Volume-7 , Issue-6 , Jun - 2019 Go Back

Today, in the advancement of Information Technology, machine learning has many applications especially in the field of Natural Language Processing. Thus with the help of NLP and algorithms of machine learning, we can automatically generate fill in the blank questions. Thus the task of manually constructing questions is no more a burden. An algorithmic approach has been deduced in this model to generate fill in the blank questions. A paragraph will be provided from which we have to select sentences with relevant content so that these sentences can be considered as options to generate fill in the blanks. The sentences with meaningful information are chosen for question generation. The questions will have relevant blanks which can be filled by one amongst the four choices provided just like multiple choice questions. Each question will have only one choice as the correct answer. The rest of the three choices will be wrong answer known as distractors.

NLP-Natural Language Processing, NER-Named Entity Recognition, POS-Part-of-Speech, RNN-Recurrent Neural Network, NLTK-Natural Language Toolkit, GloVe-Global Vector

[1] Wolfe, J.H.: Automatic question generation from text - an aid to independent study. SIGCUE Outlook 10(SI) (1976)
[2] Kunichika, H., Katayama, T., Hirashima, T., Takeuchi, A.: Automated question generation methods for intelligent English learning systems and its evaluation, Proc. of ICCE01 (2001).
[3] Simon Smith, P.V.S Avinesh and Adam Kilgarriff. 2010.Gap-fill Tests for Language Learners: Corpus-Driven Item Generation .
[4] Naveed Afzal and Viktor Pekar: Unsupervised Relation Extraction for Automatic Generation of Multiple-Choice Questions.
[5] RUSLAN MITKOV, LE AN HA and NIKIFOROS KARAMANIS: A computer-aided environment for generating multiple-choice test items(2005) .
[6] Husam Ali Yllias Chali Sadid A. Hasan: Automatic Question Generation from Sentences(2010)
[7] Takuya Goto, Tomoko Kojiri, Toyohide Watanabe, Tomoharu Iwata, Takeshi Yamada : Automatic Generation System of Multiple-Choice Cloze Questions and its Evaluation

Arpit Agrawal, Pragya Shukla, Aishwarya Panicker, Trisha Dhawe, "Automatic Fill in the Blank Question with Distractor Generation Using NLP," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.892-897, 2019.

The present study viz., A study on the Internet Addiction among college students in Chennai District is an attempt to find out the level of internet addiction and if there is any significant difference in Internet addiction of college students with respect to type of family and Annual income of the Family. Internet Addiction Test (IAT) standardized by Rajhuewar (2009) was used for the study and it was administered to 300 college students studying in four arts and science colleges by applying simple random sampling technique. Mean Standard Deviation and t -tests were calculated to test the hypotheses. The findings of this study revealed that the level of internet addiction of college students is high and there is there is significant difference in Internet addiction of college students with respect to type of family and annual income of the Family. The present paper highlights the major issues related to the Internet addiction among the youngsters. It is an alarm bell for the situation prevailing and gradually increasing trend in India.

Internet Addiction, College students, Type of family, Annual income, Component

[1] Bhattacharya, I., & Sharma, K. (2007). India in the Knowledge Economy – An Electronic Paradigm. International Journal of educational Management, 21(6), 543-568.
[2] Cox, S., & Graham, C. R. (2009). Diagramming TPCK in Practice: Using and elaborated model of the TPCK framework to analyse and depict teacher knowledge. Tech Trends, 53(5), 60-69.
[3] Dash, M. K. (2007). Integration of ICT in teaching Learning: A challenges. Edutract, 6(12), 11-13.
[4] Ertmer, (2005). "Talent Management Software Market Surges Ahead". Forbes. Retrieved 13 April 2015.

K.S. Ramakrishnan, "A Study on the Internet Addiction among College Students in Chennai," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.898-900, 2019.

Now in the recent era of attendance system, attendance system is playing a vital role in schools and colleges. Schools and colleges are trying to improve their attendance system day by day. Most of the students are being absent to colleges without intimating their parents. Their parents are unaware of the absenteeism. Keeping these things in mind and in order to overcome the situation [1], RFID based automated attendance system has come into existence. Earlier days RFID technology with BIO metric based was used where he/she can flash the id card and take biometric without attending classes, during the start and end of the College timings. There is a drawback with this system as the attendance is being marked for the entire without attending the classes, which is not an idle situation. In order to have more robust automated attendance systems and to overcome the present situation, we have come up with a new technique of GPS based technology embedded with RFID and Biometric technology. With the advent of a new technique, we can insert GPS based chip in the student`s id card. If any student flashes his or her id card and takes biometric without attending classes and trying to leave the college campus, based on the new technique, we can identify the existence of the particular person. Initially, we have to store our college location (specific location) in a microcontroller. If he/she is not in the college, the microcontroller will send a message to the parents or respective staff. This work is intended to develop a safe and secure student attendance monitoring and also the student’s location by the use of RFID, Bio Metric and GPS based technology. So based on this method message will be sent to respective student’s parent who is absent and not attending the college and similarly to the respective computer Staff.

RFID, GPS, MICROCONTROLLER, GPRS, BIO-METRICSENSOR

[1].Herdawati ebinti Mohd Kanafiah, Siti Nurul Aqmariahbinti MohdKanafiah ,MohdHelmy bin Abd. Wahab, ZarinaTukiran and Zulidabte Abdul Kadir.,”Online students supervision (088) systems using passive RFID”,2008 International Conference On Electronic Design.1-3 December 2008.
[2].SaikrishnaChatrati, Sumanth Naidu, CH.Raghava Prasad.“RFID based Student Monitoring and Attendance Tracking System.” 4th ICCCNT 2013, July 4-6 2013.
[3].MurizahKassim, HasbullahMazlan, NorlizaZaini, Muhammad KhidhirSalleh.,”Webbased Student Attendance System using RFID Technology” 2012 IEEE Control and System Graduate Research Colloquium (ICSGRC 2012).page 213-218.
[4]. Pao-Ann Hsiung, Shu-Hui Yang.,”Innovative Application of RFID Systems to Special Education Schools”,2010 Fifth IEEE International Conference on Networking, Architecture, and Storage. Page 299-304.
[5].SeemaRao, Prof.K.J.Satoa , “An Attendance Monitoring System Using Biometrics Authentication”, Volume 3, Issue 4, pp. 379-383, April 2013.
[6]. Fahad-Bin-Mazhar, O. Ahamed and M. Rasedujjaman, "Biometric smart attendance kit with fingerprint scanner by using microcontroller," 2015 International Conference on Electrical & Electronic Engineering (ICEEE), Rajshahi, 2015, pp. 13-16.
[7].Anil K. Jain, Arun Ross and SalilPrabhakar, “An introduction to biometric recognition,” Circuits and Systems for Video Technology, IEEE Transactions on Volume 14, Issue 1, pp 4-20, Jan-2004.
[8].Michael, K., Mcnamee, A., Michael, M. G. and Tootell, H., (2006), “Location-Based IntelligenceModeling Behavior in Humans Using GPS”, Proceedings of IEEE.
[9]. Ruchika Gupta and BVR Reddy. “GPS and GPRS Based Cost Effective Human Tracking System Using Mobile Phones” Volume 2, No.1, pp. 39-45, Jun 2011.
[10].G.Talaviya; R.Ramteke; A.K.Shete, “Wireless
Fingerprint Based College Attendance System Using
Zigbee Technology”, International Journal of
Engineering and Advance Technology (IJEAT), ISSBN: 2249-8958, Volume-2, Issue-3, February 2013
[11].M. K. P. Basheer, C. V. Raghu, “Fingerprint attendance
system for classroom needs,” in Proc. India Conference
(INDICON), 2012 AnnualIEEE, pp. 433-438, 7-9 Dec.
2012.
[12]. C. H. Chang, "Smart Classroom Roll Caller System with IOT Architecture," 2011 Second International Conference on Innovations in Bio-inspired Computing and Applications,, 2011, pp. 356-360.
[13]. B. Soewito, F. L. Gaol, E. Simanjuntak and F. E. Gunawan, "Smart mobile attendance system using voice recognition and fingerprint on smartphone," 2016 International Seminar on Intelligent Technology and Its Applications (ISITIA), Lombok, 2016, pp. 175-180
[14]. S. R. Kurkute, Gopal Girase, Prashant Patil, “ Automatic Energy Meter Reading System Using GSM Technology”, International Journal of Innovative Research In Electrical, Electronics, Instrumentation And Control Engineering, ISSN: 2321-2004 (Online) Volume No.-4, Issue No.-3, IF- 4.855

Y.S. Vijaya Lakshmi, V. Jagadeesh Kumar, "Smart Biometric Attendance and Monitoring System," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.901-905, 2019.

This paper is a documentary survey on different areas in which Internet of Things (IoT) can be applied. Many concepts are also discussed on different IoT architectures along with several examples. This paper examines architecture of high level, conceptual levels for the IoT from a computational perspective. The paper also includes discussion about how the communication is established between IoT setup and the application. Different types of protocols to be implemented for the communication is also explained. By deploying these IoT systems the vision of smart city can be achieved. Many of the physical objects of the world are connected with sensors and actuators, which are linked by communication infrastructures and managed by computer algorithms. IoT sensor networks and integrated systems connect intelligent objects. These systems revolutionize the way we deal with our daily lives, medical care, energy and transport. These computational systems are addressed with a variety of different models and structures. In an effort to consolidate the use of these models, this document reviews research in IoT computing.

Component, IOT applications, Energy efficiency, GPS, Biometric Systems, Routing Protocols

[1] S. Tayeb, S. Latifi, and Y. Kim, “A survey on iot communication and computation frameworks: An industrial perspective,” in 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC). IEEE, 2017, pp. 1–6.
[2] Y. Song, H. Ma, and L. Liu, “Content-centric internetworking for resource-constrained devices in the internet of things,” in 2013 IEEE International Conference on Communications (ICC). IEEE, 2013, pp. 1742–1747.
[3] K. Moslehi and R. Kumar, “Autonomous resilient grids in an iot landscape-vision for a nested transactive grid,” IEEE Transactions on Power Systems, 2018.
[4] C. P. Kruger and G. P. Hancke, “Implementing the internet of things vision in industrial wireless sensor networks,” in 2014 12th IEEE International Conference on Industrial Informatics (INDIN). IEEE, 2014, pp. 627–632.
[5] L. Da Xu, W. He, and S. Li, “Internet of things in industries: A survey,” IEEE Transactions on industrial informatics, vol. 10, no. 4, pp. 2233– 2243, 2014.
[6] T. Yilmaz and O. B. Akan, “On the use of the millimeter wave and low terahertz bands for internet of things,” in 2015 IEEE 2nd World Forum on Internet of Things (WF-IoT). IEEE, 2015, pp. 177–180.
[7] U. Albalawi and S. Joshi, “Secure and trusted telemedicine in internet of things iot,” in 2018 IEEE 4th World Forum on Internet of Things (WF-IoT). IEEE, 2018, pp. 30–34.
[8] M. Elhoseny, G. Ram´ırez-Gonzalez, O. M. Abu-Elnasr, S. A. Shawkat,´ N. Arunkumar, and A. Farouk, “Secure medical data transmission model for iot-based healthcare systems,” IEEE Access, vol. 6, pp. 20596– 20608, 2018.
[9] V. Balasubramanian, N. Kouvelas, K. Chandra, R. Prasad, A. G. Voyiatzis, and W. Liu, “A unified architecture for integrating energy harvesting iot devices with the mobile edge cloud,” in 2018 IEEE 4th World Forum on Internet of Things (WF-IoT). IEEE, 2018, pp. 13–18.
[10] R. J. Carbajales, M. Zennaro, E. Pietrosemoli, and F. Freitag, “Energyefficient internet of things monitoring with low-capacity devices,” in 2015 IEEE 2nd World Forum on Internet of Things (WF-IoT). IEEE, 2015, pp. 305–310.
[11] S. K. Datta and C. Bonnet, “Extending datatweet iot architecture for virtual iot devices,” in 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData). IEEE, 2017, pp. 689–694.
[12] B. Dhanalaxmi and G. A. Naidu, “A survey on design and analysis of robust iot architecture,” in 2017 International Conference on Innovative Mechanisms for Industry Applications (ICIMIA). IEEE, 2017, pp. 375– 378.
[13] D. Domingos, F. Martins, R. Martinho, and M. Silva, “Ad-hoc changes in iot-aware business processes,” in 2010 Internet of Things (IOT). IEEE, 2010, pp. 1–7.
[14] A. Kamilaris, F. Gao, F. X. Prenafeta-Boldu, and M. I. Ali, “Agri-´ iot: A semantic framework for internet of things-enabled smart farming applications,” in 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT). IEEE, 2016, pp. 442–447.
[15] M. Kataoka, N. Hosikawa, H. Noguchi, T. Demizu, and Y. Yamato, “Tacit computing and its application for open iot era,” in 2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC). IEEE, 2018, pp. 1–5.
[16] E. Kim, K. Chung, and T. Jeong, “Self-certifying id based trustworthy networking system for iot smart service domain,” in 2017 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2017, pp. 1299–1301.
[17] R. E. Navas, M. Lagos, L. Toutain, and K. Vijayasankar, “Nonce-based authenticated key establishment over oauth 2.0 iot proof-of-possession architecture,” in 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT). IEEE, 2016, pp. 317–322.
[18] S.-R. Oh and Y.-G. Kim, “Development of iot security component for interoperability,” in 2017 13th International Computer Engineering Conference (ICENCO). IEEE, 2017, pp. 41–44.
[19] A. M. Yousuf, E. M. Rochester, and M. Ghaderi, “A low-cost lorawan testbed for iot: Implementation and measurements,” in 2018 IEEE 4th World Forum on Internet of Things (WF-IoT). IEEE, 2018, pp. 361– 366.
[20] H. Kim, D. Lee, J. Cho, and D. Park, “Software execution freeze-safe microcontroller using power profile tracking for iot-driven connected services,” in 2018 IEEE 4th World Forum on Internet of Things (WFIoT). IEEE, 2018, pp. 237–240.
[21] I. Miladinovic and S. Schefer-Wenzl, “Nfv enabled iot architecture for an operating room environment,” in 2018 IEEE 4th World Forum on Internet of Things (WF-IoT). IEEE, 2018, pp. 98–102.
[22] B. Da, P. P. Esnault, S. Hu, and C. Wang, “Identity/identifier-enabled networks (ideas) for internet of things (iot),” in 2018 IEEE 4th World Forum on Internet of Things (WF-IoT). IEEE, 2018, pp. 412–415.
[23] S. Mathew and G. Saranya, “Advanced biometric home security system using digital signature and dna cryptography,” in 2017 International Conference on Innovations in Green Energy and Healthcare Technologies (IGEHT). IEEE, 2017, pp. 1–4.
[24] J. Cao, M. Xu, W. Shi, Z. Yu, A. Salim, and P. Kilgore, “Mypalmvein: A palm vein-based low-cost mobile identification system for wide age range,” in 2015 17th International Conference on E-health Networking, Application & Services (HealthCom). IEEE, 2015, pp. 292–297.
[25] M. A. Ikram, M. D. Alshehri, and F. K. Hussain, “Architecture of an iot-based system for football supervision (iot football),” in 2015 IEEE 2nd World Forum on Internet of Things (WF-IoT). IEEE, 2015, pp. 69–74.
[26] M. Bahadori, M. Kamal, A. Afzali-Kusha, and M. Pedram, “High-speed and energy-efficient carry skip adder operating under a wide range of supply voltage levels,” IEEE Transactions on very large scale integration (VLSI) systems, vol. 24, no. 2, pp. 421–433, 2016.
[27] C. C. Wei, “Dna approach for password conversion generator,” in 2014 International Symposium on Biometrics and Security Technologies (ISBAST). IEEE, 2014, pp. 161–165.
[28] S. Park, N. Crespi, H. Park, and S.-H. Kim, “Iot routing architecture with autonomous systems of things,” in 2014 IEEE World Forum on Internet of Things (WF-IoT). IEEE, 2014, pp. 442–445.
[29] P. L. R. Chze and K. S. Leong, “A secure multi-hop routing for iot communication,” in 2014 IEEE World Forum on Internet of Things (WFIoT). IEEE, 2014, pp. 428–432.
[30] A. R. Biswas and R. Giaffreda, “Iot and cloud convergence: Opportunities and challenges,” in 2014 IEEE World Forum on Internet of Things (WF-IoT). IEEE, 2014, pp. 375–376.
[31] Y. Benazzouz, C. Munilla, O. Gunalp, M. Gallissot, and L. G¨ urgen,¨ “Sharing user iot devices in the cloud,” in 2014 IEEE world forum on internet of things (WF-IoT). IEEE, 2014, pp. 373–374.
[32] D.-H. Park, H.-C. Bang, C. S. Pyo, and S.-J. Kang, “Semantic open iot service platform technology,” in 2014 IEEE World Forum on Internet of Things (WF-IoT). IEEE, 2014, pp. 85–88.
[33] K. Lin, D. Wang, F. Xia, and H. Ge, “Device clustering algorithm based on multimodal data correlation in cognitive internet of things,” IEEE Internet of Things Journal, vol. 5, no. 4, pp. 2263–2271, 2018.
[34] D. Giovanelli, B. Milosevic, D. Brunelli, and E. Farella, “Enhancing bluetooth low energy with wake-up radios for iot applications,” in 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC). IEEE, 2017, pp. 1622–1627.
[35] T. Ramezanifarkhani and P. Teymoori, “Securing the internet of things with recursive internetwork architecture (rina),” in 2018 International Conference on Computing, Networking and Communications (ICNC). IEEE, 2018, pp. 188–194.
[36] W. Li-Hong, T. Hai-Kun, and Y. G. Hua, “Sensors access scheme design based on internet of things gateways,” in 2014 Fifth International Conference on Intelligent Systems Design and Engineering Applications. IEEE, 2014, pp. 901–904.
[37] B. Cheng, D. Zhu, S. Zhao, and J. Chen, “Situation-aware iot service coordination using the event-driven soa paradigm,” IEEE Transactions on Network and Service Management, vol. 13, no. 2, pp. 349–361, 2016.
[38] J. J. Estrada-Lopez, A. Abuellil, A. Costilla-Reyes, and E. S´ anchez-´ Sinencio, “Technology enabling circuits and systems for the internet-ofthings: An overview,” in 2018 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2018, pp. 1–5.
[39] A. M. Ortiz, D. Hussein, S. Park, S. N. Han, and N. Crespi, “The cluster between internet of things and social networks: Review and research challenges,” IEEE Internet of Things Journal, vol. 1, no. 3, pp. 206– 215, 2014.
[40] L. Krupka, L. Vojtech, and M. Neruda, “The issue of lpwan technology coexistence in iot environment,” in 2016 17th International Conference on Mechatronics-Mechatronika (ME). IEEE, 2016, pp. 1–8.
[41] M. M. Hossain, M. Fotouhi, and R. Hasan, “Towards an analysis of security issues, challenges, and open problems in the internet of things,” in 2015 IEEE World Congress on Services. IEEE, 2015, pp. 21–28.
[42] M. Hamzei and N. J. Navimipour, “Toward efficient service composition techniques in the internet of things,” IEEE Internet of Things Journal, vol. 5, no. 5, pp. 3774–3787, 2018.
[43] V. Gazis, M. Goertz, M. Huber, A. Leonardi, K. Mathioudakis, A. Wiesmaier, and F. Zeiger, “Short paper: Iot: Challenges, projects, architectures,” in 2015 18th International Conference on Intelligence in Next Generation Networks. IEEE, 2015, pp. 145–147.
[44] J. Wan, S. Tang, Q. Hua, D. Li, C. Liu, and J. Lloret, “Context-aware cloud robotics for material handling in cognitive industrial internet of things,” IEEE Internet of Things Journal, vol. 5, no. 4, pp. 2272–2281, 2018.
[45] J. Granjal, E. Monteiro, and J. S. Silva, “Security for the internet of things: a survey of existing protocols and open research issues,” IEEE Communications Surveys & Tutorials, vol. 17, no. 3, pp. 1294–1312, 2015.
[46] A. O. Ercan, M. O. Sunay, and I. F. Akyildiz, “Rf energy harvesting and¨ transfer for spectrum sharing cellular iot communications in 5g systems,” IEEE Transactions on Mobile Computing, vol. 17, no. 7, pp. 1680–1694, 2018.
[47] J. Ko, C. Lu, M. B. Srivastava, J. A. Stankovic, A. Terzis, and M. Welsh, “Wireless sensor networks for healthcare,” Proceedings of the IEEE, vol. 98, no. 11, pp. 1947–1960, 2010.
[48] S. Chatterjee and S. Misra, “Qos estimation and selection of csp in oligopoly environment for internet of things,” in 2016 IEEE Wireless Communications and Networking Conference. IEEE, 2016, pp. 1–6.
[49] B. Fekade, T. Maksymyuk, M. Kyryk, and M. Jo, “Probabilistic recovery of incomplete sensed data in iot,” IEEE Internet of Things Journal, vol. 5, no. 4, pp. 2282–2292, 2018.
[50] P.-C. Lin, “Optimal smart gateway deployment for the internet of things in smart home environments,” in 2015 IEEE 4th Global Conference on Consumer Electronics (GCCE). IEEE, 2015, pp. 273–274.
[51] I. Miladinovic and S. Schefer-Wenzl, “A highly scalable iot architecture through network function virtualization,” Open Journal of Internet Of Things (OJIOT), vol. 3, no. 1, pp. 127–135, 2017.
[52] N. Shafiee, S. Tewari, B. Calhoun, and A. Shrivastava, “Infrastructure circuits for lifetime improvement of ultra-low power iot devices,” IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 64, no. 9, pp. 2598–2610, 2017.
[53] R. Huo, F. R. Yu, T. Huang, R. Xie, J. Liu, V. C. Leung, and
Y. Liu, “Software defined networking, caching, and computing for green wireless networks,” IEEE Communications Magazine, vol. 54, no. 11, pp. 185–193, 2016.
[54] M. Chiang and T. Zhang, “Fog and iot: An overview of research opportunities,” IEEE Internet of Things Journal, vol. 3, no. 6, pp. 854– 864, 2016.
[55] R. Ratasuk, B. Vejlgaard, N. Mangalvedhe, and A. Ghosh, “Nb-iot system for m2m communication,” in 2016 IEEE wireless communications and networking conference. IEEE, 2016, pp. 1–5.
[56] D. Dhungana, G. Engelbrecht, J. X. Parreira, A. Schuster, R. Tobler, and D. Valerio, “Data-driven ecosystems in smart cities: A living example from seestadt aspern,” in 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT). IEEE, 2016, pp. 82–87.
[57] S. Foni, T. Pecorella, R. Fantacci, C. Carlini, P. Obino, and M.-G. Di Benedetto, “Evaluation methodologies for the nb-iot system: issues and ongoing efforts,” in 2017 AEIT International Annual Conference. IEEE, 2017, pp. 1–6.
[58] Y. T. Larosa, J.-L. Chen, Y.-W. Ma, and S.-Y. Kuo, “Socio-organism inspired model forming multi-level computational scheme for integrated iot service architecture,” in 2012 2nd Baltic Congress on Future Internet Communications. IEEE, 2012, pp. 68–71.
[59] C. Prasse, A. Nettstraeter, and M. Ten Hompel, “How iot will change the design and operation of logistics systems,” in 2014 International Conference on the Internet of Things (IOT). IEEE, 2014, pp. 55–60.
[60] S. Han, T. Lin, D. Chen, and M. Nixon, “Wirelesscharm: An open system low cost wireless marshalling module for industrial environments,” in 2014 IEEE World Forum on Internet of Things (WF-IoT). IEEE, 2014, pp. 502–505.
[61] B. Cheng, D. Zhu, S. Zhao, and J. Chen, “Situation-aware iot service coordination using the event-driven soa paradigm,” IEEE Transactions on Network and Service Management, vol. 13, no. 2, pp. 349–361, 2016.
[62] W. Mardini, Y. Khamayseh, and M. H. Khatatbeh, “Genetic algorithm for friendship selection in social iot,” in 2017 International Conference on Engineering & MIS (ICEMIS). IEEE, 2017, pp. 1–4.
[63] J. Shah and B. Mishra, “Customized iot enabled wireless sensing and monitoring platform for smart buildings,” Procedia Technology, vol. 23, pp. 256–263, 2016.
[64] D. Mourtzis, E. Vlachou, and N. Milas, “Industrial big data as a result of iot adoption in manufacturing,” Procedia Cirp, vol. 55, pp. 290–295, 2016.
[65] N. Gupta, V. Naik, and S. Sengupta, “A firewall for internet of things,” in 2017 9th International Conference on Communication Systems and Networks (COMSNETS). IEEE, 2017, pp. 411–412.
[66] A. AlEnezi, Z. AlMeraj, and P. Manuel, “Challenges of iot based smart-government development,” in 2018 21st Saudi Computer Society National Computer Conference (NCC). IEEE, 2018, pp. 1–6.
[67] N. Anjum, D. Karamshuk, M. Shikh-Bahaei, and N. Sastry, “Survey on peer-assisted content delivery networks,” Computer Networks, vol. 116, pp. 79–95, 2017.
[68] F. Olivier, G. Carlos, and N. Florent, “New security architecture for iot network,” Procedia Computer Science, vol. 52, pp. 1028–1033, 2015.
[69] F. Alam, R. Mehmood, I. Katib, and A. Albeshri, “Analysis of eight data mining algorithms for smarter internet of things (iot),” Procedia Computer Science, vol. 98, pp. 437–442, 2016.
[70] V. Kumar et al., “Ontology based public healthcare system in internet of things (iot),” Procedia Computer Science, vol. 50, pp. 99–102, 2015.
[71] C. Bekara, “Security issues and challenges for the iot-based smart grid,” Procedia Computer Science, vol. 34, pp. 532–537, 2014.
[72] M. A. Shah, S. Zhang, and C. Maple, “Cognitive radio networks for internet of things: Applications, challenges and future,” in 2013 19th International Conference on Automation and Computing. IEEE, 2013, pp. 1–6.
[73] Y. Jiang, W. Xie, F. Wang, and N. Li, “An implementation of cognitive management framework for the internet of things system,” in Proceedings of 2nd International Conference on Information Technology and Electronic Commerce. IEEE, 2014, pp. 103–106.
[74] S. R. Moosavi, T. N. Gia, A.-M. Rahmani, E. Nigussie, S. Virtanen, J. Isoaho, and H. Tenhunen, “Sea: a secure and efficient authentication and authorization architecture for iot-based healthcare using smart gateways,” Procedia Computer Science, vol. 52, pp. 452–459, 2015.
[75] A. Gloria, F. Cercas, and N. Souto, “Design and implementation of an´ iot gateway to create smart environments,” Procedia Computer Science, vol. 109, pp. 568–575, 2017.
[76] A. Malek, Y Nait Kharbouch, H. El Khoukhi, M. Bakhouya, V. De Florio, D. El Ouadghiri, S. Latre, and C. Blondia, “On the use of iot and´ big data technologies for real-time monitoring and data processing,” Procedia computer science, vol. 113, pp. 429–434, 2017.
[77] D. Koo, K. Piratla, and C. J. Matthews, “Towards sustainable water supply: schematic development of big data collection using internet of things (iot),” Procedia engineering, vol. 118, pp. 489–497, 2015.
[78] F. Olivier, G. Carlos, and N. Florent, “New security architecture for iot network,” Procedia Computer Science, vol. 52, pp. 1028–1033, 2015.
[79] G. Aloi, G. Caliciuri, G. Fortino, R. Gravina, P. Pace, W. Russo, and C. Savaglio, “Enabling iot interoperability through opportunistic smartphone-based mobile gateways,” Journal of Network and Computer Applications, vol. 81, pp. 74–84, 2017.
[80] A. H. Joyce and M. Saravanan, “Design of digital zigbee transmitter for iot application,” Asian Journal of Applied Science and Technology (AJAST), vol. 1, no. 3, pp. 153–156, 2017.
[81] M. Di Yin, J. Cho, D. Park et al., “Pulse-based fast battery iot charger using dynamic frequency and duty control techniques based on multisensing of polarization curve,” Energies, vol. 9, no. 3, pp. 1–20, 2016.
[82] A. Shrivastava and R. Harshitha, “Smart parking: Green iot for smart city,” Asian Journal of Applied Science and Technology (AJAST), vol. 1, no. 5, pp. 86–90, 2017.
[83] A. Uchida, S. Shimokawa, K. Matsui, and H. Oshima, “Threedimensional wireless power transfer method to realize efficient charging of iot devices,” FUJITSU Sci. Tech. J, vol. 53, no. 2, pp. 51–56, 2017.
[84] B. Alangot, M. Suresh, A. S. Raj, R. K. Pathinarupothi, and K. Achuthan, “Reliable collective cosigning to scale blockchain with strong consistency,” in Proceedings of the Network and Distributed System Security Symposium (DISS18). NDSS, 2018.
[85] A. Al-Fuqaha, M. Guizani, M. Mohammadi, M. Aledhari, and M. Ayyash, “Internet of things: A survey on enabling technologies, protocols, and applications,” IEEE communications surveys & tutorials, vol. 17, no. 4, pp. 2347–2376, 2015.
[86] N. Sharma, A. Gupta, V. Ghadge, and M. Harwani, “lot based ration card system using bluetooth technology,” International Journal of Engineering Science and Computing, vol. 7, no. 3, 2017.
[87] R. J. Benjamin, N. Kannan, K. Lalitha, A. KM, and S. DG, “Virtual wardrobe: An iot based closet,” International Journal of Engineering Science, vol. 4984, 2017.
[88] M. N. Rajkumar and K. Karthigeyan, “Smart security management for zigbee gprs protocol using iot gateway,” 2017.
[89] K. Nirde, P. S. Mulay, and U. M. Chaskar, “Iot based solid waste management system for smart city,” in 2017 International Conference on Intelligent Computing and Control Systems (ICICCS). IEEE, 2017, pp. 666–669.
[90] A. S. Wijaya, Z. Zainuddin, and M. Niswar, “Design a smart waste bin for smart waste management,” in 2017 5th International Conference on Instrumentation, Control, and Automation (ICA). IEEE, 2017, pp. 62–66.
[91] V. T. Wilson, M. Venkatesh, S. Panicker, S. G. Bhat, and R. Sanjeetha, “Smart waste collecting hopper (swach): A service for all,” in 2015 Twelfth International Conference on Wireless and Optical Communications Networks (WOCN). IEEE, 2015, pp. 1–4.
[92] P. Haribabu, S. R. Kassa, J. Nagaraju, R. Karthik, N. Shirisha, and M. Anila, “Implementation of an smart waste management system using iot,” in 2017 International Conference on Intelligent Sustainable Systems (ICISS). IEEE, 2017, pp. 1155–1156.
[93] S. Mukherjee, B. Bhattacharyya, and N. Banerjee, “Harnessing green energy for smart dustbin,” in 2017 IEEE International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM). IEEE, 2017, pp. 484–490.
[94] C. Premalatha , “Automatic Smart Irrigation System Using IOT ,” in 2019 International Journal of Scientific Research in Computer Science and Engineering. Vol.7, Issue.1, pp.1-5 .
[95] Vidhi Tiwari, Pratibha Adkar “Implementation of IoT in Home Automation using android application ,” in 2019 International Journal of Scientific Research in Computer Science and Engineering. Vol.7, Issue.2, pp.11-16.
[96] Raghavendra S, Chitra S Reddy, Geeta C M, Rajkumar Buyya, Venugopal K R, S S Iyengar, L M Patnaik, “Survey on Data Storage and Retrieval Techniques over Encrypted Cloud Data,” in 2016 International Journal of Computer Science and Information Security (IJCSIS). pp. 484–490.
[97] Anna Kobusińska , Carson Leung, Ching-Hsien Hsu, Raghavendra S., Victor Chang, “Emerging trends, issues and challenges in Internet of Things, Big Data and cloud computing,” in 2018 Future Generation Computer Systems, pp. 416–419.

Akhila J, Ananya Lakshmi, Ashritha B, Jayashree P, Raghavendra S, Raghavendra Katagall, "A Survey on Challenges, Trends and Technologies of Internet of Things," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.906-917, 2019.

Internet of Things or IoT is an interconnected network of physical devices connected to each other through the internet. The ‘things’ here refer to the physical object in the network that has its own unique IP address and has the ability to send and receive data over the network. It is a growing topic of interest these and will deeply affect our daily life. This thesis work aims to apply the IoT paradigm for controlling and monitoring of a smart lighting application. The implementation aims to reduce the energy consumption in addition to, achieve adaptability of the lights according to the surrounding environment. The implementation uses Service Oriented Architecture (SOA) to allow heterogeneity and interoperability between components.

energy efficient, Internet of Things, Device Profile Web Service, automation, Key Performance Indicators, Web Services, Service Oriented Architecture

[1] “Energy efficient Europe,” 22 June 2011. [Online]. Available:
http://ec.europa.eu/news/energy/110622_en.htm [Accessed 22 August 2013].


[2] Aalto University School of Science and Technology, Guidebook on Energy Efficient Electric Lighting for Buildings, Raisio: IEA publications, 2010.
[3] European Research Projects on the Internet of Things (CERP-IoT), “Internet of Things -Strategic Research Roadmap,” 2009.
[4] R. Melfi, B. Rosenblum, B. Nordman, and K. Christensen, “Measuring building occupancy using existing network infrastructure,” in Green Computing Conference and Workshops (IGCC), 2011 International, July 2011, pp. 1–8.
[5] V. L. Erickson, M. A. Carreira-Perpi ´ n˜an, and A. E. Cerpa, “Occupancy ´ modeling and prediction for building energy management,” ACM Transactions on Sensor Networks (TOSN), vol. 10, no. 3, pp. 42, 2014.
[6] RF-based user location and tracking system,” proceedings of the IEEE, vol. 97, no. 3, pp. 482, 2009.
[7] M. Shur and A. Zukauskas, “Solid-State Lighting: Toward Superior Illumination,” Proceedings of the IEEE, vol. 93, no. 10, pp. 1693-1695, 2005.
[8] JUNCTIONS,” Appl. Phys. Lett., vol. 1, no. 4, pp. 82-83, 1962
[9] S. Kunić and Z. Šego, “OLED technology and displays,” in ELMAR, Zadar, 2012
[10] N. Bardsley, “OLED vs LED lighting: Is there room for OLED lighting?,” 29 May 2013. [Online]. Available: http://www.idtechex.com/research/articles/ole
D vs led lighting is there room for oled lighting-00005477.asp. [Accessed 1 November 2013].
[11] M. Miki, T. Hiroyasu and K. Imazato, “Proposal for an intelligent lighting system, and verification of control method
[12] K. Chintalapudi, A. Padmanabha Iyer, and V. N. Padmanabhan, “Indoor localization without the pain,” in Proceedings of the
[13] M. Youssef and A. Agrawala, “The Horus WLAN location determination system,” in Proceedings of the 3rd International Conference on Mobile Systems, Applications, and Services, ser. MobiSys ’05. New York, NY, USA: ACM, 2005, pp. 205–218. [Online]. Available: http://doi.acm.org/10.1145/1067170.1067193
[14] I. Guvenc, C. T. Abdallah, R. Jordan, and O. Dedeoglu, “Enhancements to RSS based indoor tracking systems using Kalman filters,in Proc. Global Signal Processing Expo (GSPx), Dallas, TX, Mar 2003
[15] Azevedo, M. G. Morgan and F. Morgan, “The Transition to Solid-State Lighting,” proceedings of the IEEE, vol. 97, no. 3, pp. 482, 2009.
[16] R. Karlicek, “Smart lighting - more than illumination,” in Asia Communications and Photonics Conference (ACP), Guangzhou, 2012.
[17] Siddiqui, A. Ahmad, H. K. Yang and C. Lee, “ZigBee based energy efficient outdoor lighting control system,” in 14th International Conference on Advanced Communication Technology (ICACT), Pyeong Chang, 2012.
[18] L. V. Popa and I. Finis, “The Design of a Street Lighting Monitoring and Control System,” in International Conference and Exposition on Electrical and Power Engineering (EPE), Iasi, 2012.

Seema, Rajkumar, "Cost Efficiency for Load Devices Based on IOT," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.918-921, 2019.

Nowadays a huge amount of data is generated by individual due to sharing of data such as photos, videos, documents, use of online platforms and various gadgets. The major challenge faced by an individual is to manage the data which exceeds the limit of mass storage devices. Cloud storage services allow its users to store their data online at affordable cost and makes it available all the time. Due to accessibility, scalability affordability, etc. the usage of cloud storage is increasing tremendously. In this paper, we aim to explore and identify the factors which affect the usage of cloud data storage and find the association between them. Under this research, a survey was held to gather data from the study area that is Vadodara city. We have used the Chi-square test for independence of attributes to check the association between the factors affecting the usage of data storage and find the degree of association between them using T Schuprow’s coefficient of association. Multiple Response Analysis to study the data was done. Statistical Package for Social Sciences (SPSS) software was used for analysis.

Cloud Computing, Data Storage, Multiple Response Analysis, Chi-square, T Schuprow’s

[1] Garrison, G., Kim, S., Wakefield, R.L. “Success Factors for Deploying Cloud Computing”. Communications of the ACM. 55, 62–68, 2012.
[2] Liang-Jie Zhang, Qun Zhou, "CCOA: Cloud Computing Open Architecture “. In proceeding of IEEE International Conference on Web Services (ICWS), pp. 607-616, 6-10, July 2009.
[3] Yashpalsinh Jadeja, Kirit Modi, “Cloud Computing Concepts, Architecture and Challenges”. In Proceeding of International Conference on Computing, Electronics and Electrical Technologies [ICCEET], 2012.
[4] Quick, D. and Choo, K. K. R. “Digital droplets: Microsoft SkyDrive forensic data remnants”. Future Generation Computer Systems-the International Journal of Grid Computing and Escience, 29, 1378-1394, 2013a.
[5] Google Drive Support. “How to share - Drive Help.”. [Online] Available at:
https://support.google.com/drive/answer/2494822?hl=en, 2015.
[6] Apple. “Backup and restore your iPhone, iPad, or iPod touch using iCloud or iTunes”- Apple Support. [Online] Available at: https://support.apple.com/en-ie/HT203977, 2015.
[7] Drago, I., Mellia, M., M Munafo, M., Sperotto, A., Sadre, R., and Pras, A. “Inside Dropbox”. The ACM
Conference, 481, 2012.
[8] Geel, M. “Cloud Storage: File Hosting and Synchronisation 2.0.” [Online] Available at:https://www.vis.ethz.ch/de/visionen/pdfs/2012/visionen_2012_3.pdf?end=15&start
=11 Google Drive Support. 2013.
[9] M. M. Dahshan and Dr. Sherif El- Kassas, Data Security in Cloud Storage Services, 2013
[10] Dean O’Gorman, Cloud Computing Data Storage: Usage, security, and privacy issues for individual users
[11] Priyanshu Srivastava and Rizwan Khan, A Review Paper on Cloud Computing, International Journals of Advanced Research in Computer Science and Software Engineering, June 2018

Khimya S Tinani, Bhargav Choithwani, Bhagyashree Patil, Pathan Faiyazkhan, Tanvi Salat, "Study on Usage Pattern of Public Cloud Storage," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.922-927, 2019.

The communication technology is growing day by day to provide instant and enhanced medical facilities to patients regardless of their physical location. Patients can be monitored and provided with quick medication while they are on the move. The existing technology is also capable to provide self-monitoring. Self-monitoring means people can use wireless technology to monitor their health at home on daily basis. The existing system provides home based ECG monitoring that reads physiological data and then convert them into readable format. Internet of Things (IOT) is new era of telecommunication that provides smart communication between human and sensor devices through various wireless technologies such as Wi-Fi, RFID, Bluetooth and ZigBee. Our proposed dynamic framework facilitates people to connect and communicate with healthcare centres in dynamic way while they are moving out of their home location. Secondly, the proposed system also make use of advance data management technique known as NoSQL especially used for un-structured datasets generated through ECG, SCG and other vital parameters of human body with the help of sensor networks. The paper is organised into sections viz. introduction, existing work, use of IoTs in wireless healthcare monitoring systems, proposed system, implementation and conclusion.

ZigBee, ECG, Sensor Network, NoSQL, IoT, Bluetooth, Wi-Fi

[1]. Uttara Gogate, Manali Marathe, Jay, Mourya, Nipunaya Mohan, “Android Based Health Monitoring System for cardiac Patients”, International Research Journal of Engineering and Technology(IRJET),Vol:04,Issue:04,2017,ISSn:2395-0072,pp:-1628-1634
[2]. Dey,N.,Ashour,A.S,Shi,F.,Fong,S.J,Sherratt,R.S,”Developing residential wireless sensor networks for ECG healthcare Monitoring”,IEEE Transactions on Consumer Electronics,63(4).pp.442-449.ISSN 0098-3063.
[3]. Uttara Gogate,Jagdish Bakal,”Healthcare monitoring System Based on Wireless Sensor Network for Cardiac Patients”,Biomedical & Pharamacology Journal,Sep 2018,Vol.11(3),pp.1681-1688
[4]. Zeinab Kamal, Aldein Mohammed, Elmustafa Sayed Ali Ahmed, “Internet of Things Applications, Challenges and Related Future Technologies”, www.worldscienticnews.com,67(2)(2017), pp.126-148
[5]. Mohamed Elgendi,Abdulla AL-Ali,Amr Mahamed,Rabab Ward,” Improving Remote Health Monitoring: A Low Complexity ECG Compression Approach”, MDPI, Diagnostics 2018,8,doi:10.3390/diagnostics8010010
[6]. Prasan Kumar Sahoo, Hiren kumar Thakkar, Wen-Yen Lin, Po-Cheng Chang,Ming Yih lee, “On the design of Efficient Cardiac Health Monitoring System Through Combined Analysis of ECG and SCG signals”, MDPI, Sensors 2018,18,379;doi:10.3390/s18020379
[7]. Dr. Archana Raje, Aniket Jgadale, ”Sql Vs NoSql: NewSql The solution for Big Data”, 4th-SICTIM’2018, IOSR journal of Computer Enginnering (IOSR-JCE), e-ISSN: 2278-0661, pp.45-51
[8]. Nancy Fernando E, “A Survey on Android Based Patient Monitoring system” GRD Journals, Global Research and Development Journal
for Engineering, International Conference on Innovations in engineering and Technology (ICIET) – 2016, July 2016 e-ISSN: 2455-5703
[9]. Nidhi Mutha1, “Patient Health Monitoring Using Android Application”
International Journal of Innovative Research in Computer And Communication Engineering Vol. 4, Issue 3, March 2016
[10]. Rajesh Naidu, D. Bindu, Asha Jyothi , G.Roshini, “Android Based Healthcare Monitoring System”. International Journal of Advance Foundation and Research in Computer (IJAFRC) Volume 2, Special Issue (NCRTIT 2015), January 2015. ISSN 2348 – 4853
[11]. N. Ebrahim, M. J. Deen and T. Mondal, “A wireless wearable ECG sensor for long-term applications,” IEEE
Commun. Mag., vol. 50, no. 1, pp. 36–43, Jan. 2012.
[12]. T. K. L. Hui, R. S. Sherratt and D. Diaz Sanchez, “Major requirements for building Smart Homes in Smart
Cities based on Internet of Things technologies,” Future Generation Computer Systems, vol. 76, pp. 358–369,
Nov. 2017.
[13]. A. Pantelopoulos and N. G. Bourbakis, “A survey on wearable sensor-based systems for health monitoring and
prognosis,” IEEE Trans. Syst. Man, Cybern. B., vol. 40, no. 1, pp. 1–12, Jan. 2010.
[14]. M. A. Ezechina, K. K. Okwara, C. A. U. Ugboaja. “The Internet of Things (Iot): A Scalable Approach to Connecting Everything.” The International Journal of Engineering
and Science 4(1) (2015) 09-12.
[15]. Sapandeep Kaur, Ikvinderpal Singh. “A Survey Report on Internet of Things Applications,” International Journal of Computer Science Trends and Technology Volume 4, Issue 2, Mar - Apr 2016.
[16]. Suwimon Vongsingthong and Sucha Smanchat. A Review of Data Management in Internet of Things. KKU Res. J. 2015
[17]. Alwan, A. Global Status Report on Noncommunicable Diseases 2010; World Health Organization: Geneva,
Switzerland, 2011.
[18]. Elgendi, M.; Eskofier, B.; Dokos, S.; Abbott, D. Revisiting QRS Detection Methodologies for Portable,
Wearable, Battery-Operated, and Wireless ECG Systems. PLoS ONE 2014, 9, 1–18.
[19]. P. Frehill, D. Chambers and C. Rotariu, “Using zigbee to integrate medical devices,” in Proc. EMBC, 2007,
pp. 6171–6720.
[20]. L.-H. Wang, Y.-M. Hsiao, X.-Q. Xie and S.-Y. Lee, “An Outdoor Intelligent Healthcare Monitoring Device
for the Elderly,” IEEE Trans. Consum. Electron., vol. 62, no. 2, pp. 128–135, May 2016.

Jaswinder Singh, Sandeep Sharma, "A Dynamic Framework for Healthcare Monitoring using Wireless Sensor Network," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.928-932, 2019.

Clustering is the grouping of a particular set of objects based on their characteristics, aggregating them according to their similarities. Regarding data mining, this methodology partitions the data implementing a specific join algorithm, most suitable for the desired information analysis. Clusters are obtained by using density based clustering and DBSCAN clustering. DBSCAN cluster is a fast clustering technique, large complexity and requires large parameters. To overcome of these problems uses the OPTICS density based algorithm. The algorithm requires the simply a single parameter, namely the least amount of points in a cluster which is required as input in density based technique. Using random projection improving the cluster quality and run time.

Cluster Analysis, Random Projections, Neighbouring

[1] Ester M, Krigel H-P, Sander J, Xu X(1996)”A density based algorithm for discovering clusters in large spatial databases either noise.” In proceeding of the ACM conference knowledge discovery and data mining (KDD),pp226-231.
[2] Ankerst M, Breunig MM, Kriegel H-P, Sander J (1999) “Optics: ordering points to identify the clustering structure.” In: Proceedings of the ACM international conference on management of data (SIGMOD),pp. 49–60.
[3] Alexander Hinneburg, Daniel A. Keim (1998),"An Efficient Approach to Clustering in Large Multimedia Databases with Noise [Online] Available: http://www.aaai.org.
[4] Hinneburg A, Gabriel H-H (2007) Denclue 2.0: fast clustering based on kernel density estimation. In Advances in intelligent data analysis (IDA), pp 70–80.
[5] Imran Khan, Joshua Zhexue Huang (2012),” Ensemble Clustering of High Dimensional Data With random Projection.” In: Proceeding of the international conference on information and knowledge management.
[6] Qi Xianting, Wang Pan,“A density-based clustering algorithm for high-dimensional data with feature selection”, 2016,IEEE.
[7] Schneider J, Vlachos M (2013) “Fast parameter less density-based clustering via random projections.” In: Proceedings of the international conference on information and knowledge management (CIKM), pp 861–866.
[8] Johannes Schneider, Michail Valchos(2017) “Scalable density based clustering with quality guarantees using random projections.” Published in Journal: Data Mining and Knowledge Discovery Volume 31 Issue 4, July 2017 pages 972-1005.

P.A. Gat, K.S. Kadam, "Quality Cluster Generation Using Random Projections," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.933-936, 2019.

In this paper using k-mean clustering method use for students school academic performance are measured by quarterly exam, half yearly exam, and final exams result. So, by taking the marks of three of exams, we can compare the final result of govt. school data and private school data. By using data clustering technique we can predict which school is best.And try to identify the weak student of particular school and will identify the result of best school.This will lead to the identification of best between private & government school in town.Strategies and techniques of best school will be followed which will help in making the education system better.

Data clustering , k-mean, academic performance etc

[1]. .Datamining Tutorial,Home>BigData&Analytics>Datamining,http://www.tutorialride.com>datamining.
[2]. https://sites.google.com/site/dataclusteringalgorithms/k-means-clustering-algorithm
[3]. 3.Oyelade, O. J ,Oladipupo,O.O,Obagbuwa.I.C (IJCSIS), Application of k-Means Clustering algorithm for prediction of Students’ Academic Performance, Vol. 7, _o. 1, 2010,
[4]. Sunita B Aher, Mr. LOBO L.M.R.J.,Data Mining in Educational System using WEKA, (ICETT) 2011
[5]. Bindiya M Varghese, Jose Tomy J, Unnikrishnan A,Poulose Jacob K,Clustering Student Data to Characterize Performance Patterns, (IJACSA)
[6]. Mohammed M. Abu Tair, Alaa M. El-Halees, Mining Educational Data to Improve Students’ Performance: Volume 2 No. 2, February 2012
[7]. Dorina Kabakchieva, Student Performance Prediction by Using Data Mining Classification Algorithms, Vol 1 Issue 4 November 2012
[8]. Surjeet Kumar Yadav,Saurabh Pal,Data Mining: A Prediction for Performance Improvement of Engineering Students using Classification, Vol. 2, No. 2, 51-56, 2012
[9]. Dr. Sudhir B. Jagtap, Dr. Kodge B. G.,Census Data Mining and Data Analysis using WEKA, (ICETSTM – 2013)
[10]. P.Veeramuthu#1, Dr.R.Periyasamy#2, V.Sugasini, Analysis of Student Result Using Clustering Techniques, (IJCSIT) Vol. 5 (4) , 2014
[11]. M. Durairaj , C. Vijitha , Educational Data mining for Prediction of Student Performance Using Clustering Algorithms, (IJCSIT) Vol. 5 (4) , 2014
[12]. Kashish Kohli,Shiivong Birla,Data Mining on Student Database to Improve Future Performance, 15, July 2016
[13]. Mr. Shashikant Pradip Borgavakar, Mr. Amit Shrivastava, Evaluating Student’s Performance using K-Means Clustering, Vol. 6 Issue 05, May – 2017
[14]. Dr. K. Karthikeyan, P. Kavipriya, On Improving Student Performance Prediction in Education Systems using Enhanced Data Mining Techniques, Volume 7, Issue 5, May 2017
[15]. Hilal Almarabeh, Analysis of Students` Performance by Using Different Data Mining Classifiers, 2017.08.02
[16]. Hafez Mousa1, Ashraf Maghari2, School Students` performance Predication Using Data Mining Classification, Vol. 6, Issue 8, August 2017
[17]. K. Govindasamya and T. Velmuruganb, A Study on Classification and Clustering Data Mining Algorithms based on Students Academic Performance Prediction, Volume 10 • Number 23 • 2017,
[18]. Abdelbaset Al-Masri, Experiences in Mining Educational Data to Analyze Teacher`s Performance: A Case Study with High Educational Teachers, 2017.10.12.01

Bhawna Janghel, Asha Ambhaikar , "A Study of Clustering Algorithm for Student Analysis," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.937-940, 2019.

In wireless communication networks like STDMA Networks give a fruitful response for engaging Wireless gadgets to get the chance to arrange resources with sensibility and viability. Right when numerous gathering correspondences are completed in such Networks, the scheduling algorithm should deliver fitting point table projects of all the programs where the objectives intend to decrease the framework length. Study the issue of conveying a capable logbook course of action for different gathering interchanges over the STDMA node scheduling framework suggested in the process of integrated multiple-group communication and traffic-oriented node scheduling (IMCTNS) issue. It is exhibited that the IMCTNS issue could be point by point as a integer linear programming (ILP) issue. A polynomial-point brought together heuristic scheduling algorithm, appointed as broadcasting Level-by-Level Scheduling (B-LBLS), is suggested for choosing the point table arrangement subject to broadcast prerequisites. To update a dimensional use capability inside every accessibility, a moved type of B-LBLS, appointed as Collision-Allowed Level-by-Level Scheduling (CA-LBLS), is future subject to adapted outline-based impedance illustrate. It is publicized that appeared differently in relation to present TDMA and STDMA-based algorithms. Here examined the whole present part with the reason of gainful scheduling.

Multi hop wireless networks, node scheduling algorithm, wireless mesh networks, load balancing

[1] W. Kiess and M. Mauve, “A survey on real-world implementations of mobile ad-hoc networks,” Ad Hoc Netw., vol. 5, no. 3, pp. 324–339, 2007.
[2] G. J. Pottie, “Wireless sensor networks,” in Proc. IEEE Inf. Theory Workshop, Jun. 1998, pp. 139–140.
[3] I. F. Akyildiz, X. Wang, and W. Wang, “Wireless mesh networks: A survey,” Comput. Netw., vol. 47, no. 4, pp. 445–487, 2005.
[4] C. Bettstetter and C. Hartmann, “Connectivity of wireless multihop networks in a shadow fading environment,” Wireless Netw., vol. 11, no. 5, pp. 571–579, 2005.
[5] P. Gupta and P. R. Kumar, “Critical power for asymptotic connectivity in wireless networks,” in Stochastic Analysis, Control, Optimization and Applications. Boston, MA, USA: Birkhäuser, 1999, pp. 547–566.
[6] P. Gupta and P. R. Kumar, “The capacity of wireless networks,” IEEE Trans. Inf. Theory, vol. 46, no. 2, pp. 388–404, Mar. 2006.
[7] J. Li, C. Blake, D. S. J. De Couto, H. I. Lee, and R. Morris, “Capacity of ad hoc wireless networks,” in Proc. 7th Annu. Int. Conf. Mobile Comput. Netw., 2001, pp. 61–69.
[8] M. Grossglauser and D. N. C. Tse, “Mobility increases the capacity of ad hoc wireless networks,” IEEE/ACM Trans. Netw., vol. 10, no. 4, pp. 477–486, Aug. 2002.
[9] S. Weber, J. G. Andrews, and N. Jindal, “An overview of the transmission capacity of wireless networks,” IEEE Trans. Commun., vol. 58, no. 12, pp. 3593–3604, Dec. 2010.
[10] L. Tassiulas and A. Ephremides, “Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks,” IEEE Trans. Autom. Control, vol. 37, no. 12, pp. 1936–1948, Dec. 1992.
[11] X. Lin and N. B. Shroff, “Joint rate control and scheduling in multihop wireless networks,” in Proc. 43rd IEEE Conf. Decision Control (CDC), vol. 2. Dec. 2004, pp. 1484–1489.
[12] N. Ben Salem and J.-P. Hubaux, “A fair scheduling for wireless mesh networks,” in Proc. IEEE Workshop Wireless Mesh Netw. (WiMesh), Sep. 2005.
[13] Z. Ning, L. Guo, Y. Peng, and X. Wang, “Joint scheduling and routing algorithm with load balancing in wireless mesh network,” Comput. Elect. Eng., vol. 38, no. 3, pp. 533–550, 2012.
[14] Y. Li and A. Ephremides, “A joint scheduling, power control, and routing algorithm for ad hoc wireless networks,” Ad Hoc Netw., vol. 5, no. 7, pp. 959–973, 2007.
[15] R. L. Cruz and A. V. Santhanam, “Optimal routing, link scheduling and power control in multihop wireless networks,” in Proc. 22nd Annu. Joint Conf. IEEE Comput. Commun. (INFOCOM), vol. 1. Mar./Apr. 2003, pp. 702–711.
[16] E. Hyytia and J. Virtamo, “On load balancing in a dense wireless multihop network,” in Proc. 2nd Conf. Next Generat. Internet Design Eng. (NGI), 2006, p. 8.
[17] A. Sgora, D. J. Vergados, and D. D. Vergados, “A survey of TDMA scheduling schemes in wireless multihop networks,” ACM Comput. Surv., vol. 47, no. 3, p. 53, 2015.
[18] R. Gunasekaran, S. Siddharth, P. Krishnaraj, M. Kalaiarasan, and V. R. Uthariaraj, “Efficient algorithms to solve broadcast scheduling problem in WiMAX mesh networks,” Comput. Commun., vol. 33, no. 11, pp. 1325–1333, 2010.
[19] J.-S. Li, K.-H. Liu, and C.-H. Wu, “Efficient group multicast node scheduling schemes in multi-hop wireless networks,” Comput. Commun., vol. 35, no. 10, pp. 1247–1258, 2012.
[20] C.-T. Chiang, H.-C. Chen, W.-H. Liao, and K.-P. Shih, “A decentralized minislot scheduling protocol (DMSP) in TDMA-based wireless mesh networks,” J. Netw. Comput. Appl., vol. 37, pp. 206–215, Jan. 2014.
[21] D. Arivudainambi and D. Rekha, “Heuristic approach for broadcast scheduling, problem in wireless mesh networks,” AEU-Int. J. Electron. Commun., vol. 68, no. 6, pp. 489–495, 2014.
[22] Y. Liu, V. O. K. Li, K.-C. Leung, and L. Zhang, “Topology-transparent distributed multicast and broadcast scheduling in mobile ad hoc networks,” in Proc. IEEE 75th Veh. Technol. Conf. (VTC Spring), May 2012, pp. 1–5.
[23] B. Zeng and Y. Dong, “A collaboration-based distributed TDMA scheduling algorithm for data collection in wireless sensor networks,” J. Netw., vol. 9, no. 9, pp. 2319–2327, 2014.
[24] C. Xu, Y. Xu, Z. Wang, and H. Luo, “A topology-transparent MAC scheduling algorithm with guaranteed QoS for multihop wireless network,” J. Control Theory Appl., vol. 9, no. 1, pp. 106–114, 2011.
[25] N. Lam, M. K. An, D. T. Huynh, and T. Nguyen, “Broadcast scheduling problem in SINR model,” Int. J. Found. Comput. Sci., vol. 25, no. 3, pp. 331–342, 2014.
[26] D. Arivudainambi and S. Balaji, “Improved memetic algorithm for energy efficient sensor scheduling with adjustable sensing range,” Wireless Pers. Commun., vol. 95, no. 2, pp. 1737–1758, 2016.
[27] Y. Liu, V. O. K. Li, K.-C. Leung, and L. Zhang, “Performance improvement of topology-transparent broadcast scheduling in mobile ad hoc networks,” IEEE Trans. Veh. Technol., vol. 63, no. 9, pp. 4594–4605, Nov. 2014.
[28] X. Tian, J. Yu, L. Ma, G. Li, and X. Cheng, “Distributed deterministic broadcasting algorithms under the SINR model,” in Proc. IEEE INFOCOM, Apr. 2016, pp. 1–9.
[29] J. G. Andrews et al., “What will 5G be?” IEEE J. Sel. Areas Commun., vol. 32, no. 6, pp. 1065–1082, Jun. 2014.
[30] N. Panwar, S. Sharma, and A. K. Singh, “A survey on 5g: The next generation of mobile communication,” Phys. Commun., vol. 18, pp. 64–84, Mar. 2016. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S1874490715000531
[31] J. Li, X. Wu, and R. Laroia, OFDMA Mobile Broadband Communications: A Systems Approach, 1st ed. New York, NY, USA: Cambridge Univ. Press, 2013.
[32] J. Xiao, C. Yang, J. Wang, and H. Dai, “Joint interference management in ultra-dense small cell networks: A multi-dimensional coordination,” in Proc. 8th Int. Conf. Wireless Commun. Signal Process. (WCSP), Oct. 2016, pp. 1–5.
[33] J. Andrews, S. Singh, Q. Ye, X. Lin, and H. Dhillon, “An overview of load balancing in HetNets: Old myths and open problems,” IEEE Wireless. Commun., vol. 21, no. 2, pp. 18–25, Apr. 2014.
[34] D. J. Vergados, N. Amelina, Y. Jiang, K. Kralevska, and O. Granichin, “Local voting: Optimal distributed node scheduling algorithm for multihop wireless networks,” in Proc. INFOCOM Workshop, Atlanta, GA, USA, May 2017, pp. 931–932.
[35] N. Amelina, A. Fradkov, Y. Jiang, and D. J. Vergados, “Approximate consensus in stochastic networks with application to load balancing,” IEEE Trans. Inf. Theory, vol. 61, no. 4, pp. 1739–1752, Apr. 2015.

B. Abhishek Reddy, "A Survey on Multi hop Wireless Network for efficient schedule algorithms," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.941-946, 2019.