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Development of Control Strategies and Implementation to Electrical Water Heaters for Energy Conservation

References 1. Kar, A. K., U. Kar. Optimum Design and Selection of Residential Storage Type Electric Water Heaters for Energy Conservation, Energy Convers. - Mgmt, Vol. 66, 1996, pp. 12-24. 2. Flossl, A., S. Hofmann. - Energy and Buildings, Vol. 100, 2015, pp. 10-15. 3. Kreuzinger, T., M. Bitzer, W. Marquardt. State Estimation ofa Stratified Storage Tank. - Control Engineering Practice, Vol. 16, 2008, pp. 308-320. 4. Becker, B. R., K. E. Stogsdill. A Domestic Hot Water Use Database. - ASHRAE

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Reasoning with Computer Code: a new Mathematical Logic


A logic is a mathematical model of knowledge used to study how we reason, how we describe the world, and how we infer the conclusions that determine our behavior. The logic presented here is natural. It has been experimentally observed, not designed. It represents knowledge as a causal set, includes a new type of inference based on the minimization of an action functional, and generates its own semantics, making it unnecessary to prescribe one. This logic is suitable for high-level reasoning with computer code, including tasks such as self-programming, objectoriented analysis, refactoring, systems integration, code reuse, and automated programming from sensor-acquired data.

A strong theoretical foundation exists for the new logic. The inference derives laws of conservation from the permutation symmetry of the causal set, and calculates the corresponding conserved quantities. The association between symmetries and conservation laws is a fundamental and well-known law of nature and a general principle in modern theoretical Physics. The conserved quantities take the form of a nested hierarchy of invariant partitions of the given set. The logic associates elements of the set and binds them together to form the levels of the hierarchy. It is conjectured that the hierarchy corresponds to the invariant representations that the brain is known to generate. The hierarchies also represent fully object-oriented, self-generated code, that can be directly compiled and executed (when a compiler becomes available), or translated to a suitable programming language.

The approach is constructivist because all entities are constructed bottom-up, with the fundamental principles of nature being at the bottom, and their existence is proved by construction.

The new logic is mathematically introduced and later discussed in the context of transformations of algorithms and computer programs. We discuss what a full self-programming capability would really mean. We argue that self-programming and the fundamental question about the origin of algorithms are inextricably linked. We discuss previously published, fully automated applications to self-programming, and present a virtual machine that supports the logic, an algorithm that allows for the virtual machine to be simulated on a digital computer, and a fully explained neural network implementation of the algorithm.

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Evolutionary Computing Based on QoS Oriented Energy Efficient VM Consolidation Scheme for Large Scale Cloud Data Centers


The high pace and increase in cloud computing technology and associated applications, especially large scale data centres, have demanded energy efficient and Quality of Service (QoS) oriented computing platform. To meet these requirements, virtualization and Virtual Machine (VM) consolidation has emerged as an effective solution. The optimization in VM consolidation by means of efficient dynamic resource-utilization prediction, VM selection and placement can achieve optimal solution for energy efficient and QoS oriented cloud computing system. In this paper, an evolutionary computing algorithm called Adaptive Genetic Algorithm (A-GA) based VM consolidation approach has been developed. A-GA based placement policy and its implementation with different VM selection policies like Minimum Migration Time (MMT), Maximum Correlation (MC) and Random Selection (RS), along with different CPU utilization estimation approaches like Inter Quartile Range (IQR), Local Regression (LR), Local Robust Regression (LRR), static THReshold (THR) and Median Absolute Deviation (MAD) has revealed that A-GA based consolidation with MMT selection policy and combined IQR and LRR can enable optimal VM consolidation for large scale infrastructures. In addition, the proposed A-GA policy has exhibited better performance as compared to other meta-heuristics such as Ant Colony Optimization (ACO) and Best Fit Decreasing. The proposed consolidation system can be used for large scale cloud infrastructures where energy conservation, minimal Service Level Agreement (SLA) violation and QoS assurance is inevitable.

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E-Braille Documents: Novel Method For Error Free Generation

, 9(9), 81–85 [5] Supriya, S., Senthilkumar, A. (2009). Electronic Braille pad. In Control, Automation, Communication and Energy Conservation, 2009. INCACEC 2009. International Conference on IEEE. 1–5 [6] Wajid, M., Abdullah, M.W., Farooq, O. (2011). Imprinted Braille-character pattern recognition using image processing techniques. In Image Information Processing (ICIIP), 2011 International Conference on IEEE. 1–5

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Chaotic behavior of the lattice Yang-Mills on CUDA

, Numerical Recipies in C , Cambridge University Press, 2002. ⇒217, 225 [12] L. E. Reichl, The Transition to Chaos , Springer-Verlag, 1992. ⇒221 [13] S. Weinberg, The Quantum Theory of Fields , Cambridge University Press CB2 1RP, 1996 ⇒217 [14] C. N. Yang, R. Mills, Conservation of isotropic spin and isotopic gauge invariance, Phys. Rev. 96 (1954) 191–195. ⇒218 [15] CUDA C Programming Guide NVIDIA Corp., 2013, . ⇒232 [16] Technology Insight: Intel Next Generation

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A Multi Route Rank Based Routing Protocol for Industrial Wireless Mesh Sensor Networks

References 1. Akyildiz, I. F., W. Su, Y. Sankarasubramaniam, E. Cayirc. Wireless Sensor Networks: A Survey. - Elsevier Journal of Computer Networks, Vol. 38, 2002, No 4, pp. 393-422. 2. Römer, K., F. Mattern. The Design Space of Wireless Sensor Networks. - IEEE Wireless Communications, Vol. 11, 2004, No 6, pp. 54-61. 3. Anastasi, G., M. Conti, M. D. Francesco, A. Passarella. Energy Conservation in Wireless Sensor Networks: A Survey. - Elsevier Journal of Ad Hoc Networks, Vol. 7, 2009, No 3, pp. 537

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Business Intelligence System via Group Decision Making

Water Network. Resources. - Conservation and Recycling, Vol. 52, 2007, pp. 441-459. 13. Morais, D. C., A. T. Almeida. Group Decision Support System Based on PROMETHEE Integrated with Problem Structuring Approach. - Group Decision and Negotiation, Stockholm, Sweden, 2013, pp. 17-20. 14. Mustakerov, I., D. Borissova. A Combinatorial Optimization Ranking Algorithm for Reasonable Decision Making. - Comptes Rendus de l’Academie Bulgare des Sciences, Vol. 66, 2013, No 1, pp. 101-110. 15. Mustakerov, I., D. Borissova. A Web

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Method for Balancing Energy through the Mobility of Node Agent in Mobile Sensor Network

REFERENCES [1] S. Basagni, A. Carosi, C. Petrioli, “Controlled Vs. Uncontrolled Mobility in Wireless Sensor Networks: Some Performance Insights,” Vehicular Technology Conference , 2007. VTC-2007 Fall. 2007 IEEE 66th. 2007. pp. 269–273. [2] D.M. Blough, P. Santi, “Investigating upper bounds on network lifetime extension for cell-based energy conservation techniques in stationary ad hoc networks,” Proc. of the 8th annual int. conf. on Mobile computing and networking. MobiCom ’02 . New York, NY, USA: ACM, 2002

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Group Decision Analysis with Interval Type-2 Fuzzy Numbers

References 1. Bouzon, M., K. Govindan, C. Rodriguez. Evaluating Barriers for Reverse Logistics Implementation undera Multiple Stakeholders’ Perspective Analysis Using Grey Decision Making Approach. Resources. - Conservation and Recycling, 2017, Science Direct (in Press). 2. Büyüközkan, G., S. Güleryüz. An Integrated DEMATEL-ANP Approach for Renewable Energy Resources Selection in Turkey. - Production Economics. Vol. 182, 2016, pp. 435-448. 3. Chen, Y. C., Lien, H. P. Lien, G. H. Tzeng. Measures and Evaluation

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Black-box Brain Experiments, Causal Mathematical Logic, and the Thermodynamics of Intelligence

:// Pissanetzky, S. 2012h. The theory of Detailed Dynamics and the Combinatorial Explosion. Available electronically at Pissanetzky, S. 2013. The unification of symmetry and conservation. Bulletin of the American Physical Society 58(3):N2.0001. Available electronically from Wallace, D. 2013. Thermodynamics as control theory. Available electronically at Wissner

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