A Survey on Flip Flop Replacement to Latch on Various Design

This paper presents survey for the replacement of flip flop to latches and the advantages of the latch based sequential design Flip flop are the major part of the design a sequential elements and this flip flop has more disadvantages as performance decreases and area increases. An alternate method to increase the performance and reduce the area size latches. Latches are used instead of flip flops in certain places to increase the performance and decrease the area

A Survey on Flip Flop Replacement to Latch on Various Design

This paper presents survey for the replacement of flip flop to latches and the advantages of the latch based sequential design Flip flop are the major part of the design a sequential elements and this flip flop has more disadvantages as performance decreases and area increases. An alternate method to increase the performance and reduce the area size latches. Latches are used instead of flip flops in certain places to increase the performance and decrease the area

The design and study of pedagogical paper recommendation

For learners engaging in senior-level courses, tutors in many cases would like to pick some articles as supplementary reading materials for them each week. Unlike researchers ‘Googling’ papers from the Internet, tutors, when making recommendations, should consider course syllabus and their assessment of learners along many dimensions. As such, simply ‘Googling’ articles from the Internet is far from enough. That is, learner models of each individual, including their learning interest, knowledge, goals, etc. should be considered when making paper recommendations, since the recommendation should be carried out so as to ensure that the suitability of a paper for a learner is calculated as the summation of the fitness of the appropriateness of it to help the learner in general. This type of the recommendation is called a Pedagogical Paper Recommender.In this thesis, we propose a set of recommendation methods for a Pedagogical Paper Recommender and study the various important issues surrounding it. Experimental studies confirm that making recommendations to learners in social learning environments is not the same as making recommendation to users in commercial environments such as Amazon.com. In such learning environments, learners are willing to accept items that are not interesting, yet meet their learning goals in some way or another; learners’ overall impression towards each paper is not solely dependent on the interestingness of the paper, but also other factors, such as the degree to which the paper can help to meet their ‘cognitive’ goals.It is also observed that most of the recommendation methods are scalable. Although the degree of this scalability is still unclear, we conjecture that those methods are consistent to up to 50 papers in terms of recommendation accuracy. The experiments conducted so far and suggestions made on the adoption of recommendation methods are based on the data we have collected during one semester of a course. Therefore, the generality of results needs to undergo further validation before more certain conclusion can be drawn. These follow up studies should be performed (ideally) in more semesters on the same course or related courses with more newly added papers. Then, some open issues can be further investigated. Despite these weaknesses, this study has been able to reach the research goals set out in the proposed pedagogical paper recommender which, although sounding intuitive, unfortunately has been largely ignored in the research community. Finding a ‘good’ paper is not trivial: it is not about the simple fact that the user will either accept the recommended items, or not; rather, it is a multiple step process that typically entails the users navigating the paper collections, understanding the recommended items, seeing what others like/dislike, and making decisions. Therefore, a future research goal to proceed from the study here is to design for different kinds of social navigation in order to study their respective impacts on user behavior, and how over time, user behavior feeds back to influence the system performance

Survey on Hardware Implementation of Montgomery Modular

This paper gives the information regarding different methodology for modular multiplication with the modification of Montgomery algorithm. Montgomery multiplier proved to be more efficient multiplier which replaces division by the modulus with series of shifting by a number and an adder block. For larger number of bits, Modular multiplication takes more time to compute and also takes more area of the chip. Different methods ensure more speed and less chip size of the system. The speed of the multiplier is decided by the multiplier. Here three modified Montgomery algorithm discussed with their output compared with each other. The three methods are Iterative architecture, Montgomery multiplier for faster Cryptography and Vedic multipliers used in Montgomery algorithm for multiplication.Here three boards have been used for the analysis and they are Altera DE2-70, FPGA board Virtex 6 and Kintex 7

Hybrid user perception model: comparing users’ perceptions toward collaborative, content-based, and hybrid recommender systems

This study examines users’ perceptions toward three types of recommender systems by employing a hybrid user perception model combining with Theory of Planned Behavior (TPB) and Technology Acceptance Model (TAM) in order to specifically explain a message-attitude-use process. Recommender systems, as an innovation applying big data ideas and algorithmic power, have been widely applied to multiple Internet industries. In order to further investigate how users perceived the use of recommender systems and the differences among users’ perceptions toward the use of different recommender systems (collaborative filtering, content-based filtering, and hybrid filtering), three perception variables (perceived usefulness, perceived behavioral control, and perceived enjoyment) were specifically assessed by using an online survey of college students. Overall, the results indicated that there were some statistically significant differences among the user perceptions towards different types of recommender systems. In addition, users generally feel positive about the use of these recommender systems, and users’ perceptions toward hybrid-filtering system were rated higher than perceptions toward collaborative filtering and content-based filtering

Survey on Hardware Implementation of Montgomery Modular

This paper gives the information regarding different methodology for modular multiplication with the modification of Montgomery algorithm. Montgomery multiplier proved to be more efficient multiplier which replaces division by the modulus with series of shifting by a number and an adder block. For larger number of bits, Modular multiplication takes more time to compute and also takes more area of the chip. Different methods ensure more speed and less chip size of the system. The speed of the multiplier is decided by the multiplier. Here three modified Montgomery algorithm discussed with their output compared with each other. The three methods are Iterative architecture, Montgomery multiplier for faster Cryptography and Vedic multipliers used in Montgomery algorithm for multiplication.Here three boards have been used for the analysis and they are Altera DE2-70, FPGA board Virtex 6 and Kintex 7