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Shital Kakad

Bio: Shital Kakad is an academic researcher. The author has contributed to research in topics: The Internet & World Wide Web. The author has an hindex of 1, co-authored 1 publications receiving 9 citations.

Papers
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01 Jan 2012
TL;DR: This paper presents a survey of various approaches which help to minimize query response time mainly for wireless sensor networks.
Abstract: Wireless sensor network is an application specific network. There are various factors which affects reliability in Wireless Sensor Network some of them are energy consumption, high packet loss, congestion, and large response time. There are different parameters, which affects query response time. Whenever Sink (Base Station) needs data, it sends query to source node and node response back to sink. In Wireless Sensor Networks (WSNs) query response time depends on number of parameters like data caching, routing algorithm, node deployment, topology, data availability, query aggregation, query processing, packet loss and congestion. This paper presents a survey of various approaches which help us to minimize query response time mainly for wireless sensor networks.

10 citations

Proceedings ArticleDOI
27 May 2022
TL;DR: This paper has implemented Digital Minimalism (DM) ontology using Protégé 5.5.0 for students to spend time wisely on the Internet.
Abstract: Nowadays students spend most of the time on the Internet for attending lectures, online certification courses and online internships. Living digital life is always joyful and fun act. Internet uses growing rapidly day by day due to online education. The digital algorithms are designed in such a way that students automatically attracts towards it instead of concentrating on study. They spend 4 - 5 hours to attend online lectures and 8 - 10 hours on social media platforms. It is very difficult for students to avoid wasting time on social media. In this paper, we have implemented Digital Minimalism (DM) ontology using Protégé 5.5.0 for students to spend time wisely on the Internet. Basically, Digital technology is developed to improve quality of life. Present time is valuable than money for students. This time can be used for career planning, personal development and learning new things. DM ontology is constructed by analyzing current problems of students. Next, we executed digital minimalism ontology DL query. Further, knowledge graph of DM ontology is graphically displayed using OntoGraph, OntoViz and VOWL.

1 citations

Proceedings ArticleDOI
26 Aug 2022
TL;DR: The amazon and flip kart reviews are taken to construct ontology for unstructured text data and the combined approach of cosine similarity and TF-IDF has been used to find similarity.
Abstract: Ontology construction takes a lot of effort and time. Semantic web extract accurate knowledge from large databases. In this paper, an ontology construction process is proposed for cross domain data. The amazon and flip kart reviews are taken to construct ontology for unstructured text data . The data is pre-processed to clean and remove noise. The combined approach of cosine similarity and TF-IDF has been used to find similarity. Further, K means clustering is applied to identify topics. The hierarchical clustering is implemented to represent ontology. The accuracy, precision and recall are calculated by applying different classifier algorithms like Decision Tree Classifier, Gaussian NB, Random Forest Classifier, Support vector classifier and, K Neighbors Classifier. Support vector classifiers show excellent results comparative to other classifier algorithms. Support vector classifier performance shows accuracy - 0.70%, precision- 0.83% , recall- 0.70% and F1-score - 0.73%.
Proceedings ArticleDOI
24 Jun 2022
TL;DR: The semantic web rule based decision support system ontology is constructed to predict students placement and knowledge graphs of constructed systems have been graphically presented using VOWL, OntoGraf, OntOViz.
Abstract: Recently, ontology has been constructed for information retrieval effectively from huge databases. Ontology shows the relationship of information. It is used to share, reuse and exchange domain knowledge to construct new ontology. Semantic web helps to solve the problem of semantic interoperability. The institution organizes a number of activities for student placement such as workshops, conferences, expert sessions, etc. The semantic web rule based decision support system ontology is constructed to predict students placement. First of all the data is collected from students. Next, the collected data is preprocessed. The J48 algorithm is used to classify the data. Further, the Expectation Maximization (EM) algorithm has been taken to form a cluster of classified data. Decision tree has been constructed using the J48 algorithm. Semantic web rules are constructed from a decision tree. The ontology is constructed in Protégé 5.5.0 and semantic web rules are added. Lastly, knowledge graphs of constructed systems have been graphically presented using VOWL, OntoGraf, OntoViz. This system will be helpful to the institute and students to track progress of placement.
TL;DR: Cross domain (Industry domain and Institute domain) ontology based semantic models are developed to bridge the institute-industry gap using Protégé 5.5.0 editor.
Abstract: The industry and institutes systems are designed to develop a smart world. The heterogeneous data is available on the web. It is difficult to retrieve precise information from the current web. Semantic web is a solution for semantic interoperability. There are different existing ontology in the education domain. Nowadays, the Industry-Institute gap is increasing due to various reasons. These gaps can be bridged after finding gaps by planning and conducting different activities for students. It will automatically reduce the unemployment rate. Industry and Institute both are equally responsible to develop quality students. In this paper, cross domain (Industry domain and Institute domain) ontology based semantic models are developed to bridge the institute-industry gap using Protégé 5.5.0 editor. The classes and sub classes of Industry-Institute ontology are designed with the help of domain experts. Then, object property and data property are defined to enhance ontology. Next, the result of ontology is validated using HermiT reasoner, DL query and SPARQL query. The graphical representation of ontology is shown by using OntoGraf, OWLViz and VOWL plugin.

Cited by
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Journal ArticleDOI
TL;DR: A hybrid algorithm is introduced with the introduction of a hybrid algorithm named Circling Ins-Rider Optimization Algorithm (CI-ROA), which hybrids the concept of Whale OptimizationAlgorithm (WOA) and Rideroptimization Al algorithm (ROA) respectively.
Abstract: Semantic web technology seems to be in the infant stage as only little efforts have been taken on ontology construction with cross-domain application. This paper intends to take an effort on a new workspace, in which the ontology construction model under cross-domain application is performed. The core concern of this work is on two decision-making process namely data filtering and data annotation. Certain process is followed in this work: (i) Preprocessing (ii) Proposed Jaccard Similarity Evaluation (iii) Data filtering and Outlier Detection (iv) Semantic annotation and clustering. More particularly, data filtering is performed based on the evaluated similarity function. The outliers are identified and grouped separately. The data annotation is performed based on the semantics and thereby the clustering process takes place to form the ontology precisely. This clustering process obviously relies to the optimization crisis as the optimal centroid selection becomes the greatest issue. In order to solve this, this paper extends with the introduction of a hybrid algorithm named Circling Insisted-Rider Optimization Algorithm (CI-ROA), which hybrids the concept of Whale Optimization Algorithm (WOA) and Rider Optimization Algorithm (ROA), respectively. Finally, the performance of proposed work is compared and proved over other state-of-the-art models.

10 citations

Proceedings ArticleDOI
05 Mar 2021
TL;DR: In this article, two major e-commerce portals, Amazon and Flipkart's reviews are collected, processed and analyzed using expectation maximization (EM) algorithm and semantic similarity, precision and recall, ontology construction and execution time are calculated using state of art models.
Abstract: Recently, researchers are focusing more attention on cross-domain customer review based ontology construction. It seems very little efforts have been taken to construct cross-domain application ontology. Online reviews help customers to get product information in detail. Bringing the reviews of same product from different e-commerce platform into single platform will enable customers make well informed decision. Customers may purchase online product by comparing reviews as manual comparison of reviews is too difficult. In future very large amount of cross-domain applications would be connected to make smart shopping possible. In this paper, two major e-commerce portals, Amazon and Flipkart’s reviews are collected, processed and analyzed using expectation maximization (EM) algorithm and semantic similarity. Next, precision and recall, ontology construction and execution time are calculated using state of art models.

10 citations

Journal ArticleDOI
TL;DR: In this study, multiple token structure has been implemented for UAVs acting with a dynamic topology and different bit error rate (BER) values are discussed in the case of the package could not be sent.
Abstract: Today, Unmanned Aerial Vehicles (UAVs) are widely used in many different areas of military and civilian applications. Developments in the UAV technology and cheapening of the cost provide opportunity to widespread use of multiple UAVs. Communication is the most important problem in the multi-UAV systems. Flying Ad hoc Network (FANET), is the most significant development method for the solution of communication problem in multi-UAV systems. It is necessary to ensure the realization of coordinated flight of UAVs in FANET. UAVs need to know the position information of each other to also ensure coordination between themselves. Token packet usage is one of the solution to sharing of coordinated information. In this method, the exchange of information between UAVs is performed by circulating a token packet in FANET. The number of UAVs increases, the size of the token containing the location information of all UAVs will also increase. Because of this increase, token will complete its circulation in FANET in a long time. For this reason, after a certain number of UAV, one token will not be sufficient. In multi-UAV systems, UAVs can learn the details of each position with multiple token circulation. In existing studies, it was assumed that UAVs move with constant topology. In addition to this, in these studies there has been assumed that 100% of the packets transmitted. In this study, multiple token structure has been implemented for UAVs acting with a dynamic topology. Also different bit error rate (BER) values are discussed in the case of the package could not be sent. In these cases, the resend packet is provided and these cases effect on the results is observed. Thus, the use of multiple tokens structure in the multi-UAV systems is obtained with more accurate results.

8 citations

Proceedings ArticleDOI
01 Nov 2016
TL;DR: The research contribution presents data reporting using the adaptive dynamic pruning and data aggregation algorithms for query based wireless sensor network called as APDA to prolong the network lifetime and reduce query latency while reducing the communication runtime overheads.
Abstract: The research contribution presents data reporting using the adaptive dynamic pruning and data aggregation algorithms for query based wireless sensor network called as APDA. The aim of APDA is to reduce the network communication overheads through dynamic sub-network pruning to save the energy, minimize the unnecessary extra non relevant data transmissions. We construct tree rooted at base station BS. Mainly, proposed work includes three algorithms: 1) network formation using MST, 2) data aggregation using normalization, and 3) pruning technique with multi-cast communication. Aggregation tree includes dominator nodes (DN) which perform certain operations like data aggregation, multicast communication and pruning the sub network using normalized values in the range of 0 to 1 and at lower layer i.e. Inferior nodes (IN) sense the requested information and reports to its upstream DN nodes. The objective of APDA is to prolong the network lifetime and reduce query latency while reducing the communication runtime overheads. The solutions are well demonstrated through extensive simulations to prove the validity of proposed approaches to minimize the query response time and to get in time delivery of requested data.

4 citations

Journal ArticleDOI
TL;DR: This study developed a common channel multi-token circulation protocol to share location information in multi-UAV systems that communicate using a FANET and ensures that UAVs inmulti- UAV systems know each other's coordinate information with minimum error.
Abstract: Unmanned Aerial Vehicle (UAV) technology is being used increasingly for military and civilian purposes. The primary reason for this increase is that UAVs eliminate the risk to human life in difficult and dangerous missions, are cost effective, and easily are deployed. Developments in UAV technology and decreasing costs have increased UAV usage. However, when multiple UAVs are deployed, inter UAV communication becomes complicated. For this reason, communication in multi-UAV systems is the most important problem that needs to be solved. To enable communication among UAVs without infrastructure support, a Flying Ad Hoc Network (FANET) is used. A FANET provides UAVs to fly in tandem without colliding. To ensure coordinated flight, UAVs require the location information of other UAVs. In this study, we developed a common channel multi-token circulation protocol to share location information in multi-UAV systems that communicate using a FANET. The proposed method ensures that UAVs in multi-UAV systems know each other's coordinate information with minimum error.DOI: 10.5755/j01.eie.25.1.22738

4 citations