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Social media platforms allow its users to publicly share any kind of content without any restriction. This shared content is available to a very large number of people having access to social media, moreover, it plays a significant role in casting their trust and belief. Due to this, there is an essential necessity to probe the genuineness and authenticity of the publicly shared content. Fake news is one such problem which has recently attracted enormous attention due to its large social, political and economic impacts on an individual and the society. Manual analysis of articles on social media is a cumbersome task and also it does not ensure a high success rate in the detection of fake news. In this article, we proposed a hybrid deep learning architecture to exploit the characteristics of Convolutional Neural Network along with Multilayer Perceptron. To evaluate the architecture, we used LIAR dataset which contains the news text and profile of the news source. After testing the architecture on various models a significant improvement was observed when compared to state of the art models.

Fake News, Deception, Convolutional neural network, Multilayer perceptron

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Mohd Zeeshan Ansari, Mumtaz Ahmed, "A Hybrid Approach for Fake News Detection using Convolution and Multilayer Perceptron," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.1181-1187, 2019.

Predicting software defects is an important issue in the software development and maintenance process, which is related to the overall success of the software. This is because predicting software failures in the previous phase can improve software quality, reliability and efficiency, and reduce software costs. However, developing robust defect prediction models is a challenging task and many techniques have been proposed in the literature. This paper proposes a software defect prediction model based on the new improved hybrid genetic rule mining algorithm (IHGBR). The supervised IHGBR algorithm has been used to predict future software failures based on historical data. The evaluation process shows that the IHGBR algorithm can be used effectively with high accuracy. The collected results show that the IHGBR method has better performance.

Rule mining, Defect, Genetic, software metrics, Prediction

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S. Maheswari, R. Ganesan, K. Chitra, "Improved Hybrid Genetic Based Rule Mining Algorithm for Software Defect Prediction," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.1188-1195, 2019.

Now days antenna designers are paying more attention on microstrip patch antennas, due to its numerous blessings in field of communication, inclusive of high reliability, light weight, ease of fabrication etc. but despite of its extreme benefits, patch antennas additionally experience some drawbacks viz low gain and narrow bandwidth. These drawbacks may be overcome by looking after a few parameters within the layout of antennas. there are various designing factors affecting the radiating traits of antenna together with patch dimensions, feeding techniques, substrate used in production of antenna etc. The paper is targeted on various bandwidth enhancement strategies. The paper accommodates of a short examine in feeding techniques, parasitic patch elements, advent of slots, twin feed, shorting pin, air hole, defective ground and so forth that enhances the bandwidth of antenna.

Technology, Electronics, Optoelectronics, Photonics, Telecommunications, Signals. Circuits, Systems, Applications

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Ritu Goyal, Y K Jain, "A Review on Bandwidth Enhancement in Microstrip Antenna," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.1196-1200, 2019.

The world has revolutionized over the years with the advent of various technologies and life of mankind has taken a significant turnaround in terms of getting the official problems solved in an effective and efficient manner in no time. One of the most powerful technologies that has come up in recent years is cloud computing. This technology has captured a special place in various Information Technology (IT) sectors and business organizations. Among all the aspects of this technology that are in existence, cloud data search optimization has become a key area of focus for the researchers. Various research works were conducted based on several fundamentals such as Gossip Protocol, Genetic Algorithm, Hybrid Algorithm, Multi-Keyword Synonym Query, Particle Swarm Optimization, Honey Bee Optimization, etc. and all these were put into practical purpose with the primary objective of optimizing the search technique in the cloud. In our paper, we have suggested the use of Ant Colony Optimization Algorithm for an effective data search in database and allocating them to the respective clients through shortest possible network path in no time. We have used the concept of pheromone values to conduct this procedure. Our suggested techniques ensure that our algorithm will achieve a higher degree of performance in terms of increased throughput and increased efficiency as compared to the traditional techniques which were carried out earlier.

Database, Client machines, Data Carrier Equipment, Wires, Quadrilateral Obstruction, Pheromone value, Ant Colony Optimization Algorithm

[1] Elham Azhir, Nima Jafari Navimipour, Mehdi Hosseinzadeh, Arash Sharifi, Aso Darwesh, “Deterministic and non-deterministic query optimization techniques in the cloud computing”, Concurrency and Computation Practice and Experience, 5th March 2019, DOI: 10.1002/cpe.5240.
[2] YoungJu Moon, HeonChang Yu, Joon Min Gil and JongBeom Lim, “A slave ants based ant colony optimization algorithm for task scheduling in cloud computing environments”, Human-centric Computing and Information Sciences, 9th October 2017, DOI: 10.1186/s13673-017-0109-2.
[3] Gurneet Kaur, “Role And Importance Of Search Engine Optimization”, International Journal Of Research-Granthaalayah, Volume 5, Issue 6, June 2017, DOI: 10.5281/zenodo.818213.
[4] Sudipta Sahana, Rajesh Bose, Debabrata Sarddar, “An Enhanced Search Optimization Protocol Based on Gossip Protocol for the Cloud”, International Journal of Applied Engineering Research, Volume 12, Number 19, pp. 8436-8442, ISSN 0973-4562, 2017.
[5] Li Liu, Miao Zhang, Rajkumar Buyya, Qi Fan, “Deadline-constrained coevolutionary genetic algorithm for scientific workflow scheduling in cloud computing”, Concurrency and Computation Practice and Experience, WILEY, 22nd July 2016, DOI: 10.1002/cpe.3942.
[6] Mohammed Abdullahi, Md Asri Ngadi, “Hybrid Symbiotic Organisms Search Optimization Algorithm for Scheduling of Tasks on Cloud Computing Environment”, PLOS One, 27th June 2016, DOI: 10.1371/journal.pone.0158229.
[7] Mohammed Abdullahi, Md Asri Ngadi, Shafi’i Muhammad Abdulhamid, “Symbiotic Organism Search optimization based task scheduling in cloud computing environment”, Future Generation Computer Systems, 24th August 2015, DOI: 10.1016/j.future.2015.08.006.
[8] Manish M. Pardeshi, R. L. Paikrao, “Enhanced and Efficient Search Multimedia Data by Using Multi-Keyword Synonym Query”, International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), Volume 4, Issue 6, June 2015.
[9] George Suciu, Ana Maria Sticlan, Cristina Butca, Alexandru Vulpe, Alexandru Stancu and Simona Halunga, “Cloud Search Based Applications for Big Data - Challenges and Methodologies for Acceleration”, ARMS-CC 2015, LNCS 9438, Springer International Publishing Switzerland 2015, pp. 177–185, 2015, DOI: 10.1007/978-3-319-28448-4_13.
[10] Qiang Xu, Zhengquan Xu, Tao Wang, “A Data-Placement Strategy Based on Genetic Algorithm in Cloud Computing”, International Journal of Intelligence Science, 2015, 5, 145-157, April 2015, DOI: 10.4236/ijis.2015.53013.
[11] Gunvir Kaur, IEr. Sugandha Sharma, “Research Paper on Optimized Utilization of Resources Using PSO and Improved Particle Swarm Optimization (IPSO) Algorithms in Cloud Computing”, International Journal of Advanced Research in Computer Science & Technology (IJARCST 2014), Vol. 2, Issue 2, Ver. 3, April-June 2014.
[12] Medhat Tawfeek, Ashraf El-Sisi, Arabi Keshk and Fawzy Torkey, “Cloud Task Scheduling Based on Ant Colony Optimization”, The International Arab Journal of Information Technology, Vol. 12, No. 2, 23rd April 2014.
[13] Vimmi Makkar, Sandeep Dalal, “Ranked Keyword Search in Cloud Computing: An Innovative Approach”, International Journal of Computational Engineering Research, Volume 3, Issue 6, June 2013.
[14] Dr S. Saravanakumar, K Ramnath, R Ranjitha and V.G.Gokul, “A New Methodology for Search Engine Optimization without getting Sandboxed”, International Journal of Advanced Research in Computer and Communication Engineering, Volume 1, Issue 7, ISSN: 2278-1021, September 2012.
[15] Lizheng Guo, Shuguang Zhao, Shigen Shen, Changyuan Jiang, “Task Scheduling Optimization in Cloud Computing Based on Heuristic Algorithm”, Journal of Networks, Volume 7, No. 3, March 2012, DOI: 10.4304/jnw.7.3.547-553.

Sudipta Sahana, Tanmoy Mukherjee, Debabrata Sarddar, "A Logical Approach Towards Effective Data Search using Ant Colony Optimization in Cloud Environment," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.1201-1207, 2019.

Abstract— Automatic voice pathology detection and classification systems effectively contribute to the assessment of voice disorders, which helps clinicians to detect the existence of any voice pathologies and the type of pathology from which patients suffer in the early stage. This paper performs detailed study on various methodologies like feature extraction techniques, pattern recognition using machine learning, artificial intelligence, data mining, etc., used by various researches to detect the voice disorder using signal processing and voice recordings. The identification of an algorithm that discriminates between pathological and healthy voices with more accuracy is necessary to realize a valid and precise health system. The key contribution of this study is to investigate the performance of several machine learning techniques useful for voice pathology detection. This work provides detailed survey and comparison of the existing works pros and cons. This study also highlights the drawbacks in the existing methods and outlines the important factors to be considered while performing

voice pathology, voice disorder, signal processing, machine learning, data mining and feature extraction

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P. Kokila, G. M. Nasira, "Perspective Analysis of Voice Disorder Detection using various Approaches," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.1208-1212, 2019.

Blockchain technology is becoming a revolution in the area of the internet. It is considered a driving force behind the next generation of the Internet. It is an unchallengeable and decentralized database that facilitates transparent and auditable management of data over a distributed network. It has the ability to transform industries and services including tax management system. We suggest that the decentralized and programmable nature of the blockchain applications can be used to improve the tax management system to gain greater efficiency in this system. The current indirect tax management system in India is complex and requires to do some activity offline. It also has an overhead of return filing. The blockchain can potentially solve these issues. The use of the blockchain based distributed ledger and smart contracts can reduce the administrative burden for accounting services and there is no need to do anything offline, everything will be done online during the tax payment itself. Using the blockchain, all the transactions are done in real time, therefore no return filing is required. The blockchain technology has the advantage that all the transactions are transparent and tamper-proof reducing any system fraud.

Blockchain, Distributed Network, Real-time, Smart Contract, Hash Function, Goods and Services Tax

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S. Ahmad, A. K. Bharti, "Design of Taxation System Based on Blockchain Technology," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.1213-1219, 2019.

Without image data security, number of problems arises with the security of different image data files, important data and security is required to send and store on cloud with assurance of confidentially, integrity and authenticity of information over the internet, in public or local networks. Image security has become a critical issue, and is playing a vital role in the domain of network communication system and web. So, there is always a need to have a method to guard the confidentiality, integrity and authenticity of images and avoid the unapproved access of image data over insecure communication environment. Various techniques have been investigated and developed to protect data and personal privacy like cryptic algorithms so far. Cryptic algorithms play a vital role in providing the information security against malicious attacks. It is challenging stuff for researchers to find out more efficient and accurate symmetric block cipher cryptic algorithm for image enciphering and deciphering, and to implement cryptic algorithm. There are many research institutes working on block cipher cryptic algorithm for secure data communication web in the form of digital images like; JPEG/JFIF, BMP, PNG TIFF, GIF, Exif, PPM, PNM, HEIF, PGM, PBM, BAT, BPG. In this paper, presents performance analysis of various symmetric algorithms and investigate of more efficient, confidential and secure symmetric block cipher cryptic algorithm for image encryption and decryption, against cryptanalysis attacks using SMCrypter tool.

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[14].Shivlal Mewada, Aarti Shrivastava, Pradeep Sharma, N Purohit and S.S. Gautam, “Performance Analysis of Encryption Algorithm in Cloud Computing,” International Journal of Computer Sciences and Engineering, Vol.3, Issue.3, pp.83-89, 2014.

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Shivlal Mewada, Pradeep Sharma, SS Gautam, "Investigation of Efficient SKC Cryptic Algorithm for Image Encipherment and Decipherment Using SMCrypter," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.1220-1226, 2019.

With IoT bringing a large number of day-by-day objects into the digital fold to make them smarter. It is also evident that the IoT is going to transform into a multi-trillion-dollar industry in the near future. However, the reality is that IoT bandwagon rushing full steam ahead is prone to count-less cyber- attack’s in the extremely hostile environment like the internet. Nowadays, standard PC security solutions won’t solve the challenge of privacy and data security transmitted over the internet. In this Paper, we have applied a Bidirectional Recurrent Neural Network to build a security solution with high durability for IoT network security. DL and ML have shown remarkable result in dealing with multimodal and voluminous hetero-generous data in regard’s to intrusion detection especially with the architectures of Recurrent Neural Network’s. Feature selection mechanism were also implemented to help identify and remove non-essential variables from data that does not affect the accuracy of the prediction model. In this case a Random Forest algorithm was implemented over Principal Component Analysis because of flexibility, and easy in using machine learning algorithms that allow production without hyper-parameter tuning, building of multiple decision tree and merging them together to get a more accurate and stable prediction. In this study a novel algorithm (BRNN) out-performed both Recurrent Neural Network and Gated Recurrent Neural Network because it consider both information from the past and the future with back and forward hidden neuron’s.

IoT, Recurrent Neural Network’s, Bi-Directional RNN, Intrusion Detection, Deep Learning, Machine Learning.

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Susheel Kumar Tiwari, Manmohan Singh, Rahul Sharma, "Bi-Directional Recurrent Neural Network for IDS in the Internet of Things," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.1227-1235, 2019.

In this study the steady hydromagnetic flow of fluid between two porous concentric circular cylinders is consider. The fluid isconsider as viscous, incompressible, conducting. The equation of motion and the constitutive equations form a system of non-linear ODEs that is investigated analytically, and in a few cases the numerical results are compared with a known numerical solution. Numerical computations show the effect of the non-Newtonian quantities on the velocity and on the shear stress as the dimensionless parameters are varied. It is supposed that the rate of suction at the inner cylinder is equal to the rate of injection at the outer.

hydromagnetic flow, porous medium, viscous, incompressible, conducting fluid.

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Anup Kumar Karak, "Analytical Solution of Steady Hydromagnetic Flow Bounded by Two Concentric Circular Cylinders in a Porous Medium," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.1236-1238, 2019.

In Human-Computer Interaction, gesture recognition is a prominent topic. Human-computer interaction (HCI) allows computers to recognize and interpret human gestures as commands. Gesture recognition is important for ease of use to operate computer machines. It has wider range of applications in the area like talking with machine, medical operation, computer game control, control of home appliances, car control driving and communication. In this research work A real-time Hand Gesture Recognition System is proposed with hybrid approach of Convolution Neural Network (CNN) and the Recurrent Neural Network (RNN). Moreover experimentation with pre-trained VGG16 is carried out with LSTM. Here LSTM is used to replace the final three layers of the VGG16 architecture, and a soft-max layer is used to produce the output. The integrated model is recognizing both static and dynamic hand motions. Proposed model has obtained training accuracy as 92.71% and validation accuracy is 87.50%.

Convolution Neural Network (CNN), Human-Computer Interaction (HCI), Recurrent Neural Network (RNN), LSTM (Long Short Term Memory)

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Sunil D. Kale, "Deep Learning-based Hybridized LSTM model for Gesture Recognition," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.1239-1246, 2019.