Both US-1 and US-2 also have several other potential advantages. First, by utilizing user requests as the base for generating test cases, the techniques are less dependent on the complex and fast changing technology underlying web applications, which is one of the major limitations of white box approaches designed to work with a subset of the avail- able protocols. Second, the level of effort involved in cap- turing URL and name-value pairs is relatively small as these are already processed by web applications. This is not the case with white box approaches such as Ricca and Tonella’s, which require a high degree of tester participation. Third, with these approaches, each user is a potential tester: this implies potential for an economy of scale in which addi- tional users provide more inputs for use in test generation. The potential power of the techniques resides in the num- ber and representativeness of the URL and name-value pairs collected, and the possibility of their use in generating a more powerful test suite (an advantage that must be bal- anced, however, against the cost of gathering the associated user-sessiondata). Finally, both approaches, unlike tradi- tional capture and replay approaches, automatically capture authentic user interactions for use in deriving test cases, as opposed to interactions created by testers.
The Limitation of our model is, to create User Interested Page Ontology for the new users in the website, because we will create UIPO from the web log information only. For the new users there is no web log data, for those cases it creates the UIPO based upon the user profile or creates the UIPO for the corresponding website without user’s interest. In future we will find solution for this problem. Ultimately the aim of our research is according to the discovered pattern to generate recommendations and improve the website Design. The results produced by our research can also provide guidelines for improving the design of web applications too. REFERENCES
Abstract— For any business output means product should be perfectly formulated which is decided in meeting and to make meeting successful there should be some strategies analysis to review different opinion of different member in meeting, and based upon that product is successful in market or not. First it was given by Anvil tool which was bit difficult to analyze because it was working on gesture recognition and then it worked on tree-based structure mechanism which created and define the sessions so that each session can accommodate the individual’s opinion, and after that session, if rectification is performed, but commands such as propose, acknowledgment, and negative response do not have a fixed structure or a notion that can differentiate them from one another. So in Proposed system we are using various Data Mining algorithms to label the nodes which differentiate from one another. The experimental results show that Threshold value which will decide future step of the product.
A session conducted under immediate supervision (line of sight) of the instructor of record using lecture, discussion, collaborative or experiential learning, that may also include incidental use of visual aids, various media, site visits, etc. at the instructor's discretion.
When routing information is ready to be transferred, the second phase of the authentication and key agreement process takes place. Authentication carries on in the available nodes starting one-hop at a time from the source to destination route. While nodes in the source to destination path are authenticated, they also agree on an encryption key, also referred to as session key, which will be used to encrypt their traffic. Similar to the pre-secure session, data confidentiality and integrity can be achieved using well-known cryptographic algorithms. Moreover, non-repudiation can be attained with cryptographic techniques, such as digital signatures, message authentication codes (MAC) and hash functions.
End-of-session questionnaires generally ask about participant’s reactions – what people thought about the program, including content, materials, facilities and administration. Were participants pleased with the session? Participant reaction is important to consider when redesigning or continuing your educational effort. Reactions do not represent outcomes but they are a major input for improving programs. Your questions might focus on people’s reactions relative to the session’s value, usefulness, quality, applicability, appropriateness, relevance or how well it met expectations. The following lists indicate a variety of reactions that might be of interest. Reactions to the presenters are covered in a separate section, Teaching and Facilitation.
Software defects, bugs, and flaws in the logic of the program are consistently the cause for software vulnerabilities. Analysis by software security professionals has proven that most vulnerabilities are due to errors in programming. Hence, it has become a must for organizations to educate their software developers about secure coding practices. Attackers try to find security vulnerabilities in the applications or servers and then try to use these vulnerabilities to steal secrets, corrupt programs and data, and gain control of computer systems and networks. Sound programming techniques and best practices can be used to develop high quality code to prevent web application attacks. Secure programming is a defensive measure against attacks targeted towards application systems.
The acquisition setup is based on the Ottobock 13E200 pre-amplified single-ended sEMG electrode (Figure 4.2a), which is a commercial sensor. It amplifies and integrates the raw EMG signal to reach an output span of 0 − 3.3V. The sensors have bandwidth spanning 90 − 450Hz and integrate an analog notch filter to remove the noise due to Power Line Interference (PLI), i.e. the capacitive coupling between the subject and the surrounding electrical devices and power grid (detailed in Section 2.1). The output analog signals were acquired with a custom embedded board based on a microcontroller equipped with an internal 16-bit ADC. The digitalized signals were streamed via Bluetooth to a laptop, for storage and off-line data analysis.
The main advantage of the early binding is that it defines the data semantics explicitly so that on-line data exchange can be carried out directly. Its disadvantage is the need for re- engineering when the data definition or the schema changes. On the other hand, the advantage of late binding is that it is schema independent and schema is stored as data so that it can be manipulated to facilitate data exchange task. Its main constraint is the lack of explicit definition of the data structure in the Kernel. An late binding solution would work well for the off-line data exchange. Because the exchange takes place through a neutral media, data interpretation has to be performed at both sides no matter how the Kernel is implemented. For on-line data exchanges, the late binding approach introduces extra complications. By definition on-line design tools will access the Kernel directly. They need to know not only the value of the data but also the semantics of the data. For this purpose, the data has to be represented explicitly as what it really is not in an abstract form. A late binding Kernel will be not able to provide this support. Therefore, an alternative solution, a combination of early and late binding, was investigated. The aim is to overcome the disadvantages of both approaches while keep their respective advantages. Two key technologies were used to achieve this aim, they are the ISO Standard Data Access Interface, SDAI for short (ISO 1993) and Objectstore database metaobject protocol (Object Design 1994).
YES core content components include the key messages and activities that are designed to emphasize the three different elements of empowerment illustrated in Figures 1 and 2: Intrapersonal (Feeling), Behavioral (Doing), and Interactional (Connecting). Each element is connected with specific skills, abilities, attitudes and beliefs that YES activities are designed to promote. Table 1 provides examples of sessions from the curriculum that support elements of empowerment. Refer to Appendix A. to see how the empowerment elements align with each session of the YES Curriculum.
Hand-held PDA devices were the first wave of dedicated electronic PRO (ePRO) technology designed to improve the data quality coming from patients and provide reviewers with more immediate access to data. While this solution has advantages over distributing paper, the small PDA screens can possibly restrict the information patients provide, and are costly to distribute and maintain. Other electronic options, EDC and IVR, also have inherent problems that can constrict accurate data collection, limiting widespread adoption of these technologies for late phase research and ePRO.
Finally, we turn to the last component of the session layer, i.e., the inter-session times. We found that no single distribution provided a good fit for the data, in any dataset. Thus, we opted for breaking the measured data into ranges, and determining the best fit for each range. Figure 6 shows the empirical distributions and best fits for measured times less than 720 minutes, which are the majority of all measurements (69%, 81% and 79% for campuses 1, 2 and 3). Once again, in order to make visual inspection clearer, we plot the curves in this figura in log scale. Inter-session times tend to be short, implying that users who leave the Dropbox service and later reconnect tend to do it quickly. This occurs more often in campuses 2 and 3 where the use of NAT and more unstable networks cause disconnections more often. For example, 52% (campuses 2 and 3) and 27% (campus 1) of the inter-session times are under 5 minutes. We find that a Log-Normal distribution is the best fit for all three campuses for this range of measured inter-session times as well as for the other considered ranges (below and above 2000 minutes 6 ). 6 In campuses 2 and 3, around 12% of the inter-session times are between
ERCA is mainly used to maintain fairness among user where more NRT user’s present in the cell. RB are allocated based on the PF criteria given by the call admission control mechanism and power allocated to each RB. In a cell more number of NRT user is placed. With the allocated RB’s path loss gain is calculated with average data rate. Based on Natural log function minimum filtering mean square method is used. Hence the natural log function is polarized when the maximum channel gain is equal to 1 with the ration of NRT User.