Wearable devices give people the ability to track almost every facet of the lives through being embedded with a multitude of sensors. The collection of data through the use of these sensors is called 'personal metrics' - the quantification of everyday activity in order to change, improve or understand human behaviour. In order to deliver meaningful insight to the user, these personal metrics need to be sent to companies for analysis. This collection of data from companies ultimately causes complex concerns for consumer's privacy, most notably among young consumers, who are widely reported as having an increased acceptance for the sharing of their data. The study was achieved through first gaining-an understanding into the research area through reviewing literature, and then conducting primary research through an online survey. Overall, it was found that education into app privacy regulation and companies' use of data alone didn't have much effect on young adult consumer's behaviours. Furthermore, it was concluded that, young adult consumers appear to have an acceptance for the loss of their privacy, however some behaviours appear to show a level of concern. Nonetheless, due to limitations in the methodology of the research undertaken, it was concluded that further studies would be required in order to ensure the validity of the data.
Audio steganography is a security technique by which a secret data to be transmitted over a public insecure channel is embedded into an audio cover object that hides it in such way that third party cannot detect the presence of the message. In this proposed system, DES cryptographic encryption algorithm is used to encrypt data before hiding it into the cover object for additional security. For the purpose of data encoding into audio samples, LSB coding algorithm is used. The overall system gives a relatively secure system that hides the secret message, a feature is provided by steganography, beside deformations the structure of the message, a feature provided by cryptography, which together leads to prepare the message travel through public channels.
Whole world and administrators of Educational institutions are concerned about the regularity of student;s attendance. Students overall academic performance is affected by the student's presence in his/her institute. Due to that, keeping track of student’s attendance becomes an important job in an academic environment. This paper presents a software design and implementation for taking student’s attendance and extract different kinds of absence reports. The software system is based on inserting, deleting, updating and querying of a database management system. In this system, the teachers engaging different classes are required to submit the attendance of the students present in their class regularly. The administrator monitoring this information, can extract different reports about a student’s weekly absence or whenever he/she wants the details using this system.
Data Mining is one of the emerging fields in research. Preparing a Data set is one of the important tasks in Data Mining. To analyze data efficiently, Data Mining systems are widely using datasets with columns in horizontal tabular layout. Building a datasets for analysis is normally a most time consuming task. Existing SQL aggregations have limitation to build data sets because they return one column for aggregated group using group functions. A method is developed to generate SQL code to return aggregated columns in a horizontal tabular layout, returning a set of numbers instead of one number per row. This new class of functions are called horizontal aggregations. This method is termed as BY-LOGIC. SQL code generator generates automatic SQL code for producing horizontal aggregation. A fundamental method to evaluate horizontal aggregation called CASE (exploiting the case programming construct) is used. Basically, there are three parameters available namely: grouping, sub-grouping and aggregating fields for creating horizontal aggregation. Query evaluation shows that CASE method responses faster than BY-LOGIC method.
A popular feature of many Online Social Network (OSN) is photo tagging and photo sharing that allows users to annotate the images who are present in the uploaded images. To overcome the user's privacy, a Facial Recognition (FR) system has been designed effectively during sharing, posting and liking of the photos. An increasing number of personal photographs are uploaded to Online Social Networks, and these photos do not exist in isolation. Photo tagging is a popular feature of many social network sites. The FR system is superior to some possible approaches in terms of increase in recognition ratio and efficiency. To achieve this, OSN specifies a privacy policy and an exposure policy. By these policies, individuals are enabled in a photo by providing permissions before posting a co-photo [11]. Exploring computational techniques and confidentiality of training sets that takes advantage of these trends seems a worthwhile endeavor. To share our photo safely we need an effective FR system, which can recognize everyone in the photo. We also attempted to develop users' private photos for designing an adaptive Face Recognition system specifically used to share a photo with their permission. Finally, the system protects user's privacy in photo sharing over Online Social Network.
The scientific output of researchers has become an important achievement in scientific community. In most recent years, several bibliographic indices were proposed to assess the quality of the academic research publications, h-index being more prominent among all indices. Considering h-index value of a journal as dependent variable and citation parameters as independent variables, a python based regression algorithmic approach was reported in this study to delineate the dependency of h-index on citation parameters such as Total Docs., Total Cites, Citable Docs., Cites/Doc. and Ref./Doc., respectively. From regression analysis, it is observed that high value of TC3, CD3 and CD2 contributes positively to enhance h-index factor of journals, whereas on the other hand, TD3 and RD would contribute negatively to hindex.
