Volume-8 , Issue-6 , Dec 2020, ISSN 2320-7639 (Online) Go Back

• Open Access   Article

  Random Forest Model for Predicting Grayscale Digits on Images

  Stanley Ziweritin, Uchenna Chikwendu Anyimukwu Ugboaja, Chidiebere Moses Osu

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.8 , Issue.6 , pp.1-7, Dec-2020

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  The random forest is one of the fastest, powerful and easy to use techniques with the ability of performing regression and classification task recorded in the biblical study of machine learning. It grows into forest with some number of decision trees as a hybrid system. The problem of missing data which results from over-fitting can best be handled by random forest. The process places a very big barrier on how well the existing methods and functions. This also affects the success metrics in the process of training, testing and validating classifiers in order to produce a more generalized and accurate results for predicting grayscale digits on images. This model is usually employed in replacing the continuous variables with the median values while computing the correct weighted proximity average of all the missing data values. Our aim is to develop an efficienct random forest model using the classification and regressor classifiers with some high-quality of input data by introducing weighted average and the best in majority vote. This model has been trained and tested using the MNIST dataset with some adjusted hyper-parameter values which defined and improved the general performance of the combined trees in the forest. The simulation was done using python programming language and resulted to 99% and 90% metrics of accuracy in comparison with the random forest classification and regression approach respectively.

  Key-Words / Index Term
  Random forest, grayscale images, RF_classification, RF_regression classification, MNIST dataset

  References
  
  [1]. H. T. Malazi, and M. David, (2018). "Combining Emerging Patterns with Random Forest for Complex Activity Recognition in Smart Homes," Applied Intelligence, Vol. 48, Issue. 2, pp.315-330, 2018.
  [2]. Y. K. Chen, and J. F. Wang, "Segmentation of Single- or Multiple-Touching handwritting Numerial String Using Background and Foreground Analysis," IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 22, Issue. 11, pp.1304-1317, 2000
  [3]. V. Y. Kulkami, and P. K. Sinha, "random Forest Classifiers: A Survey and Future Research Directions," International Journal of Advanced Computing Vol. 36, Issue. 1, pp.1144-1153,2013.
  [4]. L. Breiman, "Random Forest," Machine Learning, Vol. 45, Issue. 1, pp.279-290, 2001.
  [5]. R. Anitha, and S. R. D. Siva, "Development of Computer-aided Approach for Brain Tumor Detection using Random Forest Classifier," International Journal of Imaging Systems and technology, Vol. 28, Issue. 1, pp.48-53,2018.
  [6]. V. Lepetit, P. Fua, (2006). "Keypoint Recognition Using Randomized trees," IEEE Trans. Pattern Anaysis Machine Intelligence Vol. 28, Issue. 9, 1465-1479, 2006.
  [7]. S. Bernard, S. Adam, and L. Heutte, " Using Random Forests for Handwritten Digit Recognition," Proceedings of the 9th IAPR/IEEE International Conference on Document Analysis and Recognition(ICDAR), pp.1043-1047, 2007.
  [8]. N. Arica, and F. T. Yarman-Vural, "Optical Character Recognition for Cursive Handwritting," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 24, Issue. 6, pp.801-113, 2002.
  [9]. L. Kuncheva, "Combining Pattern Recognition: Methods and Algorithms," John Wiley and Sons, pp.60-75, 2004.
  [10]. Y. K. Vrushali, and K. S. Pradeep, "Effective Learning and Classification Using Random Forest Algorithm," International Journal of Engineering and Innovative Technology(IJEIT) Vol. 3, Issue. 11, pp.267-273, 2014.
  [11]. A. Jehad, K. Rehanulla, A. Nasir, and M. Imran, "Random Forest and Decision Trees," International Journal of Computer Science(IJCS), Vol. 9, Issue. 5, pp.273-278, 2012
  [12].H. Mishra, S. K. Pathak, and A. Srivastava, "Handwritten Digits Recognition Using Machine Learning Algorithms", International Research Journal of Engineering and Technology(IRJET), Vol. 07, Issue. 05, pp.8073-8079,2020.
  [13]. V. Garg, "Handwritten Digit Classification Using Machine Learning Models," International Research Journal of Engineering and Technology(IRJET), Vol. 06, Issue. 11, pp.3593-3597, 2019.
  [14]. K. N. H. Al-Behadili, "Classification Algorithms for Determining Handwritten Digit," Iraqi Journal for Electrical and Electronic Engineering(IJEEE), Vol. 12, Issue. 1, pp.96-102, 2016.
  [15]. V. P. Dhaka, and M. K. Sharma, "An Efficient Segmentation Technique for Devanagari Offline-Handwritten Scripts using the Feedforward Neural Network," Neural Computing and Applications, Vol. 26, Issue. 8, pp.1881-1893, 2015.
  [16]. A. Singh, and R. Sathyaraj, "A Comparison Between Classification Algorithms on Different Datasets Methodologies using Rapidminer," International Journal of Advanced Research in Computer and Communication Engineering(IJARCCE), Vol. 5, Issue 5, pp.560-563, 2016.
  [17]. R. R. Rani, P. Manikadan, and R. D. Chitra, "An Empirical Analysis of Classification Trees Algorithm for Protein Datasets," International Journal of Advanced Research in Computer Science(IJARCS), Vol. 6, Issue. 6, pp.34-39, 2015.
  [18]. Y. Chherawala, P. P. Roy, and M. Cheriet, "Feature set Evaluation for Offline Handwriting Recognition systems: Application to the Recurrent Neural Network Model," IEEE transactions on cybernetics, Vol. 46, Issue. 12, pp.2825-2836, 2016.
  [19]. S. Joseph, and J. George, "Feature Extraction and Classification Techniques of MODI Script Character Recognition," Pertanika Journal of Science and Technology(PJST), Vol. 27, Issue. 4, pp.1649 - 1669, 2019
  [20]. R. Anushri, N. Ashitha, and Mamath, "Digit Recohnition," International Advanced Research Journal in Science, Engineering and Technology(IARJSET), Vol. 4, Issue. 8, pp.44-50, 2017.
  [21]. G. Pirlo, and D. Impedovo, "Fuzzy Zoning Based Classification for Handwritten Characters," IEEE Transaction on Pattern Recognition and Machine Intelligence, Vol. 19, Issue. 04, pp.780-785, 2011.
  [22]. S. Vinneet, and P. L. Sunil, “Digits recognition using single layer neural Network with principal component analysis,” Computer Science and Engineering (APWC on CSE), Asia-Pacific World Congress IEEE, pp.4-5, 2014.
  [23]. J. Puzicha, M. Held, J. Ketterer, J. M. Buhmann, and D. W. Fellner, "On Spatial Quantization of Color Images," IEEE Transactions on Image Processing 9, pp.666–682, 2000.
  [24]. T. Horiuchi, "Grayscale Image Segmentation using Color Space," Institute of Electronics, Information and Communication Engineers(IEICE) Trans. Infomation System, Vol. E89-D, Issue. 3, pp.1231-1235, 2006.
  [25]. S. Ziweritin, C. C. Ukegbu, and E. U. Ezeorah, Building Data Mining Classification Model for Pixilated Digit Recognition System," SSRG International Journal of Computer Science and Engineering(IJCSE), Vol. 7, Issue. 10, pp.6-12, 2020.
  [26]. A. Liaw, and M. Wiener, "Classification and Regression by Random Forest," R News, Vol. 2, Issue. 3, pp.18–22, 2002
  [27]. L. Kuncheva, and C. Whitaker, "Measures of Diversity in Classifier Ensembles and their Relationship with the Ensemble Accuracy," Machine learning, Vol. 51. Issue. 2, pp.181–207, 2003.
  [28]. S. Talla, P. Venigalla, A. Shaik, and M. Vuyyuru, "Multiclass Classification Using Random Forest Classifier," International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), Vol. 5, Issue. 02, pp.493- 496, 2019.
  [29]. J. J. Rodriguez, L. I. Kuncheva, and C. J. Alonso, "Rotation forest: A New Classifier Ensemble Method," IEEE Transactions on Pattern Analysis and Machine Intelligence(TPAMI), Vol. 28, Issue. 10, pp.1619 - 1630, 2006.
  [30]. E. Kremic, and A. Subasi, "Performance of Random Forest and SVM in Face Recognition," International Arab Journal of Information Technology(IAJI), Vol. 13, Issue. 2, pp.288-292, 2016.

  Citation
  Stanley Ziweritin, Uchenna Chikwendu Anyimukwu Ugboaja, Chidiebere Moses Osu, "Random Forest Model for Predicting Grayscale Digits on Images," International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.6, pp.1-7, 2020

• Open Access   Article

  On The Standardization Practices of the Information Security Operations in Banking Sector: Evidence from Yemen

  Adel A. Nasser, Nada Kh. A. Al Ansi, Naif A. N. Al Sharabi

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.8 , Issue.6 , pp.8-18, Dec-2020

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  This paper aims to discuss the efficacy of the standardization controls of the information security operations in Yemeni banks by investigating the main requirements for their implementation to carry out their security roles effectively. Also, to determine the standardization practices` main weaknesses in the information security management systems (ISMS) of the banking sector and to provide the necessary improvement recommendations based on the ISO 27002-2013 international security standard. The researchers designed a questionnaire distributed to workers responsible for information security statements in 13 banks regulated by Yemen`s central bank, in Sana`a. The result shows that these practices` actual maturity level is 3.66 out of 5, which means that best practices are not consistently followed. The gap between the maturity level of real application of information security practices and the robust level was found; it equals 1.34, which means that the ISMSs in this sector do not have most of the security requirements necessary for their practical and robust functioning. Two significant points of strength were defined. Three main lacks and weak points were discovered, and the improvement actions and recommendations have been suggested to improve the standardization practices of information security operations in this sector. Additional implementation matrix mapping schemes and ISO-based implementation guidance for each bank have been recommended.

  Key-Words / Index Term
  Information security; Assessment; Banking sector; Yemen; Standardization Practices

  References
  [1] IBM Security, "IBM X-Force Threat Intelligence Index ", 2020.
  [2] SF. Alomgeer, “Cyber Crime In Banking Sector of Bangladesh, ”, diss., East West University, 2019.
  [3] S. Kesharwani, M. P. Sarkar, & S. Oberoi, “Growing Threat of Cyber Crime in Indian Banking Sector.”, CYBERNOMICS, Vol 1, No 4, pp 19-22,2019.
  [4] N. Tariq, “Impact of cyber-attacks on financial Institutions,” Journal of Internet Banking and Commerce, Vol. 23, No 2. pp. 1-11, 2018.
  [5] A. R. Raghavan, & L. Parthiban, “The effect of cybercrime on a Bank’s finances,” International Journal of Current Research & Academic Review, Vol. 2, No 2. pp. 173-178, 2014.
  [6] N. Alber, N., & M. Nabil, “The Impact of Information Security on Banks’ Performance in Egypt,” Available at SSRN 2752070
  [7] Sanskriti Choubey , Astitwa Bhargava , "Significance of ISO/IEC 27001 in the Implementation of Governance, Risk and Compliance," International Journal of Scientific Research in Network Security and Communication, Vol.6, Issue.2, pp 30-33, 2018
  [8] Hailye Tekleselase Woldemichael, "Emerging Cyber Security Threats in Organization," International Journal of Scientific Research in Network Security and Communication, Vol.7, Issue.6, pp 7-10, 2019
  [9] M.A.M Stambul, R. Razali, “An assessment model of information security implementation levels.,” In the Proceedings of the 2011 Electrical Engineering and Informatics (ICEEI), IEEE, pp 1-6,2011
  [10] Nnatubemugo Innocent Ngwum, “ Information Security Maturity Model (ISMM). ,” Diss., The University of Manchester., 2013.
  [11] W. M. Zeiad, “The impact of information security risks on the accounting systems in the Central Bank of Yemen." Master Thesis. The Yemeni Academy for Graduate Studies, Sana`a, Yemen, 2019. [In Arabic]
  [12] M. J. Hammodah, “ Evaluating information security strategies in banking institutions,” Master Thesis. Michigan State University- Dubai Branch, UAE,2017. [In Arabic]
  [13] Nada Ismaeil , "Protecting the security of information systems, a case study in Al-Rafidain Bank," Tikrit Journal of Administrative and Economic Sciences. Vol.7 , Issue 21, pp 72—94, 2011. [In Arabic]
  [14] A. L. Muhsen, “Information Security Management In Palestinian Banking," Master Thesis. An-Najah National University. Nablus. Palestine," 2014
  [15] ?. A. Gürcan, “Assessing Information Security Management Requirements For Finance Sector Using An ISO27001 Based Approach,” Master Thesis. Bahcesehir University. Istanbul. The Republic Of Turkey, 2014
  [16] D. Lang & D. Van der Haar, “Recommendations for Biometric Access Control System Deployment in a Vehicle Context in South Africa. ,” In Information Science and Applications, Springer, Singapore.?, pp. 305-317, 2020
  [17] N. Agrawal, & S. Tapaswi, “A trustworthy agent-based encrypted access control method for mobile cloud computing environment,” Pervasive and Mobile Computing, Vol. 52, pp 13-28.?,2019
  [18] Al-Mayahi, Ibrahim, and P. Mansoor Sa`ad. “ISO 27001 gap analysis-case study,” Proceedings of the 2012 International Conference on Security and Management (SAM). The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp), 2012.?
  [19] A. A Nasser, A. A. Al-Khulaidi, & M. N. Aljober, “ Measuring the information security maturity of enterprises under uncertainty using fuzzy AHP,” Int. J. Inf. Technol. Comput. Sci.(IJITCS), Vol. 10, No 4, pp 10-25, 2018
  [20] M. F. Saleh,, “Information security maturity model ,” International Journal of Computer Science and Security (IJCSS), Vol.5, No 3: 21?,2011
  [21] Team, CMMI Product. "Capability maturity model® integration (CMMI SM), version 1.1." CMMI for Systems Engineering, Software Engineering, Integrated Product and Process Development, and Supplier Sourcing (CMMI-SE/SW/IPPD/SS, V1. 1) , No 2,2002
  [22] G. Karokola, S. Kowalski, & L. Yngström, Towards An Information Security Maturity Model for Secure e-Government Services: A Stakeholders View. In HAISA, pp 58-73, 2011

  Citation
  Adel A. Nasser, Nada Kh. A. Al Ansi, Naif A. N. Al Sharabi, "On The Standardization Practices of the Information Security Operations in Banking Sector: Evidence from Yemen," International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.6, pp.8-18, 2020

• Open Access   Article

  Intelligent Surveillance System Using Deep Learning

  Vishwajit Dandage, Radhika Mahore, Hiemanshu Gautam, Akshay Ghavale

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.8 , Issue.6 , pp.19-21, Dec-2020

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  It`s of intensive importance to develop a way for automatic surveillance video analysis to acknowledge the presence of violence. During this work, to identify violent videos, we recommend a deep neural network. A convolutional neural network is used with a pre-trained inception model for extracting frame level features from a video. The characteristics of the frame level are then collectively employed during a long remembering variant that uses fully connected layers and leaky rectified linear units. Alongside the long remembering, the convolutional neural network is capable of capturing localized spatio-temporal features that alter the analysis of native motion within the video. The performance is more evaluated in terms of accuracy of recognition on standard benchmark datasets. The approach planned outperforms state-of -the-art strategies whereas process the videos in real time.

  Key-Words / Index Term
  CNN; LSTM; RNN; Inception; GoogLeNet; VGG; AlexNet; Data-Set; Deep Learning; TensorFlow

  References
  [1] Ali Khaleghi and Mohammad Shahram Moin, “Improved Anomaly Detection in Surveillance Videos Based on a Deep Learning Method, “978-1-5386-5706-5/18 IEEE 2018.
  [2] Antreas Antoniou Plamen Angelov, “A General-Purpose Intelligent Surveillance System for Mobile Devices using Deep Learning, “International Joint Conference on Neural Networks (IJCNN) 2016.
  [3] Swathikiran Sudhakaran, Oswald Lanz,” Learning to Detect Violent Videos using Convolutional Long Short-Term Memory,” 978-1-5386-2939-0/1720 IEEE 2017 .
  [4] Fath U Min Ullah, Amin Ullah, Khan Muhammad, Ijaz Ul Haq and Sung Wook Baik, “Violence Detection Using Spatiotemporal Features with 3D Convolutional Neural Network, “Sensors, 19, 2472; doi:10.3390/s19112472 2019.
  [5] Prakhar Singh, Vinod Pankajakshan, “A Deep Learning Based Technique for Anomaly Detection in Surveillance Videos, “Twenty Fourth National Conference on Communications 2018.
  [6] S.M. Rojin Ammar Md. Tanvir Rounak Anjum Md. Touhidul Islam,“Using Deep Learning Algorithms to Detect Violent Activities”.
  [7] Lyu, Y., Yang, Y., “Violence detection algorithm based on local spatio-temporal features and optical flow,”. 2015 International Conference on Industrial Informatics-Computing Technology, Intelligent Technology, Industrial Information Integration (ICIICII), pp. 307–311. IEEE, December 2015
  [8] C. Piciarelli, C. Micheloni, and G. L. Foresti, “Trajectory-based anomalous event detection,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 18, no. 11, pp. 1544–1554, Nov 2008.
  [9] V. Mahadevan, W. Li, V. Bhalodia, and N. Vasconcelos, “Anomaly detection in crowded scenes,” in 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 2010, pp. 1975–1981.
  [10] S. Hochreiter and J. Schmidhuber, “Long short-term memory”, Neural computation, vol. 9, no. 8, pp. 1735–1780, 1997.
  [11] P. Bilinski and F.Bremond. “Human violence recognition and detection in surveillance videos”. In AVSS, 2016.
  [12] D. Chen, H. Wactlar, M.-y. Chen, C. Gao, A. Bharucha, and A. Hauptmann. “Recognition of aggressive human behavior using binary local motion descriptors”. In International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), 2008.
  [13] Vishwajit D, A Ghavale, R Mahore, H Gautam, IRJET- “Review of Violence Detection System using Deep Learning” IRJET-V6I12326

  Citation
  Vishwajit Dandage, Radhika Mahore, Hiemanshu Gautam, Akshay Ghavale, "Intelligent Surveillance System Using Deep Learning," International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.6, pp.19-21, 2020

• Open Access   Article

  Hybrid of asymmetric cryptography (RSA) and symmetric cryptography (OTP)

  Khean Ouk, Kimsoung Lim, Sen samnang Ouk

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.8 , Issue.6 , pp.22-27, Dec-2020

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  Cryptography is a science-art that makes communication and messages more secure on the communication media, especially for state security, and business security and personal security. In the industrial revolution 4.0, security is a key to make communication more secure and the integrity and availability of data. The combination of symmetric cryptography and symmetric cryptography, symmetric cryptography and asymmetric cryptography, asymmetric cryptography and asymmetric cryptography is the main subjective to concern on security today. One of those combinations is a hybrid algorithm which is made up of asymmetric cryptography (RSA) and symmetric cryptography (OTP). It will strengthen the secureness of communication and data. This study will propose an Algorithm scheme to increase the security of cryptography. The result of the hybrid Algorithm shows steps to encrypt and decrypt the message: First of all, the sender encrypts the block of a message with the RSA public key and then generates the OTP key to encrypt this block of message again to obtain the double ciphertext from the same plaintext and then send it to the receiver. Finally, the receiver decrypts it with the OTP key and then the RSA private key. Therefore, we can say that the security of this proposed hybrid algorithm is more highly secured and guaranteed because of covering the weakness of the RSA cryptography. In conclusion, Section V describes the hybrid algorithm is highly secured and unbreakable.

  Key-Words / Index Term
  Cryptography, RSA, One Time Pad, Hybrid Algorithm, Symmetric Cryptography, Asymmetric Cryptography, Double cipher text

  References
  [1]. Behrouz A. Forouzan, “Data Communication and Networking”, fifth edition, pp44-46, 2013.
  [2]. James F. Kurose and Keith W. Ross, “Computer Networking: A Top-Down Approach Featuring the Internet”, pp 214-215, 2000.
  [3]. M G Ristiana, R Marwati and S M Gozali, “Hybrid algorithm of RSA and one time pad cryptography”, 2019.
  [4]. Shyam Nandan Kumar, “ Review on Network Security and Cryptography”, International Transaction of Electrical and Computer Engineers System, 2015, Vol. 3, No. 1, 1-11, 2015.
  [5]. Nitin R. Mise, and H. C. Srinivasaiah, “A Mathematical Attack Based Algorithm to Challenge the Security of RSA Cryptosystem”, International Journal of Advancements in Research & Technology, Volume 2, Issue 6, June-2013 202 ISSN 2278-7763.
  [6].Muhammad Iqbal, Muhammad Akbar Syahbana Pane,Andysah Putera Utama Siahaan, “SMS EncryptionUsing One-Time Pad Cipher” , IOSR Journal of Computer Engineering (IOSR-JCE),2016.
  [7].Xiaoying Ye,Chenglian Liu, Donald Gardner3, “Weakness of RSA Cryptosystem Characteristic”, International Conference of Computational Methods in Sciences and Engineering 2018 (ICCMSE 2018).
  [8]. Jon Postel,"Transmission Control Protocol," RFC 793,1981.

  Citation
  Khean Ouk, Kimsoung Lim, Sen samnang Ouk, "Hybrid of asymmetric cryptography (RSA) and symmetric cryptography (OTP)," International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.6, pp.22-27, 2020

• Open Access   Article

  Texture Analysis of Lombok Songket Fabric Image Using Feature Extraction Method

  Bahtiar Imran, Erfan Wahyudi, Muhamad Masjun Efendi, Emi Suryadi

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.8 , Issue.6 , pp.28-32, Dec-2020

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  Songket cloth is a culture that must be preserved, Lombok is one area that has a center for songket craftsmen, songket fabrics in Lombok have various types, motifs and textures according to their respective regions. In this study, texture analysis was carried out to obtain the value between one songket cloth and another. The method used in this research is the feature extraction method of GLCM and Correlation Coefficient. The results of this study were the songket from Sade produced the same results between songket keker - songket pengginang = 0.987, songket keker - songket rarang = 0.96 and songket keker -ongket subhanale = 0.977. Whereas for the songket cloth originating from Pringgasela, the value between songket anteng - songket sempara rarely = -0.817, songket anteng -songket blue line = 0.959 and anteng songket -songket antique = 0.441. The Sukarara songket cloth produces the display value between the Sukarara songket keker - subhanale songket = -0.706, the songket keker voluntary - songket wayang = -0.892. The conclusion is that the proposed method can provide good feature extraction results.

  Key-Words / Index Term
  GLCM; Texture analysis; Correlation coefficient; songket Lombok cloth; Analysis

  References
  [1] I. Amalia, "Ekstraksi Fitur Citra Songket Berdasarkan Tekstur Menggunakan Metode Gray Level Co-occurrence Matrix (GLCM)," J. Infomedia, vol. 3, no. 2, pp. 64–68, 2018, doi: 10.30811/jim.v3i2.715.
  [2] B. Pathak and D. Barooah, "Texture analysis based on the Gray-level co-occurrence Matrix considering possible Orientations," Int. J. Adv. Res. Electr. Electron. Instrum. Eng., vol. 2, no. 9, pp. 4206–4212, 2013.
  [3] P. Mohanaiah, P. Sathyanarayana, and L. Gurukumar, "Image Texture Feature Extraction Using GLCM Approach," Int. J. Sci. Res. Publ., vol. 3, no. 5, pp. 1–5, 2013.
  [4] R. Azhar, D. Tuwohingide, D. Kamudi, Sarimuddin, and N. Suciati, "Batik Image Classification Using SIFT Feature Extraction, Bag of Features and Support Vector Machine," Procedia Comput. Sci., vol. 72, pp. 24–30, 2015, doi: 10.1016/j.procs.2015.12.101.
  [5] Yuhandri, S. Madenda, E. P. Wibowo, and karmila@staff gunadarma ac id Karmilasari, "Object feature extraction of songket image using chain code algorithm," Int. J. Adv. Sci. Eng. Inf. Technol., vol. 7, no. 1, pp. 235–241, 2017, doi: 10.18517/ijaseit.7.1.1479.
  [6] A. E. Minarno, A. Kurniawardhani, and F. Bimantoro, "Image retrieval based on multi structure co-occurrence descriptor," Telkomnika (Telecommunication Comput. Electron. Control., vol. 14, no. 3, pp. 1175–1182, 2016, doi: 10.12928/TELKOMNIKA.v14i3.3292.
  [7] B. Imran and M. M. Efendi, "THE IMPLEMENTATION OF EXTRACTION FEATURE USING GLCM AND BACK-PROPAGATION ARTIFICIAL NEURAL NETWORK TO CLASIFY LOMBOK SONGKET WOVEN CLOTH," J. Techno Nusa Mandiri, vol. 17, no. 2, pp. 131–136, 2020.
  [8] Yuhandri, S. Madenda, E. P. Wibowo, and Karmilasari, "Pattern recognition and classification using backpropagation neural network algorithm for songket motifs image retrieval," Int. J. Adv. Sci. Eng. Inf. Technol., vol. 7, no. 6, pp. 2343–2349, 2017, doi: 10.18517/ijaseit.7.6.2200.
  [9] B. Imran, K. Gunawan, M. Zohri, and L. D. Bakti, "Fingerprint pattern of matching family with GLCM feature," Telkomnika (Telecommunication Comput. Electron. Control., vol. 16, no. 4, 2018, doi: 10.12928/TELKOMNIKA.v16i4.8534.
  [10] Suharjito, B. Imran, and A. S. Girsang, "Family relationship identification by using extract feature of gray level co-zoccurrence matrix (GLCM) based on parents and children fingerprint," Int. J. Electr. Comput. Eng., vol. 7, no. 5, 2017, doi: 10.11591/ijece.v7i5.pp2738-2745.

  Citation
  Bahtiar Imran, Erfan Wahyudi, Muhamad Masjun Efendi, Emi Suryadi, "Texture Analysis of Lombok Songket Fabric Image Using Feature Extraction Method," International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.6, pp.28-32, 2020

• Open Access   Article

  Mobile App security for E-Commerce

  Khean Ouk, Kimsoung Lim, Sen samnang Ouk

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.8 , Issue.6 , pp.33-37, Dec-2020

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  Today is an e-commerce world that most of the population around the world does business with high tech. A long the way to deal with it, many intruders, hackers and unauthorized users are trying to involve that business by playing a role as the owner to cash money from a bank or transferring from one account or credit card or use device to install App on mobile phone while the password or PIN was hacked or belonged to those guys illegally. The hybrid algorithm of RSA and OTP will be implemented, that is the best model to prevent those mistreated action that cause to infect to the system. A PIN and a password will be encrypted with the hybrid algorithm. In the world, there is a unique MAC address used for each NIC. The authentication can be processed unless the receiver obtained its own MAC address in advance (pre-shared key). This key (MAC address) was sent to a cloud server after establishing a connection and then while the receiver log in to the cloud, the MAC address will be sent to that receiver to compare with its own MAC address automatically. All MAC is stored in a Cloud Database data must encrypt with the OTP.

  Key-Words / Index Term
  MAC, SIM card, NIC, OTP, Cloud database, e-commerce, PIN, Authentication, hybrid algorithm

  References
  [1].Karyda, Maria,Mitrou,Lilian “DATA BREACH NOTIFICATION:ISSUES AND CHAL-LENGES FOR SECURITY MANAGEMENT”,10th Mediterranean Conference on Information Systems (MCIS), 2016.
  [2]. Roland Schlöglhofer, Johannes Sametinger, “Secure and Usable Authentication on Mobile Devices”, Proceedings of the 10th International Conference on Advances in Mobile Computing &multimedia,Bali, 2012.
  [3]. Khean Ouk, Kimsoung Lim,Sensamnang Ouk, “Message security and Parity bit recovery”, International Journal of Scientific Research in Computer Science and Engineering,Vol.8, Issue.5, pp.01-05,2020.

  Citation
  Khean Ouk, Kimsoung Lim, Sen samnang Ouk, "Mobile App security for E-Commerce," International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.6, pp.33-37, 2020

• Open Access   Article

  A Smart Android Based Fuel Price Monitoring System

  C. Fiossi, A. C. Ameyaw, D. Banuoku, I. Yemeh

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.8 , Issue.6 , pp.38-42, Dec-2020

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  Fuel products have become essential commodities and the most popular source of energy used by automobiles in Ghana and around the globe. In Ghana, the consumption of fossil fuel energy increased by 33.7% from 1995 to 2014; hence, several fuel and gas stations keep spring up daily across the country, with each selling at a different price. The difference in prices leaves consumers in a search mode, looking for the affordable price among the several stations with a locality. However, the number of these station within the same city makes it a challenge for the consumers to know the fuel prices at the various fuel stations and patronise the same product and buy it at their desired price. Therefore, this study seeks to design and develop an Android-based fuel stations application that will enable customers to view all the available fuel prices of the various fuel stations in the Bono region of Ghana conveniently and reliably. The application is intended to present the prices of daily fuel products available at these fuel stations to help users buy their preferred fuel products at the desired station based on the available prices. The developed application offered a user-friendly Graphical User Interface (GUI), speed and accuracy, time effectiveness and reliability.

  Key-Words / Index Term
  Fuel-price-Ghana; Mobile-based, Android; Graphical User Interface

  References
  [1] A. Ambre, P. Gaikwad, K. Pawar, and V. Patil, “Web and Android Application for Comparison of E-Commerce Products,” Int. J. Adv. Eng. Manag. Sci., vol. 5, Issue. 4, pp. 266–268, 2019.
  [2] I. K. Nti, A. F. Adekoya, M. Opoku, and P. Nimbe, “Synchronising Social Media into Teaching and Learning Settings at Tertiary Education,” Int. J. Soc. Media Interact. Learn. Environ., vol. 6, Issue. 3, p. 1-12, 2020.
  [3] O. Nyarko-Boateng, I. K. Nti, A. F. Adekoya, B. Weyori, Asubam, and S. Appiah, “Conceptual Framework for Efficient 802.11 A/B/G/N Wireless Networks Infrastructure to Improve Campus Internet Connectivity,” Int. J. Eng. Technol. Manag. Res., vol. 7, Issue. 11, pp. 1–8, 2020.
  [4] V. Appiah, I. K. Nti, and O. Nyarko-Boateng, “Investigating Websites and Web Application Vulnerabilities: Webmaster’s Perspective,” Int. J. Appl. Inf. Syst., vol. 12, Issue. 3, pp. 10–15, 2017.
  [5] K. Jung, Y. C. Cho, and S. Lee, “Online shoppers’ response to price comparison sites,” J. Bus. Res., vol. 67, Issue. 10, pp. 2079–2087, 2014.
  [6] Techverto, “Everything about ‘Android’ In a Nutshell!,” 2017. http://www.techverto.com/2017/09/everything-about-android-in-nutshell.html.
  [7] Developer.android.com, “Guide to app architecture.” https://developer.android.com/jetpack/guide.
  [8] M. S. Sayyad, P. Surve, N. Shaikh, M. Gharat, and P. Tambe, “IOT Based Early Flood Detection and Avoidance,” Int. J. Sci. Res. Comput. Sci. Eng., vol. 3, Issue. 12, pp. 50–55, 2020.
  [9] S. Rajbhandari, B. Thareja, V. Deep, and D. Mehrotra, “IoT based smart parking system,” 2018 Int. Conf. Innov. Intell. Informatics, Comput. Technol. 3ICT 2018, vol. 6, Issue. 6, pp. 50–52, 2018.
  [10] V. Tiwari and P. Adkar, “Implementation of IoT in Home Automation using android application,” Int. J. Sci. Res. Comput. Sci. Eng., vol. 7, Issue. 2, pp. 11–16, 2019.
  [11] N. R. Reddy and S. Subhani, “Monitoring Vehicle Speed using GPS and Categorizing Driver,” Int. J. Sci. Res. Comput. Sci. Eng., vol. 7, Issue. 5, pp. 14–21, 2019.
  [12] E. Lingappa, B. Geetavani, and J. Hareesha, “Online Signature Verification using Dynamic Properties,” Int. J. Sci. Res. Comput. Sci. Eng., vol. 5, Issue. 6, pp. 33–38, 2017.
  [13] R. Sulityowati and B. B. K. Rafik, “Prototype Design of a Realtime Monitoring System of a Fuel Tank at a Gas Station Using an Android-Based Mobile Application”, In the Proceedings of the Second International Conference on Electrical Systems, Technology and Information 2015 (ICESTI 2015), Singapore. pp. 685–692, 2016.
  [14] A. Weis, M. Strandskov, K. Yelamarthi, M. S. Aman, and A. Abdelgawad, “Rapid deployment of IoT enabled system for automobile fuel range and gas price location,” In the Proceedings of the 2017 IEEE International Conference on Electro Information Technology (EIT), pp. 452–455, 2017.
  [15] K. Komal D/o Shoukat Ali, B. Arif Ali, V. O. Mihalca, and ?arc? Radu C?t?lin, “Automatic fuel tank monitoring, tracking & theft detection system,” MATEC Web Conf., vol. 184, p. 201-208, 2018.
  [16] J. E. Meseguer, C. K. Toh, C. T. Calafate, J. C. Cano, and P. Manzoni, “Drivingstyles: a mobile platform for driving styles and fuel consumption characterization,” J. Commun. Networks, vol. 19, Issue. 2, pp. 162–168, 2017.
  [17] G. O’Regan, “Concise guide to software engineering,” Springer, pp. 297–305, 2017.
  [18] S. Akyeramfo-Sam and I. K. Nti, “State of Affairs in ICTs Usage within the Hospitality Industry (Guest House & Hotel) Operations: A Case of Brong Ahafo Region Ghana,” Int. J. Sci. Eng. Appl., vol. 6, Issue. 5, pp. 143–149, 2017.
  [19] I. K. Nti, J. A. Ansere, and A. Appiah, “Investigating ATM Frauds In Sunyani Municipality: Customer’s Perspective,” Int. J. Sci. Eng. Appl., vol. 6, Issue. 2, pp. 59–65, 2017.

  Citation
  C. Fiossi, A. C. Ameyaw, D. Banuoku, I. Yemeh, "A Smart Android Based Fuel Price Monitoring System," International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.6, pp.38-42, 2020

• Open Access   Article

  Network Design for WAN Traffic and Cost Generator

  Khean Ouk, Kimsoung Lim, Sen samnang Ouk

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.8 , Issue.6 , pp.43-49, Dec-2020

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  Wide Area Network (WAN) is an interconnected network round the world to share such as voice, data and video. So there are many types of traffic flow in and out of all directions and much type of data is transferring such as email (internal email, external email), Web Access, Database Access, file transfer and Video Conferencing or Online Meeting or Online Learning during the Covid-19. Those types of data can cause more traffic loading during the busy hours or days. As a network designer must optimize the traffic of network flow to avoid the congestion and cost much money. In this research paper focus on the way how to design the best Wide Area Network. To become an expert Network Designer we need a sample problem to study the algorithms and to hone our skills. Real networks carry real traffic and cost real money. If you can’t get the actual tariff and traffic, you will have to fill in the missing information. The generators here can be used to create a simple scenario. Solving such problems is the only way to learn the effective network design.

  Key-Words / Index Term
  Traffic, Traffic generator, Site, population, Traffic Normalization, node

  References
  [1]. Dr.Mark Sinclair, “Network Design for WAN”, Phnom Penh,2003.
  [2].Aaron Kershenbaum,“Telecommunication Network Design Algorithm”, New York , McGraw-Hill,1993.
  [3]. Robert S.chahn ,“Wide Area Network Design”,Morgan Kaufmann; First Printing edition,1998.

  Citation
  Khean Ouk, Kimsoung Lim, Sen samnang Ouk, "Network Design for WAN Traffic and Cost Generator," International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.6, pp.43-49, 2020

• Open Access   Article

  Brain Computer Interface Based Robotic Car Using Raspberry Pi

  Umme Habiba Maginmani, Mujamil Dakhani

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.8 , Issue.6 , pp.50-56, Dec-2020

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  In our society we will see that there are more individual who suffered from various diseases like paralysis in such situation they cannot talk and unfit to move from one place to another and at the same time they are not capable to communicate to other for their daily essential needs , but in such cases they can utilize their eyes for communication and sometimes their use their head to convey their messages. In this paper we shows that how our proposed methods which works under the principle of Brain Computer Interface. Our model gives confidence to those individual for controlling their wheelchair to the spot by just blinking of their eyes. By employing this method these individual need not to be more dependent on their guardian when they need of, and they can drive their wheelchair themselves. As soon as we start running the program, wheelchair begin to moves from their position and command is provided through the blinking of eyes.

  Key-Words / Index Term
  Brain, Brain Computer Interface, Wheelchair, Eye Blink, Raspberry Pi, Bluetooth, Mind-wave mobile, Brain sense

  References
  [1] S. S. Pujari, M. S. Patil, and S. S. Ingleshwar, “Remotely controlled autonomous robot using Android application”, 2017 IEEE International Conference on I-SMAC (IoT in Social, Mobile, Analytics, and Cloud) (I-SMAC), PP. 460-933,10 feb 2017.
  [2] M. R. Mishi, R. Bibi, and T. Ahsan, “Multiple motion control systems of the robotic car based on IoT to produce cloud service,” 2017 IEEE International Conference on Electrical, Computer and Communication Engineering (ECCE), 2017.
  [3] D. Chakraborty, K. Sharma, R. K. Roy, H. Singh, and T. Bezboruah, “Android application based monitoring and controlling of movement of a remotely controlled robotic car mounted with various sensors via Bluetooth,” 2016 IEEE International Conference on Advances in Electrical, Electronic and Systems Engineering (ICAEES), 2016.
  [4] S. J. Lee, J. Lim, G. Tewolde, and J. Kwon, “Autonomous tour guide robot by using ultrasonic range sensors and QR code recognition in an indoor environment,” IEEE International Conference on Electro/Information Technology, 2014.
  [5] E. Amareswar, G. S. S. K. Goud, K. R. Maheshwari, E. Akhil, S. Aashraya, and T. Naveen, “Multipurpose military service robot,” 2017 IEEE International Conference of Electronics, Communication, and Aerospace Technology (ICECA), 2017.
  [6] Premkumar, Keerthi, and K Gerard Joe Nigel. “Smart Phone-Based Robotic Arm Control Using Raspberry Pi, Android, and Wi-Fi.” IEEE International Conference on Innovations in Information, Embedded, and Communication Systems (ICIIECS), doi:10.1109/iciiecs. 2015.7192973, 2015.
  [7] Zain Anwar Ali , M. Tanveer, Habib Shaukat 2 and Saad Anwar , "Android Operated Robotic Arm", Universal Journal of Control and Automation, vol. 2, no. 1, pp. 13, 2014.
  [8] B.O. Omijeh, R. Uhunmwangho and M. Ehikhamenle. “Design Analysis of a Remote Controlled Pick and Place Robotic Vehicle”, International Journal of Engineering Research and Development, volume 10, 2014, pp. 57-68.
  [9] P. Ritika and K. Narender. “Android Mobile Phone Controlled Bluetooth Robot Using Microcontroller” International Journal of Scientific Engineering and Research (IJSER), Volume 2, Issue 7, , pp. 14-17. 2014
  [10] J. Bhuvaneshwari, A. Mohnish,, G. Rohan, B. Chetan. “Voice Controlled Robotic Vehicle”, International Research Journal of Engineering and Technology (IRJET), Volume 04, Issue 06 , pp. 191-193, 2017

  Citation
  Umme Habiba Maginmani, Mujamil Dakhani, "Brain Computer Interface Based Robotic Car Using Raspberry Pi," International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.6, pp.50-56, 2020

• Open Access   Article

  Agricultural Development: Powered by GIS and Remote Sensing-A Contemporary Overview

  P.K. Paul, R.R. Sinha, P. S. Aithal, Anil Bhuimalli, Bashiru Aremu, Pappachan Baby

  Review Paper | Journal-Paper (IJSRCSE)

  Vol.8 , Issue.6 , pp.57-61, Dec-2020

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  Agriculture is an important and vital concern for all of us due to its real need among the human being. The field which is responsible for the agricultural systems better and scientific is Agricultural Science and additionally some of the related and allied fields viz. Agricultural Engineering, Agricultural Management, etc. There are different technologies enhancing traditional agricultural systems and among these important are Biotechnology, Information Technology, Nanotechnology, Genetic Engineering and so on. As far as Information Technology is concerned Geo Information Systems is an important name in advancing Agricultural Systems by its healthy and sophisticated features and functions. Though it is important to note that GIS in agriculture is not a new phenomenon but in recent past various new attributes been added into the. The agricultural sector is considered as mainstream for enhancing economy around the world and it is responsible also in socio-economic privileges and changes. The Technologies are important stakeholders in developing agriculture and vice versa agricultural growth. Geo Information Systems including Remote Sensing play a leading role in developing and modernizing Smart Agricultural Systems and healthy Agricultural Informatics practice. The present paper is on Agricultural Information Systems Designing and Development using GIS and Remote Sensing Based tools. The paper highlighted the basic and emerging applications in this regard.

  Key-Words / Index Term
  Agricultural Informatics, Geo Information Systems, Agricultural Systems, Smart Agriculture, Spatial Technologies, Geo Information Science

  References
  [1] Abbasi, A. Z., Islam, N., & Shaikh, Z. A. (2014). A review of wireless sensors and networks` applications in agriculture. Computer Standards & Interfaces, 36(2), 263-270,
  [2] Adão, T., Hruška, J., Pádua, L., Bessa, J., Peres, E., Morais, R., & Sousa, J. J. (2017). Hyperspectral imaging: A review on UAV-based sensors, data processing and applications for agriculture and forestry. Remote Sensing, 9(11), 1110.
  [3] Al-Adamat (et.al) (2012). The combination of indigenous knowledge and geo-informatics for water harvesting siting in the Jordanian Badia. Journal of Geographic Information System, 4(4), 366-376.
  [4] Altbach, P. G. (1993). The dilemma of change in Indian higher education. Higher Education, 26(1), 3-20.
  [5] Dayal, I. (2002). Developing management education in India. Journal of management Research, 2(2), 98-106.
  [6] Dong, B., Andrews, B., Lam, K. P., Höynck, M., Zhang, R., Chiou, Y. S., & Benitez, D. (2010). An information technology enabled sustainability test-bed (ITEST) for occupancy detection through an environmental sensing network. Energy and Buildings, 42(7), 1038-1046.
  [7] DU, P. J., LI, J., ZHANG, H. R., & CHEN, Y. H. (2007). Discussion on Specialty Education of GIS based on UCGIS Geographic Information Science and Technology Body of Knowledge. Geomatics World, 4.
  [8] Ehlers, M. (2008). Geoinformatics and digital earth initiatives: a German perspective. International journal of digital earth, 1(1), 17-30.
  [9] Kingra, P. K., Majumder, D., & Singh, S. P. (2016). Application of remote sensing and GIS in agriculture and natural resource management under changing climatic conditions. Agric Res J, 53(3), 295-302.
  [10] La Rosa, D., Barbarossa, L., Privitera, R., & Martinico, F. (2014). Agriculture and the city: A method for sustainable planning of new forms of agriculture in urban contexts. Land use policy, 41, 290-303.
  [11] Li, M., & Ye, L. R. (1999). Information technology and firm performance: Linking with environmental, strategic and managerial contexts. Information & Management, 35(1), 43-51.
  [12] Li, T. S., & Li, B. (2007). Research on Data Model and Query Optimization of Electronic Map in Embedded GIS. Aeronautical Computing Technique, (2), 26-35.
  [13] Moqi, J. H. L. (2010). Application of Geographic Information System in Digital Mining Information System [J]. Standardization of Surveying and Mapping, 3.
  [14] Paul, P. K. (2013). MSc-Information Science [Geo Informatics]: Overview emphasizing twoproposed curriculum for sophisticated Geo Spatial development. International Journal of Pharmaceutical and Biological Research (IJPBR), 4(5), 218-227.
  [15] Paul, P. K. and Aithal, P. S. (2020). Environment and Studies related to Environmental Sciences: The Overview of Allied Areas.Educational Quest: An Int. J. of Education and Applied Social Science, 11(1), 01-05.
  [16] Paul, P.K., A. Bhuimali, Aithal, P. S.,Tiwary, K. S., Ripu Ranjan Sinha (2020). Environmental Informatics: Educational Opportunities at Bachelors level—International Context and Indian Potentialities.International Journal of Applied Engineering and Management Letters (IJAEML), 4(1), 243-256.
  [17] Paul, P.K., Aithal, P.S., Bhuimali, A. (2020). Environmental Informatics and Educational Opportunities in Post Graduate level—Indian Potentialities based on International Scenario. IRA-International Journal of Management & Social Sciences, 16(2), 45-58.
  [18] Sandler, S. I. (1996). Infinite dilution activity coefficients in chemical, environmental and biochemical engineering. Fluid Phase Equilibria, 116(1-2), 343-353.
  [19] Singh, A. (2016). Managing the water resources problems of irrigated agriculture through geospatial techniques: An overview. Agricultural Water Management, 174, 2-10.
  [20] Suprem, A., Mahalik, N., & Kim, K. (2013). A review on application of technology systems, standards and interfaces for agriculture and food sector. Computer Standards & Interfaces, 35(4), 355-364.
  [21] Tochtermann, K., & Maurer, H. A. (2000). Knowledge management and environmental informatics. Journal of Universal Computer Science, 6(5), 517-536.
  [22] Thompson, S., Treweek, J. R., &Thurling, D. (1997). The ecological component of environmental impact assessment: a critical review of British environmental statements. Journal of environmental Planning and Management, 40(2), 157-172.
  [23] Yakhou, M., &Dorweiler, V. P. (2004). Environmental accounting: an essential component of business strategy. Business Strategy and the Environment, 13(2), 65-77.
  [24] You-yi, J. I. A. N. G. (2012). Teaching of GIS Course for Surveying and Mapping Engineering Specialty in Universities. Technology and Innovation Management, (5), 28-37.
  [25] WANG, J. X., & GUO, H. L. (2010). The Characteristics and Teaching Methods of High-tech Disciplines of GPS, GIS and RS——Taking the GIS majors of Zhengzhou University as an example [J]. Geomatics World, 6.
  [26] WU, Q., & LI, X. Y. (2015). Remote sensing dynamic monitoring of mining geo-environment based on computational geometry and information TUPU. Journal of China Coal Society, (1), 26-34.

  Citation
  P.K. Paul, R.R. Sinha, P. S. Aithal, Anil Bhuimalli, Bashiru Aremu, Pappachan Baby, "Agricultural Development: Powered by GIS and Remote Sensing-A Contemporary Overview," International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.6, pp.57-61, 2020