Mayas Publications logo
Buy Books Buy journals

Journal Issues

Back To Archive
Vehicle Localization and Velocity Estimation using Smart Phones
K.MADHINI
Pages: 1- 4 | First Published: 05 Feb 2017
Full text | Abstract | Purchase | References | Request permissions

Abstract 
Android operating system is at the top in market because of its features like portability, platform independence, and low memory consumption.Our Application is designed for children and Parent to track the children while they are travelling through School or College Bus through Gps Technology. Now time has come for both he parents to work in such scenario the security of children is very important.This Application is mainly developed for toddler
Our proposed Application is a multipurpose students safety application which will work
on android platform.
 

References

  1. S. Li, Y. Lou, B. Liu, "Bluetooth aided  mobile phone localization: a non linear neural circuit approach," ACM
    Transactions on Embedded Computing Systems, vol. 13, no. 14, article no. 78, 2014. 

  2. S. Li, B. Liu, B. Chen, Y. Lou,"Neural network based mobile phone localization using Bluetooth connectivity," Neural Computing and Applications, vol. 23, no. 3, pp. 667-675, 2012. 

  3. G. Rose, "Mobile phones as traffic probes: practices, prospects and issues," Transport Reviews, vol. 26, no. 3, pp. 275-291, 2006. 

  4.  S. Li, F. Qin,"A dynamic neural network approach for solving nonlinear inequalities defined on a graph and its application to distributed, routing-free, range-free localization of WSNs," Neuro computing, vol. 117, pp. 72-80, 2013. 

  5. A. Thiagarajan, L. Ravindranath, K. LaCurts, S. Madden, H. Balakrishnan, S. Toledo, J. Eriksson, "VTrack: accurate,
    energy-aware road traffic delay estimation using mobile phones," Proceedings of the 7th ACM Conference
    on Embedded Networked Sensor Systems, Berkeley, California, USA, 2009.  

  6. Wikipedia: Street canyon. [Online]. Available:  

Fall Accident Rescue using Fall Detection Algorithm
T . HEMALATHA
Pages: 5-11 | First Published: 05 Feb 2017
Full text | Abstract | Purchase | References | Request permissions

Abstract 
Architecture for the fall accident detection and corresponding wide area rescue system based on a smart phone and the third generation(3G) networks. To realize the fall detection algorithm, the angles acquired by the electronic compass and the waveform sequence of the triaxial accelerometer on the smart phone are used as the system inputs. The acquired signals are then used to generate an ordered feature sequence and then examined in a
sequential manner by the proposed cascade classifier for recognition purpose. With the proposed cascaded classification architecture, the computational burden and power consumption issue on the smart phone system can be alleviated.
Keywords: Fall detection; Fast Emergency Rescue; Triaxial Accelerometer; Cascade Classifier; 
 

References

  1. G. Acampora, D. J. Cook, P. Rashidi, and A. V. Vasilakos, “A Survey on ambient intelligence in healthcare,”
    Proc. IEEE, vol. 101, no. 12, pp. 2470 – 2494, Dec. 2013.  

  2. P. Rashidi and A. Mihailidis, “A survey on ambient-assisted living tools for older adults,” IEEE J. Biomed.
    Health Informat., vol. 17, no. 3, pp. 579–590, May 2013. 

  3. M. Mubashir, L. Shao, and L. Seed “A survey on fall detection:Principles and approaches,” Neuro computing, vol. 100, no. 16, pp. 144–152, 2013. 

  4. T. Shany, S. J. Redmond, M. R. Narayanan, and N. H. Lovell, “Sensors- Based wearable systems for
    monitoring of human movement and falls,” IEEE Sensors J., vol. 12, no. 3, pp. 658–670, Mar. 2012.

  5. B.Mirmahboub, S. Samavi,N.Karimi, and S. Shirani, “Automatic monocular system for human fall detection based on variations in silhouette area,” IEEE Trans. Biomed. Eng., vol. 60, no. 2, pp. 427–436, Feb. 2013.  

  6. M. Yu, Y. Yu, A. Rhuma, S. M. R. Naqvi, L. Wang, and J. A. Chambers, “An online one class support vector machine-based person-specific fall detection system for monitoring an elderly individual in a room environment,” IEEE J. Biomed. Health Informatics, vol. 17, no. 6, pp. 1002– 1014, Nov. 2013.  

  7. M. Yu, A. Rhuma, S. M. Naqvi, L. Wang, and J. Chambers, “A posture recognition-based fall detection system
    for monitoring an elderly person in a smart home environment,” IEEE Trans. Inf. Technol. Biomed., vol. 16,
    no. 6, pp. 1274–1286, Nov. 2012. 

  8. E.Auvinet, F. Multon, A. SaintArnaud, J. Rousseau, and J. Meunier, “Fall detection with multiple cameras:
    An occlusion-resistant method based on 3-D silhouette vertical distribution,” IEEE Trans. Inf. Technol. Biomed., vol. 15, no. 2, pp. 290–300, Mar. 2011. 

  9. C. Rougier, J. Meunier, A. St-Arnaud, and J. Rousseau, “Robust video surveillance for fall detection based on
    human shape deformation,” IEEE Trans. Circuits Syst. Video Technol., vol. 21, no. 5, pp. 611–622, May 2011. 

  10. Y. Li, K. C. Ho, and M. Popescu, “A microphone array system for automatic fall detection,” IEEE Trans. Biomed

  11.  A. Ariani, S. J. Redmond, D. Chang, and N. H. Lovell, “Simulated unobtrusive falls detection with
    multiple persons,” IEEE Trans. Biomed. Eng., vol. 59, no. 11, pp. 3185–3196, Nov. 2012.  

  12. M. Mercuri, P. J. Soh, G. Pandey, P. Karsmakers, G. A. E. Vandenbosch, P. Leroux, andD. Schreurs, “Analysis of
    an indoor biomedical radar-based system for health monitoring,” IEEE Trans.Microw. Theory Tech., vol. 61,
    no. 5, pp. 2061–2068, May 2013. 

  13. H. Rimminen, J. Lindstr¨om, M. Linnavuo, and R. Sepponen, “Detection of falls among the elderly by a floor sensor using the electric near field,” IEEE Trans. Inf. Technol. Biomed., vol. 14, no. 6, pp. 1475– 1476, Nov. 2010.  

Collaborative Filtering Model Based on Matrix Factorization Using Incremental and Static Combined Scheme
M.MARY RESHMA
Pages: 12-18 | First Published: 05 Feb 2017
Full text | Abstract | Purchase | References | Request permissions

Abstract  
The last decade has witnessed a tremendous
growth of Web services as a major
technology for sharing data, computing
resources, and programs on the Web. With
increasing adoption and presence of Web
services, designing novel approaches for
efficient and effective Web service
recommendation has become of paramount
importance. In existing web services
discovery and recommendation approaches
focus on keyword-dominant Web service
search engines, which possess many
limitations such as poor recommendation
performance and heavy dependence on
correct and complex queries from users.
Recent research efforts on Web service
recommendation center on two prominent
approaches: collaborative filtering and
content-based recommendation.  Unfortunately, both approaches have some
drawbacks, which restrict their applicability
in Web service recommendation. In
proposed system for recommendation we
will be using Agglomerative Hierarchal
Clustering or Hierarchal Agglomerative
Clustering for effective recommendation in
web-services. our approach considers
simultaneously both rating data (e.g., QoS)
and semantic content data (e.g.,
functionalities) of Web services using a
probabilistic generative model.
Index Terms—Collaborative filtering,
incremental model, matrix factorization,
recommender system, combined scheme,
static model.
 

References

  1.  Burton W. Andrews, Kevin M. Passino,  and Thomas  A. Waite, ―Social Foraging Theory For Robust Multiagent System Design,‖ IEEE Transactions on Automation     Science   and   Engineering, Jan 2007, Vol.4

  2. Deepak Agarwal, Bee-Chung Chen, Pradheep Elango,  ― Fast Online Learning  through   Offline Initialization   for  Time-sensitive   Recommendation,‖ IEEE    Transactions  On   Consumer  Electronics,   Vol.56, No.3,March 2010. 

  3.  Gedimina  s   Adomavicius   and   Alexander  Tuzhilin , ―Toward the  Next   Generation   of   Recommender   Systems, A Survey of the State-of-the and Possible Extensions, ‖ IEEE Transactions on Knowledge and   Data  Engineering, Jan 2005, Vol.17. 

  4. Gediminas Adomavicius   and  Young Ok Kwon,  ―Improving Aggregate   Recommendation  Diversity   
    Using  Ranking-Based Techniques,‖   IEEE Transactions  on Knowledge and Data Engineering, May 2012, Vol.24.

  5. Genevieve Gorrell, “Generalized Hebbian Algorithm for Incremental Singular Value Decomposition in
    Natural Language Processing,‖ IEEE Transactions On Consumer Electronics Vol.54.No.3, Jan 2006. 

  6. István Pilászy, Dávid Zibriczky, Domonkos Tikk, “Fast ALS-based Matrix Factorization for Explicit and Implicit Feedback Datasets,‖ IEEE Transactions On Consumer Electronics Vol.54 ,No.1, Jan 2010. 

  7. Jeffrey  Junfeng Pan,   Sinno Jialin Pan, Jie Yin,  Lionel  M. Ni and Qiang Yang, ―Tracking  Mobile   Users in  
    Wireless Networks via  Semi-Supervised   Colocalization ,‖   IEEE  Transactions   on  Pattern Analysis and Machine   Intelligence   March 2012, Vol.34 

Team Work and Employment Practices at Glory Boys Apparel Pvt. Ltd., Bangalore
Mr. I.V. RANJIT KUMAR,
Pages: 19-32 | First Published: 05 Feb 2017
Full text | Abstract | Purchase | References | Request permissions

Abstract
Teamwork is viewed as a panacea for enhancing communication, coordination and integration of diverse information at the disposal of individual members. In this regard, teamwork opposes the traditional Taylors intentions to isolate employees by assigning to standard tasks sequentially designed and at the same time allowing fewer chances for communication.
Keywords:  Team Work, Communication, Involvement, Empowerment
 

References

  1. The employees of Age group 31-50  years and above have less Mutual Support than the below 20 years of age group, so they have to improve mutual support between them.

  2. The employees having Educational Qualification of SSC and PG has less Mutual Support so, they have to improve it.

  3.  The team structure of employees having below 5years of experience, 11 and above years of experience is not
    good, so they have to improve the team structure. 

  4. To reduce the communication gap between the employees of low vs medium and Medium vs high groups. 

  5. To change the team structure of job characteristics and employee
    empowerment of employees belonging to the low vs medium and low vs high groups. 

  6. The mutual support of medium vs high is less so the employees of those groups must improve it. 

The Impact of Retail Investor’s Behavior on Equity Shares in Chennai City – an Empirical Study
Dr.E.VISWANATHAN
Pages: 33-46 | First Published: 05 Feb 2017
Full text | Abstract | Purchase | References | Request permissions

References

  1.  Levine and Ross, “Stock market  Development and Economic Growth, The world Bank Economic Review, Vol.
    1012), 2008, pp: 323 – 339.  
  2. Bajpai G.N, “Indian Securities Markets – New Bench Marks”, SEBI Bulletin, Vol.1, No.8, August 2009, pp: 5-14.
  3. Retail Investments into Equity”, IIM Working paper series, E27119, p:4. 
  4. Taraporewala, Russi Jai, “The Union Budget 2005 -06 and the Capital Market”, BMA Review, Vol. III, No.26,
    March 14-278, 2006.  
  5. Ramesh Gupta, “Retail Investor – A lost Species”, IIM Working paper series, E 15378, p: 1. 
  6. Chopra V.K, “Capital Market Reforms in India: Recent Initiatives”, SEBI Bulletin, Vol.4, No. 11, Nov 2008, pp:
    7-11. 
  7. Chopra V. K, “Investor Protection: An Indian Perspective”, SEBI Bulletin, Vol.4, No.11, Nov 2010, pp: 11-15.  8 Ibid. Pp.24-26 
Text Categorization Based on Bayesian Classification Approach using Class-Specific Features
A.POORNIMA,
Pages: 56-61 | First Published: 05 Feb 2017
Full text | Abstract | Purchase | References | Request permissions

Abstract
The wide availability of web documents in electronic forms requires an automatic technique to label the documents with a predefined set of topics, what is known as automatic Text Categorization (TC). Over the past decades, it has been witnessed a  large number of advanced machine learning algorithms to address this challenging task. The generated presentation slides can be used as drafts to help the presenters prepare their formal slides in a quicker way. A novel system called PPSGen is proposed to address this task. Documents are usually represented by the ―bag-of-words‖: namely, each word  or phrase occurs in documents once or more times is considered as a feature. It first employs the regression method to learn the importance scores of the sentences in an academic paper, and then exploits the integer linear programming (ILP) method to generate well-structured slides by selecting and aligning key phrases and sentences.. This paper proposes a novel system called PPSGen to generate presentation slides from academic papers. We train a sentence scoring model based on SVR and use the ILP method to align and extract key phrases and sentences for generating the slides. Experimental results show that our method can generate much better slides than traditional methods.
Keywords: Text Categorization(TC); Machine Learning Algorithms; SVR; PPS Generate; Integer Linear Programming;
 

References

  1. H. Liu and L. Yu, ―Toward integrating  feature selection algorithms for classification and clustering,‖ IEEE
    Transactions on Knowledge and Data Engineering, vol. 17, no. 4, pp. 491– 502,2005. 

  2.  P. M. Baggen stoss, ―Class-specific feature sets in classification, ‖IEEE Transactions on Signal Processing, vol.
    47, no. 12,pp. 3428–3432, 1999. 

  3. B. Tang and H. He, ―ENN: Extended nearest neighbor method for pattern recognition [research frontier],‖ IEEE  Computational Intelligence Magazine, vol. 10, no. 3, pp. 52–60, 2015. 

  4. I.-S. Oh, J.-S. Lee, and C. Y. Suen, Analysis of class separation and combination of class-dependent features for handwriting recognition,‖ IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 10, pp. 1089–1094, 1999. 

  5. D. Cai, X. He, and J. Han, ―Document clustering using locality preserving indexing,‖ IEEE Transactions on
    Knowledge and Data Engineering, vol. 17, no. 12, pp. 1624–1637, 2005.

To Demonstrate that Proposed Ip Trace back Method Through DPM
S.SOWMIYA,
Pages: 62-68 | First Published: 05 Feb 2017
Full text | Abstract | Purchase | References | Request permissions

Abstracts
Link error and malicious packet dropping are two sources for packet losses in multi hop wireless ad hoc network. In this paper, while observing a sequence of packet losses in the network, we are interested in determining whether the losses are caused by link errors only, or by the combined effect of link errors and malicious drop.
We are especially interested in the insider attack case, whereby malicious nodes that are part of the route exploit their knowledge of the communication context to selectively drop a small amount of packets critical to the network performance. Because the packet dropping rate in this case is comparable to the channel error rate, conventional algorithms that are based on detecting the packet loss rate cannot achieve satisfactory detection
accuracy. To improve the detection accuracy, we propose to exploit the correlations between lost packets.
Furthermore, to ensure truthful calculation of these correlations, we develop a homomorphic linear authenticator (HLA) based public auditing architecture that allows the detector to verify the truthfulness of the packet loss information reported by nodes. This construction is privacy preserving, collusion proof, and incurs low communication and storage overheads. To reduce the computation overhead of the baseline scheme, a packetblock-based mechanism is also proposed, which allows one to trade detection accuracy for lower computation complexity. Through extensive simulations, we verify that the proposed mechanisms achieve significantly better detection accuracy than conventional methods such as a maximum-likelihood based detection.
Keywords: HDM; Multi-hop Wireless adhoc Network; Conventional Algorithms; Cybersecurity; IP traceback; Scalability ;
 

References

  1.  K. Liu, J. Deng, P. Varshney, and K. Balakrishnan, ―An acknowledgement- based approach for the detection of routing misbehavior in MANETs,‖ IEEE Trans. Mobile Comput., vol. 6, no. 5, pp. 536– 550, May 2006. 

  2. Y. Liu and Y. R. Yang, ―Reputation propagation and agreement in mobile adhoc networks,‖ in Proc. IEEE WCNC Conf., 2003, pp. 1510–1515. 

  3. S. Marti, T. J. Giuli, K. Lai, and M. Baker, ―Mitigating routing misbehavior in mobile ad hoc networks,‖ in Proc. ACM MobiCom Conf., 2000, pp. 255–265. 

  4. G. Noubir and G. Lin, ―Low-power DoS attacks in data wireless lans and countermeasures,‖ ACM SIGMOBILE Mobile Comput. Commun. Rev., vol. 7, no. 3, pp. 29–30, Jul. 2003. 

  5. V. N. Padmanabhan and D. R. Simon, ―Secure traceroute to detect faulty or malicious routing,‖ in Proc. ACM SIGCOMM Conf., 2003, pp. 77–82. 

  6. P. Papadimitratos and Z. Haas, ―Secure message transmission in mobile ad hoc networks,‖ Ad Hoc Netw., vol. 1, no. 1, pp. 193–209, 2003.  A. Proano and L. Lazos, ―Selective jamming attacks in wireless networks,‖ in Proc.
    IEEE ICC Conf., 2010, pp. 1–6.

  7.  A. Proano and L. Lazos, ―Packet-hiding methods for preventing selective jamming attacks,‖ IEEE Trans. Depend. 1, pp. 101– 114, Jan./Feb.2012. 
     

Abeyance Conscious Ipv6 Package Delivery System Over Ieee 802.15.4 Based Battery-Free Wireless Sensor Networks
R.SUPRIYA,
Pages: 69-76 | First Published: 05 Feb 2017
Full text | Abstract | Purchase | References | Request permissions

Abstract 
We consider a complex (i.e., nonlinear)  road scenario where users aboard vehicles equipped with communication interfaces are interested in downloading large files from road-side Access Points (APs). We investigate the possibility of exploiting opportunistic encounters among mobile nodes so to augment the transfer rate experienced by vehicular downloader’s. To that end, we devise solutions for the selection of carriers and data chunks at the APs, and evaluate them in real-world road topologies, under different AP deployment strategies. Through extensive simulations, we show that carry & forward transfers can significantly increase the download
rate of vehicular users in urban/suburban environments, and that such a result holds throughout diverse mobility scenarios, AP placements and network loads.
Keywords: APs; Mobility Scenarios; Forward Transfer; Topologies; Chunk 

References

  1. Y. Yang, L. Su, Y. Gao, T.F.  Abdelzaher, “SolarCode: Utilizing Erasure Codes for Reliable Data Delivery in Solar-powered Wireless Sensor Networks,” 2010 Proceedings IEEE INFOCOM, 2010, pp.1-5. 

  2. M. Y. Naderi, P. Nintanavongsa, K. R. Chowdhury, “RF-MAC: A Medium Access Control Protocol for ReChargeable Sensor Networks Powered by Wireless Energy Harvesting,” IEEE Transactions on Wireless
    Communications, vol. 13, no. 7, pp. 3926 C 3937, 2014.

  3.  V. Liu, A. Parks, V. Talla, S. Gollakota, D. Wether all, and J. R.Smith, “Ambient Backscatter: Wireless Communication Out of Thin Air,”SIGCOMM ’13: Proceedings of the ACM SIGCOMM 2013 conference
    on SIGCOMM, August 12-16, 2013, Hong Kong, China, pp. 39-50. 

  4. P. C. Jain, “Recent Trends in Energy Harvesting for Green Wireless Sensor Networks,” International Conference on Signal Processing and Communication (ICSC), 2015, Noida, pp. 40-45. 

  5. R. Gomez Cid-Fuentes, A. Cabellos Aparicio, E. Alarcon, “Energy Buffer Dimensioning Through EnergyErlangs
    in Spatio-Temporal-Correlated Energy-Harvesting-Enabled Wireless Sensor Networks,” IEEE Journal on
    Emerging and Selected Topics in Circuits and Systems, vol. 4, no. 3, 2014,pp. 301-312.

  6.  W. K. G. Seah, E. Z. Ang, and H. Tan, “Wireless sensor networks powered by ambient energy harvesting (WSNHEAP) - Survey and challenges,” 1st International Conference on Wireless Communication, Vehicular
    Technology, Information Theory and Aerospace & Electronic Systems Technology, 2009, Wireless VITAE
    2009, pp. 1-5.  

  7. Y.-H. Zhu, S. Luan, V. C. M. Leung, and K. Chi, “Enhancing Timer based Power Management to Support DelayI nto lerant Uplink Traffic in Infrastructure IEEE 802.11 WLANs,” IEEE Transactions on Vehicular
    Technology, vol. 64, no. 1, pp. 386399, 2015.

  8. H. Ma, L. Liu, A. Zhou, and D. Zhao, “On Networking of Internet of Things: Explorations and Challenges,” IEEE
    Internet of Things Journal, DOI:10.1109/JIOT.2015.2493082,2015.

Mining Cryptography Using Enhanced Apriori Algorithm
A.ASHA
Pages: 77- 82 | First Published: 05 Feb 2017
Full text | Abstract | Purchase | References | Request permissions

Abstract
Developers use cryptographic primitives like block ciphers and message authenticate codes (MACs) to secure data and communications. Cryptographers know there is a right way and a wrong way to use these primitives, where the right way provides strong security guarantees and the wrong way invariably leads to trouble. This work analyzes cryptography misuse by software developers, from their contributions to online forums on cryptography-based security and cryptographic programming. Over the last few years, researchers proposed a multitude of automated bug-detection approaches that mine a class of bugs that we call API misuses. We also found that cryptographic bad practices frequently occur in pairs or triples. We related triple associations to use cases and tasks, characterizing worst case scenarios of cryptography misuse. In this paper, we proposed to design a modernized misuse detection System which consist method to find misuse detection. Our system proposed to find pattern of cryptography strength, which is profiled using an algorithm called Enhanced  Apriori Algorithm.
Keywords: MACs; Cryptography; Apriori Algorithm; Bug-Detection; API Misuses;
 

References

  1. Ye Changguo , “The Research on the Application of Association Rules Mining Algorithm in NetworkIntrusion Detection” Transactions on Software Engineering, IEEECommunicationMagazine. 

  2. 2. Aly Ei-Semary, Janica Edmonds, Jesus Gonzalez-Pino, Mauricio Papa, “Applying Data Mining of Fuzzy Association Rules to Network Intrusion Detection”, in the Proceedings of Workshop on Information Assurance United States Military Academy 2006, IEEE Communication Magazine, West Point, Y,DOI:10.1109/IAW.2006/652083. 

  3. Amir Azimi, Alasti, Ahrabi, Ahmad Habibizad Navin, Hadi Bahrbegi, “A New System for Clustering &
    Classification of Intrusion Detection System Alerts Using SOM”, International Journal of Computer
    Science & Security, Vol: 4, Issue: 6, pp-589-597, 2011. 

  4. Anderson.J.P, “Computer Security Threat Monitoring & Surveilance”, Technical Report, James P Anderson
    co., Fort Washington, Pennsylvania, 1980. 

  5. Denning .D.E, ”An Intrusion Detection Model”, Transactions on Software Engineering, IEEE Communication
    Magazine, 1987,SE-13, PP-222232,DOI:10.1109/TSE.1987.232894.

  6. Dewan Md, Farid, Mohammed Zahidur Rahman, “Anomaly Network Intrusion Detection Based on Improved Self Adaptive Bayesian Algorithm”, Journal of Computers, Vol 5, pp-23-31, Jan 2010, DOI:10.4.304/jcp 5.1.

  7. Jake Ryan, Meng - Jang Lin, Risto Miikkulainen,”Intrusion Detection With Neural Networks”, Advances in
    Neural Information Processing System 10, Cambridge, MA:MIT Press,1998,DOI:10.1.1.31.3570. 

  8. Jin-Ling Zhao, Jiu-fen Zhao ,Jian-Jun Li, “Intrusion Detection Based on Clustering Genetic Algorithm”, in
    Proceedings of International Conference on Machine Learning & Cybernetics (ICML), 2005, IEEE Communication Magazine,ISBN:07803-9091DOI:10.1109/ICML.2005.1527621.

  9. Norouzian.M.R, Merati.S, “Classifying Attacks in a Network Intrusion Detection System Based on Artificial
    Neural Networks”, in the Proceedings of 13th International Conference on
    Advanced Communication Technology (ICACT), 2011, ISBN:978-1-42448830-8, pp-868-873.

 

Load Balancing using Resource Utilization for Cloud Computing
M.MONIKA
Pages: 83-88 | First Published: 05 Feb 2017
Full text | Abstract | Purchase | References | Request permissions

Abstract
Load balancing is a technique that distributes the excess dynamic local workload evenly across all the nodes. It is
used for achieving a better service provisioning and resource utilization ratio, hence improving the overall performance of the system Incoming tasks are coming from different location are received by the load balancer and then distributed to the data center ,for the proper load distribution. The aim of our project is as
follows: To increase the availability of services, To increase the, user satisfaction, To maximize resource utilization. To reduce the execution time and waiting time of task coming from different location. To improve the performance, Maintain system stability, Build fault tolerance system, Accommodate future modification, Avoid overloading of virtual machine. With the demand in Cloud Computing industry, the cloud service providers attracts customers with various demands. The diverse price scheme safeguards the discount pricing strategy from the market of Cloud brokers. The Cloud brokers take the full advantage of Cloud service providers. The cloud service providers helps every customers to utilize discount pricing strategy offered through online schedule.
Keywords: Cloud Computing; Cloud Brokers; Virtual Machine; Fault Tolerance System; Utilization Ratio;
 

References

  1. Alibaba cloud computing [online].  available :http://www.aliyun.com/,apr 2015. 

  2. Amazon. Amazon elastic compute cloud (amazon ec2) [online]. available: http://aws.amazon/cn/ec2/,apr 2015. 

  3. L. Andrew, A. Wireman, and A. Tang,“Optimal speed scaling under arbitrary power functions”, ACM 
    SIGMETRI CS perform. 

  4. Apache. Apache hadoop [Online]. Available: http://hadoop.apache.org/, Apr. 2015. 

  5. 5. N. Bansal, H. Chan, and K. Pruhs, “Speed scaling with an arbitrary power function,” in Proc. 20th Annu. ACMSIAM Symp.

  6. . Chang, H. Gabow, and S. Khuller, “A model for minimizing active processor time,” in Proc. 20th Annu.
    Eur. Symp., 2012. 

  7. N. Gohring. Confirmed: Cloud infrastructure pricing is absurd  [Online]. Available: http://www.itworld.com/cloudcomputing/387149/confirmed-cloudiaas-pricing-absurd, Apr. 2015.

  8. G. Guisewite and P. Pardalos, “Algorithms for the single-source uncapacitated minimum concave-cost
    network flow problem,” J.Global Optim., vol. 1, no. 3, ppt. 

  9. Jian Li,Barna  Saha  and Samir Khuller Energy efficient scheduling via partial shutdown 2015. 

  10. Shivangi goyal A computing study of cloud computing services providers 2012. 

The Impact of Work Environment and Job Satisfaction With Special Reference to Public and Private Sectors Banking Employees in Chennai
Mrs.N.SUMATHY
Pages: 89-94 | First Published: 05 Feb 2017
Full text | Abstract | Purchase | References | Request permissions

Abstract
This study details with impact of work environment and job satisfaction” The main objective of the study are to know the attitude of employees towards the work environment and to find out the various factors that affect the work environment. The Employee satisfaction regarding various aspects of the job is also determined. The research design adapted in this study was descriptive. The nature of the study carried out is census survey in
which the entire population of banking employees in Chennai is considered. The population size of is 150.The
Questionnaire is distributed to all the employees of public and private sectors banks. The main tool employed in
collecting the primary data is through framing a structured questionnaire. The Statistical tools used in this study are Percentage analysis, Pearson‟s correlation, weighted average method, Chi-square test. This study concentrates on finding the physiological factors in work environment and satisfaction level of employees towards various aspects of job. Suggestions are given to improve the work environment and to overcome the
difficulties faced by employees in work. 
 

References

  1. Arun monappa “industrial relations”, thirty seventh revised edition 2010.

  2.  Human Resource Management Practice Kogan Page Publishers, 2006.  

  3. Robert L.Mathis John H.Jackson,”Human Resource Management” Thirteenth Edition 

  4. S.P.GUPTA, “Statistical Methods”, Thirty-Third Revised Edition 2004, published by Sultan Chand &Sons.

  5. C.R.KOTHARI., “Research Methodology”, method and techniques, second revised edition 2004, new age International (p) Limited. 

  6. "Workplace spirituality and employee work attitudes: An exploratory empirical assessment", Journal of Organizational Change Management, Vol. 16 Iss: 4, pp.426 – 447.

  7. The International Journal of Human Resource Management, Apr 2007, Volume: 18 Issue: 4 pp.537-567 (31 pages).

  8.  Employee attitude and job satisfaction, Winter 2004, Vol. 43, No. 4, Pp. 395–407 2004.  

Exploratory Factor Analysis on Investors Decision Making Criteria on Intra-Day Trading
Ms.P.MALATHI
Pages: 95-`103 | First Published: 05 Feb 2017
Full text | Abstract | Purchase | References | Request permissions

Abstract
Day trading also called Intra-day trading is perhaps the most well known active trading style in the growing stock market. Day trading, as its name implies, is the method of buying and selling securities within the same day. Positions are closed out within the same day they are taken, and no position is held overnight. Traditionally, day trading is done by professional traders, such as specialists or market makers. However, electronic trading has opened up this practice to beginner traders. there are many criteria considered by the investors before picking
stock for intra-day trading. this study to identify the factors involve in decision criteria in intra-day trading. 
Keywords: Intra-day trading, Stock , Investor, Stock Market



 

References 

  1.  Blume, M.E and Friend, I. (1978), The Changing Role of the Individual Investor: A Twentieth Century Fund
    Report, Wiley, New York, NY,.

  2. Carter, R.B and Van Auken, H.E. (1990), "Security analysis and portfolio management: a survey and analysis",
    Journal of Portfolio Management, Vol. 16 No.1, pp.81-5. 

  3. Chenhall, R.H and Juchau, R. (1977), "Investors information needs: an Australian. 

  4.  Hussein, A.H. (2007) Factors influencing individual investor behaviour in the UAE financial markets. Journal of
    Business, Vol.92. 

  5. Nagy and Obenberger, (1994) “Factors influencing investor behavior”, Financial Analysts Journal, Vol.50. 

  6. Potter, R.E. (1971), "An empirical study of motivations of common stock investors", Southern Journal of Business, Vol. 6 No.1, pp.41-4.