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The paper aims at generating automated captions by learning the contents of the image. At present images are annotated with human intervention and it becomes nearly impossible task for huge commercial databases. The image database is given as input to a deep neural network (Convolutional Neural Network (CNN)) encoder for generating “thought vector” which extracts the features and nuances out of our image and RNN (Recurrent Neural Network) decoder is used to translate the features and objects given by our image to obtain sequential, meaningful description of the image .In this paper we are going to explain the survey about image captioning and our proposed system.

image annotation, deep learning, CNN, RNN, LSTM, python3, flask, etc.

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S.S. Pophale, Praveen Mokate, Sandip Najan, Sandesh Gajare, Sanket Swami, "Automatic Image Caption Generation Using CNN, RNN and LSTM," International Journal of Computer Sciences and Engineering, Vol.9, Issue.8, pp.60-62, 2021.

The major concept of the Monetary Based Approach (MBA) network uses the Label Switch Path (LSP) technique that pro- vides high performance in packet delivery without routing table lookup. Nevertheless, it needs more overhead to rebuild a new path when occurring link failure in the MBA network. MBA (Monetary Based Approach) networks are currently evolving towards a universal and convergent network, capable of flowing multiservice traffic (voice, data and video) over the same IP based infrastructure. Quality of Service (QoS) is more and more becoming a necessity for emerging applications carried by MBA networks. This fact stimulates service providers to improve network planning techniques to adequately provide network resources and overcome all failures. The paper presents typical network failures, which cause path recovery in MBA networks and experimental results of network failures, when MBA is used.

Label Switch Path (LSP), Monetary Based Approach (MBA), peer-to-peer system, Quality of Service (QoS)

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Durba Das Gupta, Faiyaz Ahamad, Mohammad Zunnun Khan, "Simulation Based Exploration of SKC Block Cipher AlgorithmAn Exploration of Monetary Based Approach (MBA) in Peer-to-peer system Network: A Review," International Journal of Computer Sciences and Engineering, Vol.9, Issue.8, pp.63-71, 2021.

In the present work we have fabricated a thick film SnO2 sensor on a 1?x1? alumina substrate. It consists of a gas sensitive layer (SnO2) doped with ZnO, a pair of electrodes underneath the gas sensing layer serving as a contact pad for sensor and a heater element on the backside of the substrate was printed. The sensitivity of sensor has been studied and measured at different temperatures (1500C - 3500C) upon exposure to SO2. An approach is made to measure the sensitivity of ZnO-doped SnO2 by using Artificial Neural Network tool. Finally we have shown the results that shows the potential of Artificial Neural Network as a design tool in the area of thick film gas sensor fabrication and development.

Artificial Neural Network, Thick film sensor, sensitivity, ZnO

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Jitendra K. Srivastava, Deepak Kumar Verma, "Development of ZnO-doped SnO2 sensor for Detection of SO2 and Performance Validation through Artificial Neural Network," International Journal of Computer Sciences and Engineering, Vol.9, Issue.8, pp.72-75, 2021.

The development of a mobile Application (Math Tech) is presented, base on the Scrum methodology, which shows an innovative way a set of mathematical formulas and examples of their use for the subjects of mathematics for pre-university courses, linear algebra, differential and integral calculus and operation research of the curricula by Instituto Tecnologico Superior de Comalcalco (ITSC). The App will be a great support in order to improve their abilities in Math. The use of Scrum, given its characteristics, allowed for the programming of the App in a clear, agile and simple way. Additionally, a variety of creative visuals elements have been included that give to the app a higher quality.

Teaching mathematics, mobile App, m-learning, Scrum methodology, educational software

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J. Moreno, M. Sandoval, C. Morales, L. Castillo, "Development of Mobile App for College Math: MathTech," International Journal of Computer Sciences and Engineering, Vol.9, Issue.8, pp.76-80, 2021.

In the past, researchers study candidate filters used to solve the problem for the last years. Pulsar is a type of star, which is interested in the great scientific topic. Through which we discover this celestial pulsar. Here we have used the decision tree under the new machine learning in this research. We use two classification techniques C4.5 Tree and classification and regression tree CART to classify the HTRU2 dataset and we set a model C4.5 Tree and CART from the ensemble of the classification and regression tree. The Model Ensemble C4.5 Tree and CART provides the best performance compared to the individual models of each classifier. Ensemble Model is useful for classifying candidates in pulsar and non-pulsar.

Classification, C4.5, CART, Ensemble Model, HTRU2

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Sanat Kumar Sahu, "Classification of Pulsar Candidates Using an Ensemble Model," International Journal of Computer Sciences and Engineering, Vol.9, Issue.8, pp.81-83, 2021.

Data Mining (DM) and Machine Learning (ML) are used as training algorithm for learning classification and feature selection technique (FST) from data. The DM and ML are contemporary concepts that are used to classify data with remarkable accuracy and efficiency. This paper contains a collection of research publications that utilized DM and ML techniques to diagnose diabetes. The survey`s objective was to determine the study objective, diabetic type, data sets and technologies employed, as well as the results.

Classification, data mining, diabetic disease, feature selection technique, machine learning

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Sanat Kumar Sahu, "Diabetes Risk Detection Review Using Machine Learning Techniques," International Journal of Computer Sciences and Engineering, Vol.9, Issue.8, pp.84-86, 2021.