The most intuitive form of description of the world for people is natural language. Situations, relationships, real or abstract objects are assigned to expressions (words, phrases), by which they distinguish between them. The advantage of natural language is the ability to describe the object for which we do not know the exact phrase, by combining familiar words. We tend to use native language to describe world around us. But what happens when we try to extract information from the written sources? We soon realise that we need to identify the context based on relationships between the written expressions. This paper considers using ontology for knowledge interpretation.

Keywords: Descriptive logic, knowledge, knowledgebase, ontology.

[1]. Gruber, 1992. [Online]. Available: http://www-ksl.stanford.edu/kst/what-is-an-ontology.html.
[2]. M. O bitko, "Introduction to Ontologies and Semantic Web," 2006 2007. [Online]. Available: http://www.obitko.com/tutorials/ontologies semantic web/description logics.html). [Cit. 14 10 2013]
[3]. H. H. T. Z. V. M. Lukasová A., Formální reprezentace znalostí, O strava: Ostravská univerzita v Ostravě, 2010.
[4]. S. D. Maniraj V., "Ontology Languages A Review," International Journal of Computer Theory and Engineering, zv. Vol.2, %1. vyd.No.6, 2010.
[5]. "Semantic Web,"W3C, [Online]. Available: http://www.w3.org/standards/semanticweb/. [Cit. 14 10 2013].

Over the past decade due to increasing the population Overcrowding in emergency care unit (CU) departments is a problem in many countries. This overcrowding which leads reduces the quality of care and increases medical errors. Generally predicting the transition processes of patients (PFP) is more difficult and crucial process. The field of data mining has involved in those domains to predict Patient Flow effectively. The previous studies have used several features to predict Patient Flow, which has been collected from patient‟s hospital data. The main drawbacks of the previous studies are that need accurate and more number of features to effectively predict the patient flow and this system can only apply in discrete time series................

Keywords: Patient Flow, Machine Learning, DCM.

[1]. Dr. Kasthuri, Sreejith. R. "Using Mutually-Correcting Nonparametric Model to Predict and Classify of Patient Data". JNCET, February 2018.
[2]. Díez-Pastor, José F., Juan J. Rodríguez, César García-Osorio, and Ludmila I. Kuncheva. "Imbalanced data using Ensembles of variable prior‟s classifiers: Random balance." Knowledge-Based Systems 85 (2015):
[3]. Faten Ajmi, Sarah Ben Othman, Hayfa Zgaya Biau, Slim Hammadi. "Identifying Overcrowding Indicators by using Patient Pathway Workflow Model in Emergency Department". ICCS (2): 540-552, Jun 2018.
[4]. Maratea, Antonio, Alfredo Petrosino, and Mario Manzo. "Imbalanced data learning by using Adjusted F-measure and kernel scaling" Information Sciences 257: 331-341, (2014).
[5]. Wang, Yichen, Robert Chen, Joydeep Ghosh, Joshua C. Denny, Abel Kho, You Chen, Bradley A. Malin, and Jimeng Sun. "Health data analytics is using the Knowledge guided tensor factorization and completion: Rubik." In Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1265-1274. ACM, 2015.

Stone column technique is proven to be the most suitable ground improvement technique for improving the soft soils. Out of other methods, stone columns technique is the most effective method for flexible structures like embankments, oil storage tanks etc. Soft soils stabilized with stone columns can be further improved by reinforcing the column with any geosynthetic material. In this study, Silica-Manganese slag mixed with Sand was used as the stone column material to improve the soft marine clay and geotextile material was used to reinforce the stone columns. This geotextile was made into circular discs and placed within the stone column horizontally at a spacing of 50mm (equal tothe diameter "D" of the stone column). The results indicate that the soft soil can be improved with the stone column and can be further stabilized with the geotextile reinforcement.

Keywords: Load carrying capacity, Marine soil, Sand, Silica-Manganese slag, Stone column.

[1]. D.A. Greenwood, Mechanical Improvement of soils below ground surface, Conference on Ground Engineering, Institution of Civil Engineers, London, 1970, 11-22.
[2]. K. Deb, N.K. Samadhiya, J.B. Namdeo,Laboratory model studies on unreinforced and geogridreinforced sand bed over stone column-improved soft clay,Geotextiles and Geomembranes, 29(2), 2010, 190-196.
[3]. A.P. Ambily,and S.R. Gandhi,Behaviour of Stone Columns Based on Experimental and FEM Analysis,Journal of Geotechnical and Geoenvironmental Engineering, ASCE, 133(4), 2007, 405-515.
[4]. Y.K. Tandel, C.H. Solanki and A.K. Desai, Reinforced stone column: remedial of ordinary stone column, International Journal of Advances in Engineering & Technology, 3(2), 2012,340-348.
[5]. R. Sharma, B.R. Phani Kumar,and G. Nagerdra,"Compressive load response of granular piles reinforced with geogrids, Canadian Geotechnical Journal, 41(1), 2011, 187-192.

Cloud computing provides promising scalable dynamic infrastructure to maintain various processing of a variety of big data real time applications in sectors such as healthcare and business and other area. Data sets like electronic health records in such applications often contain privacy-sensitive information, which brings about privacy concerns potentially shared to third-parties in cloud. Privacy-preserving data mining (PPDM) refers seeks to preserve sensitive information from unsolicited or unsanctioned disclosure. Protecting the individual privacy within the sensitive data is becoming a prominent research focus data in big data environment. Local-Recoding Anonymization plays major role in privacy preservation. Data anonymization refers to hiding identity of sensitive data so that the privacy of an individual is effectively preserved. Most of the existing privacy model fails to maintain effective privacy Preservation due to their insufficiency or poor scalability..............

Keywords: Big data analytics, Machine Learning, Healthcare, Disease Detection, Medical Data Analytics.

[1]. Ashwin Machanavajjhala, Johannes Gehrke, Daniel Kifer, Muthuramakrishnan, Venkitasubramaniam. "l-diversity: Privacy Beyond k-anonymity". Proceedings of the 22nd International Conference on Data Engineering (ICDE‟06). (2006).
[2]. Gagan Aggarwal, Tomas Feder, Krishnaram Kenthapadi, Samir Khuller, Rina Panigrahy, Dilys Thomas, An Zhu. "Achieving Anonymity via Clustering". Encyclopedia of Database Systems. Springer, Boston, MA. 2136-2137. (2009).
[3]. Jian Xu, Wei Wang, Jian Pei, Xiaoyuan Wang, Baile Shi, Ada Wai-Chee Fu. " utility-based anonymization using local recoding". Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2006.
[4]. Ji-Won Byun, Ashish Kamra, Elisa Bertino, and Ninghui Li. "Efficient k-Anonymization Using Clustering Techniques". International Conference on Database Systems for Advanced Applications. Springer, Berlin, Heidelberg, 2007. [5]. Kristen LeFevre, DeWitt D J, Raghu Ramakrishnan. "Mondrian Multidimensional K-anonymity". Data Engineering, 2006. ICDE'06. Proceedings of the 22nd International Conference on. IEEE, 2006.

Graph Processing System (GPS) is one of the open-source systems. It gives the advantages like scalability, fault-tolerance and easy program execution. The GPS is similar to the Google's proprietary systems such as pregel and apache giraph.Therefore, memory usage patterns emerge as a primaryconcern in distributed graph processing.Obtainingeffective memory optimization in vertex-centric distributed environment is critical and most of the existing research failed to obtain it. In existing system, the field of data mining has involved in those domains to optimize thememory in Distributed Graph Processing.Those techniques cannot achieve high optimization and this technique cannot apply for Real-World Graphsanalytics. The study proposes a Sequence Single-source Shortest Paths along with Enhanced RedBlackTreeEdgesdata mining framework andCBIIMframework to improve the Memory Optimization in Distributed Graph Processing.

Keywords : Distributed Graph Processing, Graph Compression, Pregel, Apache Giraph, Memory Optimization, GraphX.

[1]. Gonzalez J E, Y. Low, Gu H, Bickson D, and Guestrin C, "PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs," in Proc. of the 10th USENIX Symposium on Operating Systems Design and Implementation, Hollywood, CA, USA, October 8-10, pp. 17–30.(2012)
[2]. Han M and Daudjee K, "Giraph Unchained: Barrierless Asynchronous Parallel Execution in Pregel-like Graph Processing Systems," Proc. VLDB Endow., vol. 8, no. 9, pp. 950–961, (May 2015).
[3]. Low Y, Gonzalez J, Kyrola A, Bickson D, Guestrin C, and Hellerstein J M, "Distributed GraphLab: A Framework for Machine Learning in the Cloud," Proc. of the VLDB Endowment, vol. 5, no. 8, pp. 716–727. (2012)
[4]. Malewicz G, Austern M H,Bik A J C, Dehnert J C, Horn I, Leiser N, and Czajkowski G, "Pregel: A System for Large-Scale Graph Processing," in Proc. of the ACM SIGMOD Int. Conf. on Management of Data, Indianapolis, Indiana, USA, June 6-10, pp. 135–146.(2010).

Total Quality Management (TQM) has an important role in any company, since its implementation can continuously improve company's performance. The general purpose of this study was to investigate the concept and level of implementation of total quality management in small and medium scale construction firms in south- east Nigeria. The sample size of 328 respondents from small and medium scale construction firms was adopted for this study. They completed a questionnaire covering ten critical success factors of total quality management namely: Leadership and top management commitment and leadership, Customer Focus, continuous improvement, employee participation, Recognition and Award, Training, Quality culture, communication, performance measurement and strategic planning.............

KEYWORDS: Total Quality Management, Small and medium scale construction firms, south-east, Quality, Implementation

[1]. L. Mendes, Proceedings of the 4th World Conference for International council for Small Business; Quality and the relationship SME's / Supplier: The experience of two Portuguese SME, held in San Juan, Puerto Rico 16-19, 2002
[2]. N. Chileshe and P.A.Watson, Investigating the rationale for pursuing total Quality Management (TQM) as a valid Competitive Strategy For SME's in proceedings of the 2nd Southern African Conference on Sustainable Development in the Built Environment, 23-25 Aug, 2000 Pretoria, South Africa.
[3]. G.I, Idoro, G. I, Influence of quality performance on clients' patronage of indigenous and expatriate construction contractors in Nigeria. Journal of Civil Engineering and Management, 16(1), 2010, 65–73.
[4]. G. Ofori, G, Small and Medium Sized Construction Enterprise Development. Construction for Development. (ISIZA). 1st Quarter 2009.
[5]. A.Abdullah, A.A. Bilau, W.I. Enegbuma, A.M.Ajagbe, K.N. Ali and S.A. Bustani, Small and Medium Sized Construction Firms Job Satisfaction and Evaluation in Nigeria. International Journal of Social Science and Humanity, 2(1), 2012, 35-40.

The influence of foliar fertilizing with organic fertilizers on the yield of two pepper cultivars grown in protected spaces in Strumica region was examined. The experiment was set in four variants and three repetitions for each cultivar separately. The variants in the experiment were: Control (untreated); NPK+Ever green (55% organic matter, 2%w/w Mg, 2%w/w Fe, 2%w/w Zn, 2% w/w Mn, 0.5 %w/w Cu, 0.5 %w/w B); NPK+Biolinfa (34% organic matter, 3 %N, 5.80 % K2O); NPK+Oligomix (1.20 % B, 0.10 % Cu, 4 % Fe, 1.50 % Mn, 0.10 % Mo, 2 % Zn)..............

Keywords - foliar fertilizing, peppers, yield.

[1]. Bogdanović, M., Velkonija, N., Racz, Z. (1966). Chemical methods of soil analysis. Book I, sine loco. 44,162,184,189.
[2]. Datnoff, L.E., Elmer, W.H., Huber, D. M. (2007). Mineral nutrition and plant disease, American Phytopathological Society, St Paul, M. N. (278), (89-93).
[3]. Domagalski, J.L., Ator, S., Coupe, R. (2008). Comparative study of transport processes of nitrogen, phosphorus and herbicides to streams in five agricultural basins, USA. J Environ Qual, Vol. 37 (1158), (69-72).
[4]. Dzamič, R., Stevanović, D. (2000). Agrochemistry, Faculty of agriculture, Belgrade.
[5]. El-Bassiony, A.M., Fawzy, Z.F., Abd El-Samad, E.H., Riad, G.S. (2010). Growth, Yield and Fruit Quality of Sweet Pepper Plants (Capsicum annuum L.) as Affected by Potassium Fertilization. Journal of American Science, 6(12); Vegetables Crop Research Dept., National Research Centre, Dokki, Cairo, Egypt (125-131).

In the current study, an investigation made on fabrication of 63 micron B4C particles reinforced Al2618 alloy composites and evaluation of mechanical properties. Al2618-2 and 4 wt. % of B4C composites were synthesized by liquid stir casting process. Microstructural characterization was carried out by using scanning electron microscope and energy dispersive spectroscope. Prepared composites were evaluated for mechanical properties as per ASTM standards. Scanning electron micro photographs revealed the distribution of B4C particulates in the Al matrix and were confirmed by EDS analysis. Further, B4C particulates reinforced composites were shown more enhanced hardness, ultimate tensile strength and yield strength as compared to Al2618 alloy. Ductility of Al2618 alloy was decreased with addition hard ceramic particles.

Keywords - Al2618 Alloy, B4C particulates, Microstructure, Hardness, Tensile Strength.

[1]. T. Hariprasad, K. Varatharajan and S. Ravi, "Wear characteristics of B4C and Al2O3 reinforced with Al 5083 metal matrix based hybrid composites", Procedia Engineering, 97, pp. 925-929, 2014.
[2]. Narayana Yuvaraj, Sivanandan Aravindan and Vipin, "Fabrication of Al5083/B4C surface composite by friction stir processing and its tribological characterization", Journal of Materials Research and Technology, 4 (4), pp. 398-410, 2015.
[3]. Gurdial Blugan et al., "Si3N4-TiN-SiC three particle phase composites for wear applications", Ceramics International, 40, pp. 1439-1446, 2014.
[4]. M. Khakbiz and F. Akhlaghi, "Synthesis and structural characterization of Al-B4C nano composite powders by mechanical alloying", Journal of Alloys and Compounds, 479, pp. 334-341, 2009.
[5]. Syed Nasimul Alam and Lailesh Kumar, "Mechanical properties of aluminium based metal matrix composites reinforced with graphite nanoplatelets", Materials Science & Engineering A, pp. 16-32, 2016.

This paper presents the method binding statistical and data mining techniques, which aims to sup-port the decision-making process in selected diseases in digestive systems. Currently, there is no precise diagno-sis for these two diseases: ulcerative colitis (UC) and Crohn's disease (CD). Specialist physicians must exclude many other diseases occurring in the colon. The first goal of this study is a retrospective analysis of medical data of patients hospitalized in the Department of Gastroenterology and Internal Diseases and finding the symptoms differentiating the two analyzed diseases. The second goal is to build a system that clearly points to one of the diseases UC or CD, which shortens the time of diagnosis and facilitates the future treatment of patients. The work focuses on building a model that can be the basis for the construction of classifiers, which are one of the basic elements in the medical recommendation system.

Keywords - Colon disease, decision system, information system, action rule, statistical methods.

[1]. Agrawal R., Srikant R. (1993),Fast algorithm for mining assocation rules, International Conference on Very Large Databases, 487-499.
[2]. Crohn B.B., Ginzburg L., Oppenheimer G.D. 1932, Regional ileitis. A pathologic and clinical entity, J Am Med Ass. 99:1323-1329.
[3]. Dardzinska A. (2013), Action Rules Mining. Springer, pp.90.
[4]. Dardzinska A., Romaniuk A. (2016), Mining of Frequent Action Rules, Machine Intelligence and Big Data in Industry: 6th International Conference on Pattern Recognition and Machine Intelligence, 87-95 .
[5]. Dardzinska A., Kasperczuk A. (2018), Decision-making Process in Colon Disease and Crohn's Disease Treatment, Acta Mechanica et Automatica, Vol. 12 no. 3, pp. 227-231.

This paper proposes a space vector pulse width amplitude modulation (SVPWAM) method for a buck–boost voltage/current source inverter. For a voltage source inverter, the switching loss is reduced by 87%, compared to a conventional sinusoidal pulse width modulation (SPWM) method. For a current source inverter, the switching loss is reduced by 60%. In both cases, the power density is increased by a factor of 2 to 3. In addition, it is also verified that the output harmonic distortions of SVPWAM is lower than SPWM, by only using one-third switching frequency of the latter one. As a result, it is feasible to use SVPWAM to make the buck–boost inverter suitable for applications that require high efficiency, high power density, high temperature, and low cost. Such applications include electric vehicle motor drive or engine starter/alternator.

Keywords - Buck-boost, SVPWAM, switching loss reduction, THD.

[1]. D. M. Divan and G. Skibinski, "Zero-switching-loss inverters for highpower applications," IEEE Trans. Ind. Appl., vol. 25, no. 4, pp. 634–643, Jul./Aug. 1989.
[2]. W. McMurray, "Resonant snubbers with auxiliary switches," IEEE Trans. Ind. Appl., vol. 29, no. 2, pp. 355–362, Mar./Apr. 1993.
[3]. J.-S. Lai, R. W. Young, Sr., G. W. Ott, Jr., J. W. McKeever, and F. Z. Peng, "A delta-configured auxiliary resonant snubber inverter," IEEE Trans. Ind. Appl., vol. 32, no. 3, pp. 518–525, May/Jun. 1996.
[4]. J. S. Kim and S. K. Sul, "New control scheme for ac-dc-ac converter without dc link electrolytic capacitor," in Proc. 24th Annu. IEEE Power Electron. Spec. Conf., Jun. 1993, pp. 300–306.
[5]. K. Rigbers, S. Thomas, U. Boke, and R. W. De Doncker, "Behavior and loss modeling of a three-phase resonant pole inverter operating with 120A˚ double flattop modulation," in Proc. 41st IAS Annu. Meeting IEEE Ind. Appl. Conf., Oct. 8–12, 2006, vol. 4, pp. 1694–1701.

Data mining is applied in almost all type of applications like ecommerce, many business, education and health care, etc. The most famous area of data mining is handling health care datasets. From the numerous health attributes, disease prediction and its risk analysis are performed by effective data mining techniques such as clustering and classification. Detection of heart diseases from patient electronic health records is very dynamic in nature and achieving that is a very promising area of research in now days. From the numerous health data, the proposed system handles popular disease dataset such as heart diseases. In the proposed system IACA algorithm has been proposed to address the active learning problem, and this created with the aim at detecting the object label from a large amount of data.................

[1]. S. Sharmila. "Analysis of heart disease prediction using data mining technique", JCSE, 2017.
[2]. Aqueel Ahmed, Shaikh Abdul Hannan, "Data Mining Techniques to Find Out Heart Diseases: An Overview", International Journal of Innovative Technology and Exploring Engineering (IJITEE), September 2012.
[3]. Ramin Assari, Parham Azimi, Mohammad Reza Taghva. "Heart Disease Diagnosis Using Data Mining Techniques", Int J Econ Manag Sci, ISSN: 2162-6359, Volume 6 • Issue 3 • 1000415,2017.
[4]. Mudasir M Kirmani. "Cardiovascular Disease Prediction Using Data Mining Techniques: A Review". Orient.J. Comp. Sci. and Technol;10(2) ,June, 2017.
[5]. Aditya Methaila, Prince Kansal,Himanshu Arya, Pankaj Kumar. "Early Heart Disease Prediction Using Data Mining Techniques". CCSEIT, DMDB, ICBB, MoWiN, AIAP – 2014.

As compare to fossil fuels solar power is everlasting supply of energy whereas fossil fuels and traditional sources of power are restricted. currently solar power or solar photovoltaic's (PV) gaining a lot of attention of the researchers and market players of this field. Maximum power point tracking (MPPT) is that the optimum answer to extract maximum SPV generated power. MPPT is nothing but the tracking of maximum available power of an SPV system by means of the DC-DC converter. Presently so many methods are available for MPPT operation of solar photovoltaic (SPV). In this paper simulation of SPV along with the Perturb and Observe (P&O) method of MPPT is presented. The mathematical modeling of SPV array and the most popular MPPT technique that is P&O and its implementation is presented in this paper.

[1]. Verma Deepak, Nema Savita,Nema RK, "Implementation of Perturb and Observe Method of Maximum Power Point Tracking in SIMSCAPE/MATLAB" IEEE International Conference on Intelligent Sustainable Systems ICISS 2017
[2]. Chauhan, Anurag, R P Saini, "A review on Integrated Renewable Energy System based power generation for stand-alone applications, Configurations, storage options, sizing methodologies and control," Renewable and Sustainable Energy Reviews 2014,vol. 38,pp. 120-99.
[3]. Sebri, Maamar, Ousama Ben Salha, "On the causal dynamics between economic growth, renewable energy consumption, CO2emissions and trade openness, Fresh evidence from BRICS countries," Renewable and Sustainable Energy Reviews 2014, vol. 39, pp. 23-14.
[4]. International Energy Agency, "Tracking Clean Energy Progress," Paris, France 2014.
[5]. International Energy Agency, "World Energy Investment Outlook - Special Report Paris," France 2014.

The expansion of Internet - connected automation offers a number of previously unimaginable opportunities and applications. The Internet of Things (IoT) is a prominent example. IoT is a network system composed of a number of wired or wireless intelligent sensors and applications. The development of IoT took decades. Cyber - attacks, however, have threatened the IoT since its birth; different threats and attacks can cause serious disasters to the network system without the essential security. This makes the security and management of the IoT security system very important. The proposed architecture can be used to provide security management for an IoT network in detail. Finally, summarize the results of the implementation of the proposed architecture of security functions to achieve efficient and strong IoT security.

Keywords- Internet of things (IoT), security, architecture, threats

[1]. Ovidiu Vermesan, Peter Friess, Internet of Things: Converging Technologies for SmartEnvironments and Integrated Ecosystem. Aalborg, Denmark: River Publishers, 2013.
[2]. Punit Gupta, Jasmeet Chhabra, "IoT Based Smart Home Design Using Power and SecurityManagement," International Conference on Innovation and Challenges in Cyber Security,pp. 6-10, August 2016.
[3]. M.U. Farooq, Muhammad Waseem, Anjum Khairi, Sadia Mazhar, "A Critical Analysis onthe Security Concerns of Internet of Things (IoT)," International Journal of Computer Applications, vol. 111, pp. 1-4, February 2015.
[4]. Ovidiu Vermesan, Peter Friess, Internet of Things from Research and Innovation to MarketDeployment. Aalborg, Denmark: River Publishers, 2014.
[5]. Klaus Finkenzeller, RFID Handbook Fundamental and Applications in Contactless SmartCards, Radio Frequency Identification and Near-Field Communication. Wiltshire, UK: JohnWiley & Sons, 3rd ed., 2010.

In the present study, the shape of the absorber tube of parabolic trough collector is modified and a fin is employed inside the absorber tube to improve the heat transfer. The regular circular absorber tube is replaced with a parabolic absorber tube. The distribution of solar flux over the absorber tube is calculated by using the Monte Carlo ray tracing method. Finite volume approach is used to carry out the thermal analysis and both the method are validated by comparing their results with analytical and experimental results. A comparative study is presented between circular absorber tube and parabolic absorber tube, for the range of Reynolds numbers 0.14x105 to 2.93x105. The maximum gain in the collector efficiency of the parabolic trough collector is found to be 6.2%.

Keywords - Solar thermal energy, CSP, MCRT, FVM, PTC.

[1]. Yogi Goswami, D., Solar Thermal Power Technology: Present Status and Ideas for the Future. Energy Sources, 1998. 20(2): 137-145.
[2]. Ghomrassi, A., H. Mhiri, and P. Bournot, Numerical Study and Optimization of Parabolic Trough Solar Collector Receiver Tube. Journal of Solar Energy Engineering, 2015. 137(5): 051003.
[3]. Cheng, Z.D., Y.L. He, and F.Q. Cui, Numerical study of heat transfer enhancement by unilateral longitudinal vortex generators inside parabolic trough solar receivers. International Journal of Heat and Mass Transfer, 2012. 55(21): 5631-5641.
[4]. Price, H., E. Lüpfert, D. Kearney, E. Zarza, G. Cohen, R. Gee, and R. Mahoney, Advances in Parabolic Trough Solar Power Technology. Journal of Solar Energy Engineering, 2002. 124(2): 109-125.