45 research outputs found
Functional fatigue in NiTi shape memory alloy wires - A comparative study
No full textThe functional fatigue behaviour of two near equi-atomic NiTi shape memory alloy wires obtained from different sources were evaluated. Results showed that though the wires had similar transformation temperatures and mechanical properties, their functional fatigue behaviour upon thermo-mechanical cycling was at variance. Under a variable stress in the range 150-450 MPa and 4% recovery strain, one of the wires showed better stability, and significantly higher fatigue life (~30,000 cycles) than the other (~3,500 cycles). The reasons for such wide variation in thermo-mechanical fatigue behaviour have been discussed in this paper
Executive Power: The Springs of Authority and Mandate Rhetoric
No full textReviewing: SAIKRISHNA PRAKASH, IMPERIAL FROM THE BEGINNING: THE CONSTITUTION OF THE ORIGINAL EXECUTIVE (YALE UNIVERSITY PRESS 2015); JULIA AZARI, DELIVERING THE PEOPLE’S MESSAGE: THE CHANGING POLITICS OF THE PRESIDENTIAL MANDATE (CORNELL UNIVERSITY PRESS 2014)
An Invisible Logo Watermarking Using Arnold Transform
No full textAbstractDigital watermarking is the process of hiding information into the digital content. The method of embedding a smaller logo image into the host image is called logo watermarking. The system proposes an invisible and secure watermarking. The key entered initially determine the location of embedding and thus classified the host image to white and black textured regions. The logo image is then transformed using Arnold transform. Discrete Wavelet Transform (DWT) technique is employed for embedding the transformed logo into the white textured regions. Watermark extraction is done by entering the same key which was already entered during embedding. The system is secure and the logo is imperceptible within the host image. Finally for analysis, PSNR value has been used as a metric for determining the quality of the recovered image
Is that English You\u27re Speaking? Some Arguments for the Primacy of Intent in Interpretation
No full textTextualism is a very general and abstract term that represents a variety of views about the interpretation of legal texts. One strand of textualism is conceptual and descriptive; this strand makes claims about what texts actually mean. Another strand of textualism is normative; this strand makes claims about how judges ought to proceed when they interpret particular kinds of legal texts, such as constitutions and statutes. In the first part of this paper, we are particularly concerned with an especially strong form of conceptual textualism - the position that texts can be interpreted without any reference, express or implied, to the meaning intended by the author of the text. The defining feature of this form of textualism is the insistence that intentions play no role in the production of meaning, and so we call this view intention free textualism, or I-F-textualism. We do not know if anyone actually is an I-F-textualist so defined, although sometimes loose remarks by some self-identifying as textualists suggest that they hold this position. In any event, whether or not there is anyone who actually is a textualist of this stripe, it will be useful to drive a stake through the heart of such a position. Doing so will make it clear that what is at stake in the so-called dispute between textualists and intentionalists is not the conceptual point about what interpretation is and what determines texts\u27 meanings. Rather, it is the normative point about what evidence of authorial intent authoritative interpreters of legal texts should or should not consider, or whether interpreters should look to the intentions of actual authors or hypothetical ones.
Part One, therefore, will establish that textualism of the I-F type is a conceptual impossibility. Regardless of what position people claim to hold, no one can be such a textualist. Part One will establish that texts mean what their authors mean by them. Indeed, texts can only be identified as texts by reference to authorial intent. All of this is consistent, of course, with the possibility that one author might appropriate the marks made by another author and intend a meaning by them that is different from the meaning intended by their creator. It is also consistent with a reader\u27s imagining what a text would mean had it been authored by someone other than its actual author. Leaving these possibilities aside, however, the point Part One establishes is that texts mean what their authors intend them to mean.
In Part Two we deal with how the actual meaning of a legal text - what its author(s) intended it to mean - might differ from the authoritative meaning that an authoritative interpreter gives it. Essentially, such a divergence can be produced whenever the authoritative interpreter is debarred from considering certain types of evidence of authorial intent. The divergence occurs when the excluded evidence, had it been considered, would show the authorial intent to be different from what it appears to be given the restricted set of evidence
Is That English You\u27re Speaking? Why Intention Free Interpretation is an Impossibility
No full textTextualism is a very general and abstract term that represents a variety of views about the interpretation of legal texts. One strand of textualism is conceptual and descriptive; this strand makes claims about what texts actually mean. Another strand of textualism is normative; this strand makes claims about how judges ought to proceed when they interpret particular kinds of legal texts, such as constitutions and statutes. In the first part of this paper, we are particularly concerned with an especially strong form of conceptual textualism - the position that texts can be interpreted without any reference, express or implied, to the meaning intended by the author of the text. The defining feature of this form of textualism is the insistence that intentions play no role in the production of meaning, and so we call this view intention free textualism, or I-F-textualism. We do not know if anyone actually is an I-F-textualist so defined, although sometimes loose remarks by some self-identifying as textualists suggest that they hold this position. In any event, whether or not there is anyone who actually is a textualist of this stripe, it will be useful to drive a stake through the heart of such a position. Doing so will make it clear that what is at stake in the so-called dispute between textualists and intentionalists is not the conceptual point about what interpretation is and what determines texts\u27 meanings. Rather, it is the normative point about what evidence of authorial intent authoritative interpreters of legal texts should or should not consider, or whether interpreters should look to the intentions of actual authors or hypothetical ones. Part One, therefore, will establish that textualism of the I-F type is a conceptual impossibility. Regardless of what position people claim to hold, no one can be such a textualist. Part One will establish that texts mean what their authors mean by them. Indeed, texts can only be identified as texts by reference to authorial intent. All of this is consistent, of course, with the possibility that one author might appropriate the marks made by another author and intend a meaning by them that is different from the meaning intended by their creator. It is also consistent with a reader\u27s imagining what a text would mean had it been authored by someone other than its actual author. Leaving these possibilities aside, however, the point Part One establishes is that texts mean what their authors intend them to mean. In Part Two we deal with how the actual meaning of a legal text - what its author(s) intended it to mean - might differ from the authoritative meaning that an authoritative interpreter gives it. Essentially, such a divergence can be produced whenever the authoritative interpreter is debarred from considering certain types of evidence of authorial intent. The divergence occurs when the excluded evidence, had it been considered, would show the authorial intent to be different from what it appears to be given the restricted set of evidence
Meta-Data of Papers in Asia-Pacific Software Engineering Conference from 2010 to 2015
No full textThe Asia-Pacific Software
Engineering Conference (APSEC) is an annual conference started in the year 1994
in Tokyo (Japan) with the aim of brining software engineering researchers and
practitioners from both university and industry around the world to exchange
research results and ideas. APSEC 1994 (Tokyo, Japan) was the first edition of
the conference and the annual event completes 23 editions in 2016 (Hamilton,
New Zealand). The dataset contains meta-data on APSEC 2010 to APSEC 2015 papers
from various perspectives such as paper
acceptance rates, conference location, scholarly output of various countries, keynotes,
workshops, conference organizers and sponsors, tutorials, prolific authors,
citation impact, internal and external collaboration, university and industry
participation and collaboration, gender imbalance, topical analysis, yearly author
churn and program committee characteristics. The paper titled “A Review of Six
Years of Asia-Pacific Software Engineering Conference” by Lov Kumar, Saikrishna
Sripada and Ashish Sureka published in APSEC 2016 is based on this dataset</p
MML Inference of Finite State Automata for Probabilistic Spam Detection
No full textAbstract—MML (Minimum Message Length) has emerged as a powerful tool in inductive inference of discrete, continuous and hybrid structures. The Probabilistic Finite State Automaton (PFSA) is one such discrete structure that needs to be inferred for classes of problems in the field of Computer Science including artificial intelligence, pattern recognition and data mining. MML has also served as a viable tool in many classes of problems in the field of Machine Learning including both supervised and unsupervised learning. The classification problem is the most common among them. This research is a two-fold solution to a problem where one part focusses on the best inferred PFSA using MML and the second part focusses on the classification problem of Spam Detection. Using the best PFSA inferred in part 1, the Spam Detection theory has been tested using MML on a publicly available Enron Spam dataset. The filter was evaluated on various performance parameters like precision and recall. The evaluation was also done taking into consideration the cost of misclassification in terms of weighted accuracy rate and weighted error rate. The results of our empirical evaluation indicate the classification accuracy to be around 93%, which outperforms well-known established spam filters
Statistical compression-based models for text classification
No full textText classification is the task of assigning predefined categories to text documents. It is a common machine learning problem. Statistical text classification that makes use of machine learning methods to learn classification rules are particularly known to be successful in this regard. In this research project we are trying to re-invent the text classification problem with a sound methodology based on statistical data compression technique-the Minimum Message Length (MML) principle. To model the data sequence we have used the Probabilistic Finite State Automata (PFSAs). We propose two approaches for text classification using the MML-PFSAs. We have tested both the approaches with the Enron spam dataset and the results of our empirical evaluation has been recorded in terms of the well known classification measures i.e. recall, precision, accuracy and error. The results indicate good classification accuracy that can be compared with the state of art classifiers. © 2016 IEEE
