A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Kumar, J. Ashok
- Optimal Power Dispatch of Photovoltaic Inverters in Residential Distribution Systems
Authors
Source
Programmable Device Circuits and Systems, Vol 8, No 6 (2016), Pagination: 181-184Abstract
Power generated through residential Photovoltaic (Solar panels) and dispatched among residential depends on demand and supply accordingly. It is known that photovoltaic inverter controllers, which are designed to harvest maximum power at unity power factor, cannot address secondary performance objectives such as voltage regulation and network loss minimization. Optimal power flow techniques can be utilized to select which inverters will provide ancillary services and to compute their optimal real and reactive power set points according to well-defined performance criteria and economic objectives.
- A Real-Time Recognition Non-Intrusive Electrical Appliance Monitoring Algorithm for Home Energy Management System
Authors
Source
Biometrics and Bioinformatics, Vol 8, No 6 (2016), Pagination: 134-138Abstract
The concern of energy price hikes and the impact of climate change because of energy generation and usage forms the basis for residential building energy conservation. Existing energy meters do not provide much information about the energy usage of the individual appliance apart from its power rating. The detection of the appliance energy usage will not only help in energy conservation, but also facilitate the Demand Response (DR) market participation as well as being one way of building energy conservation. However, energy usage by individual appliance is quite difficult to estimate. This paper proposes a novel approach: an unsupervised disaggregation method, which is a variant of the Hidden Markov Model (HMM), to detect an appliance and its operation state based on practicable measurable parameters from the household energy meter. Performing experiments in a practical environment validates our proposed method. Our results show that our model can provide appliance detection and power usage information in a non-intrusive manner, which is ideal for enabling power conservation efforts and participation in the demand response market. Data identified by the NILM are very useful for DR implementation. For DR implementation, the NSGA-II-based multi objective in-home power scheduling mechanism autonomously and meta-heuristically schedules monitored and enrolled major household appliances without user intervention. It is based on an analysis of the NILM with historical data with past trends. The experimental results reported in this paper reveal that the proposed advanced HEMS with the NILM assessed in a real-house environment with uncertainties is workable and feasible.
Keywords
Data Fusion, Demand Response (DR), Energy Management System, Nonintrusive Load Monitoring (NILM), Power Scheduling, Smart Grid, Smart House.- Applications for Innovative Internet of Things Using Smart Surveillance System
Authors
Source
Artificial Intelligent Systems and Machine Learning, Vol 8, No 6 (2016), Pagination: 207-211Abstract
In the logistics and supply chain, the traditional supply of goods is based on established agreements between manufacturers and suppliers. Orders are made in advance and tracking is done by various stakeholders in the supply chain, i.e., assembly lines, manufacturers and logistics managers. With the use of smart technologies such as active RFID (executable codes in tag), it is possible to envision that goods may be transported without human intervention from manufacturers to suppliers. Warehouses will become completely automatic with goods moving in and out; forwarding of the goods will be made, using intelligent decisions based on information received via readers and positioning systems to optimise transiting routes The concept of Internet of Things (IoT) has become the most popular term through the widespread of its applications such as greenhouse and telemedicine monitoring. Actually, building IoT systems requires an accurate infrastructure planning. Furthermore, management and security of these systems are considered as the most important challenges facing system developers. As security will be a fundamental enabling factor of most IoT applications, mechanisms must also be designed to protect communications enabled by such technologies. This survey analyses existing protocols and mechanisms to secure communications in the IoT, as well as open research issues. We analyse how existing approaches ensure fundamental security requirements and protect communications on the IoT, together with the open challenges and strategies for future research work in the area. This is, as far as our knowledge goes, the first survey with such goals. In this paper, the traditional techniques are studied and evaluated. Accordingly, analysis and design of innovative general purpose system, which protect the IoT resources such as devices and data against hacking or stealing, are proposed.Keywords
Internet of Things, End-to-End Security, Network Security, QoS, Internetworking.- Restoration of Old Genus Name Penaeus Based on Molecular Phylogenetic Affiliations Using Complete Mitochondrial Genome
Authors
1 ICAR-Central Institute of Brackishwater Aquaculture, Chennai 680 028, IN
Source
Current Science, Vol 121, No 3 (2021), Pagination: 423-428Abstract
Genus Penaeus sensu lato has been focus of intense scientific research for several decades owing to the high market demand of this group. Twenty eight species of shrimps, were grouped in this genus until Perez Farfante and Kensely raising the former six subgenera in this genus to generic status. Being a most valuable group, this decision made considerable concern among the end users. Recently research group from ICAR-Central Institute of Brackishwater Aquaculture made a comprehensive phylogenetic analysis and confirmed the monophyletic origin of genus Penaeus. In the present article we provide a summary of the revisionary work, and currently accepted binomial to encourage practitioners to use the modern up-to-date classification.Keywords
Genus Penaeus, Molecular Phylogenetic Affiliations, Mitochondrial Genome, Scientific Name.Full Text
References
- Crisp, D. J. and Fogg, G. E., Taxonomic instability continues to irritate. Nature, 1988, 335(6186), 120–121.
- Teletchea, F., Systematics and aquaculture: what could they bring to each other? J. Life Sci., 2016, 10, 240–244.
- Flegel, T. W., Confirmation of the right to refuse revision in the genus Penaeus. Aquaculture, 2008, 1, 1–4.
- Burkenroad, D., The Penaeidae of Louisiana, with a discussion of their world relationships. Bull. Am. Mus. Nat. Hist., 1934, 68, 61–143.
- Dall, W., Hill, B., Rothlisberg, P. and Sharples, D., The biology of the Penaeidae. In Advances in Marine Biology (eds Blaxter, J. H. S. and Southward, A. J.), Academic Press, New York, 1990, pp. 1–489.
- Lavery, S., Chan, T. Y., Tam, Y. K. and Chu, K. H., Phylogenetic relationships and evolutionary history of the shrimp genus Penaeus sl derived from mitochondrial DNA. Molec. Phylogenet. Evol., 2004, 31(1), 39–49.
- Farfante, P. I. and Kensley, B. F., Penaeoid and sergestoid shrimps and prawns of the world. Keys and diagnoses for the families and genera. Mémoir. Muséum National d’Histoire Natur., 1997, 175, 1–233.
- Schram, F. R. and Ng, P. K., What is cancer? J. Crustacean Biol., 2012, 32(4), 665–672.
- Flegel, T. W., The right to refuse revision in the genus Penaeus. Aquaculture, 2007, 64, 2–8.
- Auttarat, J., Phiriyangkul, P. and Utarabhand, P., Characterization of vitellin from the ovaries of the banana shrimp Litopenaeus merguiensis. Comp. Biochem. Physiol. B, 2006, 143, 27–36.
- Rosenberry, B., Why are you still saying ‘Litopenaeus’ vannamei? Shrimp News International, 9 February 2015.
- Baldwin, J. D., Bass, A. L., Bowen, B. W. and Clark Jr, W. H., Molecular phylogeny and biogeography of the marine shrimp Penaeus. Mol. Phylogenet. Evol., 1998, 10, 399–407.
- Chu, K. H., Li, C. P., Tam, Y. K. and Lavery, S., Application of mitochondrial control region in population genetic studies of the shrimp Penaeus. Mol. Ecol. Notes, 2003, 3(1), 120–122.
- Maggioni, R., Rogers, A. D., Maclean, N. and D’Incao, F., Molecular phylogeny of western Atlantic Farfantepenaeus and Litopenaeus shrimp based on mitochondrial 16S partial sequences. Mol. Phylogenet. Evol., 2001, 18, 66–73.
- Voloch, C. M., Freire, P. R. and Russo, C. A., Molecular phylogeny of penaeid shrimps inferred from two mitochondrial markers. Genet. Mol. Biol., 2005, 4, 668–674.
- Wang, Z. Y., Tsoi, K. H. and Chu, K. H., Applications of AFLP technology in genetic and phylogenetic analysis of penaeid shrimp. Biochem. Syst. Ecol., 2004, 32, 399–407.
- Ma, K. Y., Chan, T. Y. and Chu, K. H., Refuting the six–genus classification of Penaeus sl (Dendrobranchiata, Penaeidae): a combined analysis of mitochondrial and nuclear genes. Zool. Scr., 2011, 40, 498–508.
- Morin, P. A. et al., Complete mitochondrial genome phylogeographic analysis of killer whales (Orcinus orca) indicates multiple species. Genome Res., 2010, 20, 908–916.
- DeFilippis, V. R. and Moore, W. S., Resolution of phylogenetic relationships among recently evolved species as a function of amount of DNA sequence: an empirical study based on woodpeckers (Aves: Picidae). Mol. Phylogenet. Evol., 2000, 16(1), 143–160.
- Rokas, A. and Carroll, S. B., More genes or more taxa? The relative contribution of gene number and taxon number to phylogenetic accuracy. Mol. Biol. Evol., 2005, 22, 1337–1344.
- Ma, H., Ma, C., Li, X., Xu, Z., Feng, N. and Ma, L., The complete mitochondrial genome sequence and gene organization of the mud crab (Scylla paramamosain) with phylogenetic consideration. Gene, 2013, 519, 120–127.
- Katneni, V. K. et al., Phylogenetic relations and mitogenome‐wide similarity metrics reveal monophyly of Penaeus sensu lato. Ecol. Evol., 2021, 11, 2040–2049.
- Guindon, S., Dufayard, J. F., Lefort, V., Anisimova, M., Hordijk, W. and Gascuel, O., New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. System. Biol., 2010, 59, 307–321.
- Lanfear, R., Frandsen, P. B., Wright, A. M., Senfeld, T. and Calcott, B., PartitionFinder 2: new methods for selecting partitioned models of evolution for molecular and morphological phylogenetic analyses. Mol. Biol. Evol., 2017, 34, 772–773.
- Stamatakis, A., RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics, 2014, 30, 1312–131.
- Huelsenbeck, J. P. and Ronquist, F., MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics, 2001, 17(8), 754–755.
- McLaughlin, P. A., Lemaitre, R., Ferrari, F. D., Felder, D. L. and Bauer, R. T., A reply to TW Flegel. Aquaculture, 2008, 275, 370–373.
- Seberg, O., Humphries, C. J., Knapp, S., Stevenson, D. W., Petersen, G., Scharff, N. and Andersen, N. M., Shortcuts in systematics? A commentary on DNA-based taxonomy. Trends Ecol. Evol., 2003, 18(2), 63–65.