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Utilizing a Photo-Analysis Software for Content Identifying Method (CIM)

., Patterson, M. E., and Noe, F. P. (1994). Identifying and predicting visual preference of southern Appalachian forest recreation vistas. Landscape and Urban Planning, 29, 171-183. Herzog, T. R. (1989). A cognitive analysis of preference for urban nature. Journal of Environmental Psychology, 9, 27-43. Hull, R. B., & Revell, G. R. (1988). Cross-cultural comparison of landscape scenic beauty evaluations: a case study in Bali. Journal of Environmental Psychology, 9, 177-191. Hull, R.B. & Stewart, W.P. (1992). Validity of photo

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Sufficient Conditions for a Digraph to Admit A (1, ≤ℓ)-Identifying Code

References [1] G. Araujo-Pardo, C. Balbuena, L. Montejano and J.C. Valenzuela, Partial linear spaces and identifying codes , European J. Combin. 32 (2011) 344–351. doi:10.1016/j.ejc.2010.10.014 [2] C. Balbuena, C. Dalfó and B. Martínez-Barona, Characterizing identifying codes from the spectrum of a graph or digraph , Linear Algebra Appl. 570 (2019) 138–147. doi:10.1016/j.laa.2019.02.010 [3] C. Balbuena, F. Foucaud and A. Hansberg, Locating-dominating sets and identifying codes in graphs of girth at least 5, Electron. J. Combin. 22

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Genetic Algorithm Combined with a Local Search Method for Identifying Susceptibility Genes

Biology Reports, vol. 40, pp. 4227-4233, Jul 2013. [13] J. B. Chen, L. Y. Chuang, Y. D. Lin, C. W. Liou, T. K. Lin, W. C. Lee, et al., Genetic algorithmgenerated SNP barcodes of the mitochondrial Dloop for chronic dialysis susceptibility, Mitochondrial DNA, vol. 25, pp. 231-237, Jun 2014. [14] W. C. Chang, Y. Y. Fang, H. W. Chang, L. Y. Chuang, Y. D. Lin, M. F. Hou, et al., “Identifying association model for single-nucleotide polymorphisms of ORAI1 gene for breast cancer,” Cancer Cell International, vol. 14, pp. 29, Mar 2014

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Development of a Gait Recognition System in NI LabVIEW Programming Language


Nowadays, the biometric identifier’s world is one of the most rapidly developing security technology areas. Within the biometric identification, the research team worked in the area of gait recognition. The research team developed a complex walking recognition system in NI LabVIEW environment that can detect multiple simultaneous reference points using a universal camera and capable of matching a predetermined curve to the collected samples. In the first version, real-time processing was done with a single camera, while in the second, two high-resolution cameras work with post-processing. The program can compare and evaluate the functions that are matched to the reference curve and the current curve in a specific way, whether two walking images are identical. The self-developed gait recognition system was tested on several test subjects by the research team and according to the results, the False Acceptance Rate was zero.

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The Compared Costs of Domination Location-Domination and Identification

R eferences [1] C. Berge, Graphes (Gauthier-Villars, Paris, 1983). [2] C. Berge, Graphs (North-Holland Publishing Co., Amsterdam, 1985). [3] N. Bertrand, Codes identifiants et codes localisateurs-dominateurs sur certains graphes , Mémoire de stage de maîtrise, ENST (Paris, France, 2001). [4] I. Charon, O. Hudry and A. Lobstein, Possible cardinalities for identifying codes in graphs , Australas. J. Combin. 32 (2005) 177–195. [5] I. Charon, O. Hudry and A. Lobstein, Possible cardinalities for locating-dominating codes in graphs

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Identifier Services: Modeling and Implementing Distributed Data Management in Cyberinfrastructure

-research, published, and reused genomics data in a distributed environment. These functions use different data attributes to establish identity, such as: metadata, checksums, local and global identifiers, file locations, results of data content comparisons, and the sources that data belong to. One or several of these attributes and the relations between them can uniquely distinguish files or groups of files as belonging to a specific class, such as a research stage or process (e.g., alignment data, analysis, data, and published data). Identity functions can contribute to making

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The Second-order h-type Indicators for Identifying Top Units

-indices ( Schubert, 2007 ; Ruane & Tol, 2008 ), have been discussed. However, Prathap’s “second-order” h-index is not really “of order two,” and the h-series are h-indices at different objects. The further consideration of the h-index of h-series has not yet been performed because real ‘second-order h-indexes’ have never been used. Thus, the real second-order h-index remains an unanswered question, and our study focuses on the question of how a second-order h-index can be defined and identified for the same unit. Recently, the topic of research excellence has received

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Identifying nursing research priorities in Vietnam: a modified Delphi study

priority setting is considered as the critical strategy for the development of nursing science 3 and brings new insights of key stakeholders to come to a consensus as to the gaps in the science that need to be filled. 4 Nursing research priority is dynamic in response to the stage of nursing development, and can be used by faculty, students, and nurse scholars to design focused research plans, efforts, and investments for the best outcomes in the community. 2 Identifying and setting nursing research priorities has been popular internationally and serves multiple

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A blockchain based Trusted Persistent Identifier system for Big Data in Science

References [1] [2] ALICE Collaboration. ALICE data preservation strategy. CERN Open Data Portal, 2013 [3] Altman, M., Borgman, C., Crosas, M., Martone, M. An introduction to the joint principles for data citation. Bulletin of the Association for Information Science and Technology 41, 43-45 (2015). [4] Androulaki E., Barger A., Bortnikov V., Cachin C., Christidis K., De Caro AS., Enyeart D

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Towards a Methodology to Identify a Talent by Using Psychological Cognitive Prototyping

recognition as pattern recognition: How entrepreneurs “connect the dots” to identify new business opportunities. The Academy of Management Perspectives, 20 (1), 104-119. Baron, R. A., & Ensley, M. D. (2006). Opportunity recognition as the detection of meaningful patterns: Evidence from comparisons of novice and experienced entrepreneurs. Management Science, 52 (9), 1331-1344. Baron, R. A., & Ward, T. B. (2004). Expanding entrepreneurial cognition's toolbox: Potential contributions from the field of cognitive science. Entrepreneurship Theory and Practice, 28

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