBalancing Using Fuzzy Logic in Grid Computing
A Survey of Various Task Scheduling Algorithms In Cloud Computing
A Viable Solution to Prevent SQL Injection Attack Using SQL Injection
A Computational Intelligence Technique for Effective Medical Diagnosis Using Decision Tree Algorithm
Integrated Atlas Based Localisation Features in Lungs Images
R is a great degree adaptable factual programming language and condition that is open source and unreservedly accessible for all standard working frameworks. The aim of this paper is to bring significance of R to the allied fields of Data science and development of R in different innovations like Data Analysis, Image Processing, Big Data Analytics and Machine Learning everything under data science advancements. R studio contributes numerous packages, which are valuable in their respective environment and projects effortlessly. Its short syntax structure to quicken tasks on the data, loading and storing information for both nearby and over web, an extensive rundown of long list of tools for data analysis pulls in clients to work with R. R demonstrates that imperative strategies not accessible somewhere else can be actualized in R effectively.
Cloud computing is the technology of forming a network of remote servers hosted on the Internet to manage process and store data. This technology has its own drawback from the security point of view. This research work aims to address the most recent attack called the man in the cloud attack and the possible solution to overcome it. The attack is tried to be defended at multilevel, so that we can protect our system to the at most level. The first level is to notify the user by detecting the phishing sites, through which the malware is sent into the user's system. At the second level, the user's token id is encrypted, so that the switching of credentials can be avoided.
Now-a-days as the trend is to go online in every field like E-commerce, Banking, security is one of the main concerns. Some of this information additionally incorporates delicate data such as personal information or top secret government documents. So it is very important to protect personal data and information. Only DES or IDEA may be attacked by different sorts of cryptanalysis utilizing parallel procedure. In this paper, the author implements a symmetric key algorithm combining with two symmetric key algorithms, i.e. IDEA and 3DES with some modifications in order to improve the security and make it more complex for the attackers to break this algorithm. Using the combinations of these keys, we get 2^ (56+128) =2^184 that is 3.32 times stronger than conventional DES and 1.44 times stronger than conventional IDEA algorithm. The recommendation of S-IDEA algorithm is that it likewise be actualized in equipment utilizing VLSI innovation.
Wireless Sensor Networks are extensively used for monitoring in difficult terrains since these could be easily deployed due to their small size and their ability to work on their own without additional equipment as they communicate in adhoc manner. Each node consists of an individual power source in the form of a battery and remains active in the network till its energy is exhausted. To extend the network lifetime and optimising the use of restricted power supply, clustering algorithms are widely used to group neighbouring nodes and work in small clusters imitating the behaviour of the actual network. Hybrid Energy Efficient Distributed Clustering (HEED) algorithm was proposed to address the limited power supply and the network lifetime in WSNs. HEED selects cluster heads periodically according to their residual energy and node degree. This paper suggests a few improvements in the original HEED algorithm and a new model has been proposed based on these improvements. The algorithms are analysed with both homogeneous and heterogeneous node batteries and it was found that the proposed model improves the average energy of each node and extends the network lifetime.
This paper shows the improvement in the work carried in Machine Translation as compared to the other techniques used. The work is the enhancement of “Enhancing Bi-Lingual Machine Translation Approach”. It shows the development in a Language Translation using Python, which consist of predefined packages like TextBlob and Google-API. The paper talks about enhancing Bilingual Machine Translation. English language into Indian Languages like Hindi, Marathi, Gujarati, Sindhi, Punjabi, Bengali, Urdu, and Dravidian languages. The work shown in the paper is implemented using a speech_recognition module, where speech input is taken from user so as to translate into any Indian language. After comparison with various techniques and research, the paper shows efficient result up to 94% accuracy.
Human beings communicate through language, be it verbal or be it a sign language that makes use of body motion. Hearing and Speech impaired people, having no way to communicate verbally, make use of Sign Language. They perform gestures using a sign language in order to convey their message and effectively communicate with each other. Since, not everyone knows about Indian Sign Language (ISL), it becomes difficult for normal people to fluently communicate with Hearing and Speech impaired community. This paper proposes ISL gesture recognition system in order to decrease this communication gap. The dataset consists of videos of ISL gestures, which are performed by different Subjects. The proposed system uses OpenPose library, which helps in creating the skeleton of human body and thus it provides keypoints of the whole human body frame by frame. The use of this library removes the dependency on lighting conditions and background. It helps in focusing on just the gesture movements. After extracting the keypoints, Long Short Term Memory (LSTM) is used for classification of gestures. LSTM model classifies which ISL gesture the particular video belongs to.