International Journal of Computer and Information Technology
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An Intelligent Approach to Automatic Query Formation from Plain Text using Artificial Intelligence
Get PDFMan have always been, inherently, curious creatures. They ask questions in order to satiate their insatiable curiosity. For example, kids ask questions to learn more from their teachers, teachers ask questions to assist themselves to evaluate student performance, and we all ask questions in our daily lives. Numerous learning exchanges, ranging from one-on-one tutoring sessions to thorough exams, as well as real-life debates, rely heavily on questions. One notable fact is that, due to their inconsistency in particular contexts, humans are often inept at asking appropriate questions. It has been discovered that most people have difficulty identifying their own knowledge gaps. This becomes our primary motivator for automating question generation in the hopes that the benefits of an automated Question Generation (QG) system will help humans achieve their useful inquiry needs. QG and Information Extraction (IE) have become two major issues for language processing communities, and QG has recently become an important component of learning environments, systems, and information seeking systems, among other applications. The Text-to-Question generation job has piqued the interest of the Natural Language Processing (NLP), Natural Language Generation (NLG), Intelligent Tutoring System (ITS), and Information Retrieval (IR) groups as a possible option for the shared task. A text is submitted to a QG system in the Text-to-Question generation task. Its purpose would be to create a series of questions for which the text has answers (such as a word, a set of words, a single sentence, a text, a set of texts, a stretch of conversational dialogue, an inadequate query, and so on)
ENMSJ : An Efficiency Filtering Technique using Bitmap Vectors for n-way Joins in Wireless Sensor Networks
Get PDFIn wireless sensor networks, join queries execution introduces a high energy consumption. While energy is an important factor for sensors survival, several techniques were developed to reduce it. Sensors energy is affected by the number of transferred messages whereas query is performed. The aim of the proposed techniques was then to decrease the communicated data volume. So, the exchanged data volume is soaring when joins are performed between many data tables. This joins type is called: n-way join query. In this paper, we present an efficiency technique to treat n-way join queries in wireless sensor networks. This technique is named: Enhanced N-way Mediated Semi-Join (ENMSJ). ENMSJ is an improvement of a precedent strategie that we proposed: N-way Mediated Semi-Join (NMSJ). ENMSJ uses bitmap tables to more reduce transferred messages quantity. We compared the two techniques to test their performance. Obtained results are very hopeful.
Pulsar Star Detection: A Comparative Analysis of Classification Algorithms using SMOTE
Get PDFA Pulsar is a highly magnetized rotating compact star whose magnetic poles emit beams of radiation. The application of pulsar stars has a great application in the field of astronomical study. Applications like the existence of gravitational radiation can be indirectly confirmed from the observation of pulsars in a binary neutron star system. Therefore, the identification of pulsars is necessary for the study of gravitational waves and general relativity. Detection of pulsars in the universe can help research in the field of astrophysics. At present, there are millions of pulsar candidates present to be searched. Machine learning techniques can help detect pulsars from such a large number of candidates. The paper discusses nine common classification algorithms for the prediction of pulsar stars and then compares their performances using various classification metrics such as classification accuracy, precision and recall value, ROC score and f-score on both balanced and unbalanced data. SMOTE-technique is used to balance the data for better results. Among the nine algorithms, XGBoosting algorithm achieved the best results. The paper is concluded with prospects of machine learning for pulsar detection in the field of astronomy
A Protection Layer over MapReduce Framework for Big Data Privacy
Get PDFIn many organizations, big data analytics has become a trend in gathering valuable data insights. The framework MapReduce, which is generally used for this purpose, has been accepted by most organizations for its exceptional characteristics. However, because of the availability of significant processing resources, dispersed privacy-sensitive details can be collected quickly, increasing the widespread privacy concerns. This article reviews some of the existing research articles on the MapReduce framework\u27s privacy issues and proposes an additional layer of privacy protection over the adopted framework. The data is split into bits and processed in the clouds, and two other steps are taken. Hadoop splits the file into bits of a smaller scale. The task tracker then allocates these bits to several mappers. First, the data is split up into key-value pairs, and the intermediate data sets are generated. The efficiency of the suggested approach may then be effectively interpreted. Overall, the proposed method provides improved scalability. The following figures compare execution time with relation to file size and the number of partitions. As privacy protection technique is used, the loss of data content can be appropriately handled. It has been demonstrated that MRPL outperforms current methods in terms of CPU optimization, memory usage, and reduced information loss. Research reveals that the suggested strategy creates significant advantages for Big Data by enhancing privacy and protection. MRPL can considerably solve the privacy issues in Big Data
Analysis of Deep-Fake Technology Impacting Digital World Credibility: A Comprehensive Literature Review
Get PDFDeep-Fake Technique is a new scientific method that uses Artificial-Intelligince to make fake videos with an affect of facial expressions and coordinated movement of lips. This technology is frequently employed in a variety of contexts with various goals. Deep-Fake technology is being used to generate an extremely realistic fake video that can be widely distributed to promote false information or fake news about any celebrity or leader that was not created by them. Because of the widespread use of social media, these fraudulent videos can garner billions of views in under an hour and have a significant impact on our culture. Deep-Fakes are a threat to our celebrities, democracy, religious views, and commerce, according to the findings, but they can be managed through rules and regulations, strong company policy, and general internet user awareness and education. We need to devise a process for examining such video and distinguishing between actual and fraudulent footage
A Cloud-based Framework for Quality Assurance and Enhancement as a Service (QAEaaS) for Universities with Blended Learning Approach
Get PDFThe dynamic and multi-dimensional quality assurance process for Saudi higher education institutes under the National Commission for Academic Accreditation and Assessment (NCAAA) demands an integrated framework for management and support of internal quality reviews and evidence-based self -studies in a cost-effective way. Due to cross-institutional involvement, quality assurance compliance with NCAAA standards is even more challenging for institutes offering courses with blended learning paradigm in multiple campuses. This papers proposes a Cloud-based framework to realize Quality Assurance and Enhancement as a Service (QAEaaS) to facilitate the internal quality reviews by providing efficient data management and effective communication for different stakeholders. Architecture of the proposed framework is described with respective features to cope with the identified quality assurance challenges and issues faced by the Saudi higher education institutes
Comparison of A* Algorithm and Greedy Best Search in Searching Fifteen Puzzle Solution
Get PDFArtificial Intelligence is an exciting field to research. Artificial Intelligence itself is a broad subject. The application of artificial intelligence in daily routine is various. One of the usages of artificial intelligence is finding the shortest route on a map. In general, the algorithm which can be used for finding the shortest route is A*. A* is often used in finding the shortest route in a graph or map. Generally speaking, A* is used to make a game, especially for finding the shortest route of an intelligent agent inside it. In this paper, the finding solution of puzzle game using A* and Greedy Best First Search is to be discussed. The puzzle game which is discussed is the Fifteen Puzzle. This research compares the two algorithms used, A* and Greedy Best First Search. This research shows that Greedy Best First Search gives a slightly faster solution than A*
Drone Tracking with Drone using Deep Learning
Get PDFWith the development of technology, studies in fields such as artificial intelligence, computer vision and deep learning are increasing day by day. In line with these developments, object tracking and object detection studies have spread over wide areas. In this article, a study is presented by simulating two different drones, a leader and a follower drone, accompanied by deep learning algorithms. Within the scope of this study, it is aimed to perform a drone tracking with drone in an autonomous way. Two different approaches are developed and tested in the simulator environment within the scope of drone tracking. The first of these approaches is to enable the leader drone to detect the target drone by using object-tracking algorithms. YOLOv5 deep learning algorithm is preferred for object detection. A data set of approximately 2500 images was created for training the YOLOv5 algorithm. The Yolov5 object detection algorithm, which was trained with the created data set, reached a success rate of approximately 93% as a result of the training. As the second approach, the object-tracking algorithm we developed is used. Trainings were carried out in the simulator created in the Matlab environment. The results are presented in detail in the following sections. In this article, some artificial neural networks and some object tracking methods used in the literature are explained
Mutation Based Hybrid Routing Algorithm for Mobile Ad-hoc Networks
Get PDFMobile Adhoc NETworks (MANETs) usually present challenges such as a highly dynamic topology due to node mobility, route rediscovery process, and packet loss. This leads to low throughput, a lot of energy consumption, delay and low packet delivery ratio. In order to ensure that the route is not rediscovered over and over, multipath routing protocols such as Adhoc Multipath Distance Vector (AOMDV) is used in order to utilize the alternate routes. However, nodes that have low residual energy can die and add to the problem of disconnection of network and route rediscovery. This paper proposes a multipath routing algorithm based on AOMDV and genetic mutation. It takes into account residual energy, hop count, congestion and received signal strength for primary route selection. For secondary path selection it uses residual energy, hop count, congestion and received signal strength together with mutation. The simulation results show that the proposed algorithm gives better performance results compared to AOMDV by 11% for residual energy, 45% throughput, 3% packet delivery ratio, and 63% less delay
Review of Semantic Importance and Role of using Ontologies in Web Information Retrieval Techniques
Get PDFThe Web contains an enormous amount of information, which is managed to accumulate, researched, and regularly used by many users. The nature of the Web is multilingual and growing very fast with its diverse nature of data including unstructured or semi-structured data such as Websites, texts, journals, and files. Obtaining critical relevant data from such vast data with its diverse nature has been a monotonous and challenging task. Simple key phrase data gathering systems rely heavily on statistics, resulting in a word incompatibility problem related to a specific word\u27s inescapable semantic and situation variants. As a result, there is an urgent need to arrange such colossal data systematically to find out the relevant information that can be quickly analyzed and fulfill the users\u27 needs in the relevant context. Over the years ontologies are widely used in the semantic Web to contain unorganized information systematic and structured manner. Still, they have also significantly enhanced the efficiency of various information recovery approaches. Ontological information gathering systems recover files focused on the semantic relation of the search request and the searchable information. This paper examines contemporary ontology-based information extraction techniques for texts, interactive media, and multilingual data types. Moreover, the study tried to compare and classify the most significant developments utilized in the search and retrieval techniques and their major disadvantages and benefits