Volume-06 , Special Issue-10 , Nov - 2018 Go Back

From the perspective of humans and computers, a picture can be interpreted in distinct manner. In the case of humans, a picture will be clearly a few description or scene of a motion or environment and so forth, whilst with respect to computers, it is just a few aggregates of pixels or digital numbers. The system of photo captioning offers with assigning inner facts in the shape of captions with the aid of extracting the applicable functions from an input picture. This venture aims at producing meaningful captions for a given picture. The proposed work is based on deep neural networks. The proposed work has three fundamental units. The first is the picture module that is given as input to the function extractor unit. The next unit is a feature extractor unit based on CNN (Convolutional Neural Network) which extracts the applicable characteristic. The final unit is the language generator. It generates sentences that describe the input image. To assess the quality of the generated textual content, BLEU(Bi-Lingual Evaluation Understudy) rating is used. Suitable captions will help the users to search snapshots with lengthy queries. Such systems may also be beneficial for visually impaired humans in understanding pictures.

BLEU rating, captions, CNN, deep neural network

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[2] J. Donahue et al., "Long-Term Recurrent Convolutional Networks for Visual Recognition and Description," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39, Issue 4, pp. 677-691, April 1 2017.
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[4] Arnab Ghoshal, Pavel Ircing, Sanjeev Khudanpur "Hidden Markov Models for Automatic Annotation and Content-Based Retrieval of Images and Video".
[5] Zajic R. Schwartz, D & Door, B & Schwartz, Richard "Automatic Headline Generation for Newspaper Stories", 2018.
[6] PHILO SUMI , ANU.T.P " A Systematic Approach for News aption Generation", International Journal of Advanced Research in Computer Science & Technology (IJARCST 2014), Vol. 2, Issue 2, Ver. 1 (April -June 2014).
[7] K. Ramnath et al., "AutoCaption: Automatic caption generation for personal photos," IEEE Winter Conference on Applications of Computer Vision, Steamboat Springs, CO, 2014, pp. 1050-1057.

Sailee P. Pawaskar, J. A. Laxminarayana, "Image Caption Generation Using Deep Learning", International Journal of Computer Sciences and Engineering, Vol.06, Issue.10, pp.53-55, 2018.

Increasing population and unhealthy lifestyle in urban and semi-urban areas is giving rise to catastrophic decline in cleanliness of surroundings. Recently there are several government programs and NGOS that are focused in making people aware in keeping their surroundings clean. This paper discusses about a system designed using Internet of Things (IoT) which informs organization as soon as garbage bin is full. Organization may include government body or any private firm that is responsible for garbage collection. Various sensors help detecting when the garbage bin is full and then via telegram it will inform the organizations to act. Gas sensor helps to detect toxic and harmful gases. To detect fire in garbage bin temperature sensor is placed, if the temperature goes beyond the predefined threshold value or presence of harmful gas is detected, alarm will be raised to alert the nearby people and organization will be notified using telegram. This will help to keep the polluted places clean in a smart and effective way. The organization will be notified by the system automatically, when the garbage bin is filled, which reduces time for manual checking.

IoT, sensors, RPI

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[2] Misra, Debajyoti, et al. "An IoT-based waste management system monitored by cloud" Journal of Material Cycles and Waste Management (2018): 1-9.
[3] Anagnostopoulos, Theodoros, et al. "Challenges and opportunities of waste management in IoT-enabled smart cities: a survey" IEEE Transactions on Sustainable Computing 2.3 (2017): 275-289.
[4] Gutierrez, Jose M., et al. "Smart waste collection system based on location intelligence" Procedia Computer Science 61 (2015): 120-127.
[5] Akhtar, Mahmuda, et al. "Backtracking search algorithm in CVRP models for efficient solid waste collection and route optimization" Waste Management 61 (2017): 117-128.
[6] Cristóbal, Jorge, et al. "Prioritizing and optimizing sustainable measures for food waste prevention and management" Waste Management 72 (2018): 3-16.
[7] Kiddee, Peeranart, Ravi Naidu, and Ming H. Wong. "Electronic waste management approaches: An overview" Waste Management 33.5 (2013): 1237-1250.
[8] Sharmin, Sadia, and Sikder Tahsin Al-Amin. "A Cloud-based dynamic waste management system for smart cities" Proceedings of the 7th Annual Symposium on Computing for Development. ACM, 2016.
[9] Zhao, Yiran, et al. "VibeBin: A Vibration-Based Waste Bin Level Detection System" Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1.3 (2017): 122.
[10] Sharmin, Sadia, and Sikder Tahsin Al-Amin. "A Cloud-based dynamic waste management system for smart cities" Proceedings of the 7th Annual Symposium on Computing for Development. ACM, 2016.

Reeja S R, Kumar Abhishek Gaurav, Ladly Patel, Rino Cherian, "Garbage Management Using Internet of Things", International Journal of Computer Sciences and Engineering, Vol.06, Issue.10, pp.56-59, 2018.

Most current machine translation systems for translation from English to regional Indian languages ignore the presence of idioms in the text or return the exact literal meaning of the phrase in another language which loses the essence of the proverb. The main issues that arise include timely detection of the proverbs from a given paragraph and the separate processing required for translations of idioms into other languages. This paper presents a combination of natural language grammar-based approach and context-based approach towards detection of idioms in given English text and further presents a trie-based ontology that can be used to translate proverbs into regional languages. The grammar-based approach involves parsing English sentences and identifying the parts-of-speech tags and determining statistically the probability whether the given sentence is a proverb using certain grammar-based rules applicable for only proverbs. The context-based approach classifies and compares keywords in the proverbs and the keywords present in remaining part of the paragraph. Based on the combination of these two approaches, the proverb can be determined with better accuracy. For quick translation of detected proverbs into regional languages, keyword based priority search can be implemented on previously developed trie-based ontology using parts-of-speech tags.

Machine translation, Proverbs, Idioms, English, Regional Languages, grammar-based approach, classification, context-based approach, trie-based ontology

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Naziya Shaikh, "Grammar And Context Based Approach For Identification And Translation Of Proverbs Using Trie-Based Ontology", International Journal of Computer Sciences and Engineering, Vol.06, Issue.10, pp.60-63, 2018.

The foremost common authentication strategy is to use alphanumeric usernames and passwords. This strategy has been appeared to posses critical disadvantages. Clients prefer to choose passwords which are effectively speculated. At the same time, if the password is difficult to figure, then at that point its obviously difficult to keep in mind. To solve this issue a few analyst have created verification strategy’s that utilizes images as passwords. This paper examines the qualities of the existing graphical passwords methodologies and we try to answer a question “whether a graphical password more secure to a text based password”?

Authentication strategy, graphical passwords, secure passwords

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Norman Dias, Reeja S R, "A quantitative report on the present strategies of Graphical authentication", International Journal of Computer Sciences and Engineering, Vol.06, Issue.10, pp.64-73, 2018.