Abstract: The Internet of Things (IoT) will lead to the development of advanced Smart Home services that are pervasive, cost-effective, and can be accessed by home occupants from anywhere and at any time. However, advanced smart home applications will introduce grand security challenges due to the increase in the attack surface. Current approaches do not handle cybersecurity from a holistic point of view; hence, a systematic cybersecurity mechanism needs to be adopted when designing smart home applications. In this paper, we present a generic intrusion detection methodology to detect and mitigate the anomaly behaviors happened in Smart Home Systems (SHS). By utilizing our Smart Home Context Data Structure, the heterogeneous information and services acquired from SHS are mapped in context attributes which can describe the context of smart home operation precisely and accurately. Runtime models for describing usage patterns of home assets are developed based on characterization functions. A threat-aware action management methodology, used to efficiently mitigate anomaly behaviors, is proposed at the end. Our preliminary experimental results show that our methodology can be used to detect and mitigate known and unknown threats, as well as to protect SHS premises and services.
Abstract: Advertising is commonly used to foster sales and reputation of an institution. It is at first the growth of print advertising that has increased the population and number of periodicals of newspaper and its circulation. The rise of Internet and online media has somehow blurred the role of media and advertising though the intention is still to reach out to audience and to increase sales. The relationship between advertising and audience on a product purchase through persuasion has been developing from print media to online media. From the changing media environment and audience, it is the concern of this research to study the impact of online advertising to such a relationship cycle. The content of online advertisements is much of text, multimedia, photo, audio and video. The messages of such content format may indeed bring impacts to its audience and its credibility. This study is therefore reflecting the effectiveness of online advertisement and its influences on generation Y in their purchasing behavior. This study uses Media Dependency Theory to analyze the relationship between the impact of online advertisement and media usage pattern of generation Y. Hierarchy of Effectiveness Model is used as a marketing communication model to study the effectiveness of advertising and further to determine the impact of online advertisement on generation Y in their purchasing decision making. This research uses online survey to reach out the sample of generation Y. The results have shown that online advertisements do not affect much on purchase decision making even though generation Y relies much on the media content including online advertisement for its information and believing in its credibility. There are few other external factors that may interrupt the effectiveness of online advertising. The very obvious influence of purchasing behavior is actually derived from the peers.
Abstract: Web Usage Mining is the application of data mining
techniques to find usage patterns from web log data, so as to grasp
required patterns and serve the requirements of Web-based
applications. User’s expertise on the internet may be improved by
minimizing user’s web access latency. This may be done by
predicting the future search page earlier and the same may be prefetched
and cached. Therefore, to enhance the standard of web
services, it is needed topic to research the user web navigation
behavior. Analysis of user’s web navigation behavior is achieved
through modeling web navigation history. We propose this technique
which cluster’s the user sessions, based on the K-medoids technique.
Abstract: Home Energy Management System (HEMS), which makes the residential consumers, contribute to the demand response is attracting attention in recent years. An aim of HEMS is to minimize their electricity cost by controlling the use of their appliances according to electricity price. The use of appliances in HEMS may be affected by some conditions such as external temperature and electricity price. Therefore, the user’s usage pattern of appliances should be modeled according to the external conditions, and the resultant usage pattern is related to the user’s comfortability on use of each appliances. This paper proposes a methodology to model the usage pattern based on the historical data with the copula function. Through copula function, the usage range of each appliance can be obtained and is able to satisfy the appropriate user’s comfort according to the external conditions for next day. Within the usage range, an optimal scheduling for appliances would be conducted so as to minimize an electricity cost with considering user’s comfort. Among the home appliance, electric heater (EH) is a representative appliance, which is affected by the external temperature. In this paper, an optimal scheduling algorithm for an electric heater (EH) is addressed based on the method of branch and bound. As a result, scenarios for the EH usage are obtained according to user’s comfort levels and then the residential consumer would select the best scenario. The case study shows the effects of the proposed algorithm compared with the traditional operation of the EH, and it represents impacts of the comfort level on the scheduling result.
Abstract: This paper explores and provides substantiated
evidence on the usage patterns of Information and Communication
Technologies (ICTs) by female users at Vhembe District in Limpopo-
Province, South Africa. The study presents a comprehensive picture
on the usage of ICTs from female users’ perspective. The
significance of this study stems from the need to assess the role,
relevance and usage patterns of ICTs such as smartphones,
computers, laptops, and iPods, the internet and social networking
sites among females following the developments of new media
technologies in society. The objective of the study is to investigate
the usability and accessibility of ICTs to empower female users in
South Africa. The study used quantitative and qualitative research
methods to determine the major ideas, perceptions and usage patterns
of ICTs by users. Data collection involved the use of structured selfadministered
questionnaire from two groups of respondents who
participated in this study. Thus, (n=50) female students at the
University of Venda provided their ideas and perceptions about the
usefulness and usage patterns of ICTs such as smartphones, the
Internet and computers at the university level, whereas, the second
group were (n=50) learners from Makhado Comprehensive School
who provided their perceptions and ideas about the use of ICTs at the
high school level. The researcher also noted that the findings of the
study were useful as a guideline and model for ICT intervention that
could work as an empowerment to women in South Africa. It was
observed that the central purpose of ICTs among female users was to
search for information regarding assignment writing, conducting
research, dating, exchanging ideas and networking with friends and
relatives. This was demonstrated by a high number of females who
used ICTs for e-learning (62%) and social purposes (85%).
Therefore, the study revealed that most females used ICTs for social
purposes and accessing the internet rather than for entertainment, a
gesture that provides an opportune space to empower rural women in
South Africa.
Abstract: In this study, we discussed the effects on the thermal
comfort of super high-rise residences that how effected by the high
thermal capacity structural components. We considered different
building orientations, structures, and insulation methods. We used the
dynamic simulation software THERB (simulation of the thermal
environment of residential buildings). It can estimate the temperature,
humidity, sensible temperature, and heating/cooling load for multiple
buildings. In the past studies, we examined the impact of
air-conditioning loads (hereinafter referred to as AC loads) on the
interior structural parts and the AC-usage patterns of super-high-rise
residences.
Super-high-rise residences have more structural components such
as pillars and beams than do ordinary apartment buildings. The
skeleton is generally made of concrete and steel, which have high
thermal-storage capacities. The thermal-storage capacity of
super-high-rise residences is considered to have a larger impact on the
AC load and thermal comfort than that of ordinary residences.
We show that the AC load of super-high-rise units would be
reduced by installing insulation on the surfaces of interior walls that
are not usually insulated in Japan.
Abstract: In this report we present a rule-based approach to
detect anomalous telephone calls. The method described here uses
subscriber usage CDR (call detail record) data sampled over two
observation periods: study period and test period. The study period
contains call records of customers- non-anomalous behaviour.
Customers are first grouped according to their similar usage
behaviour (like, average number of local calls per week, etc). For
customers in each group, we develop a probabilistic model to describe
their usage. Next, we use maximum likelihood estimation (MLE) to
estimate the parameters of the calling behaviour. Then we determine
thresholds by calculating acceptable change within a group. MLE is
used on the data in the test period to estimate the parameters of the
calling behaviour. These parameters are compared against thresholds.
Any deviation beyond the threshold is used to raise an alarm. This
method has the advantage of identifying local anomalies as compared
to techniques which identify global anomalies. The method is tested
for 90 days of study data and 10 days of test data of telecom
customers. For medium to large deviations in the data in test window,
the method is able to identify 90% of anomalous usage with less than
1% false alarm rate.
Abstract: With the explosive growth of data available on the
Internet, personalization of this information space become a
necessity. At present time with the rapid increasing popularity of the
WWW, Websites are playing a crucial role to convey knowledge and
information to the end users. Discovering hidden and meaningful
information about Web users usage patterns is critical to determine
effective marketing strategies to optimize the Web server usage for
accommodating future growth. The task of mining useful information
becomes more challenging when the Web traffic volume is enormous
and keeps on growing. In this paper, we propose a intelligent model
to discover and analyze useful knowledge from the available Web
log data.
Abstract: The purpose of this paper is to propose an integrated
consumer health informatics utilization framework that can be used
to gauge the online health information needs and usage patterns
among Malaysian women. The proposed framework was developed
based on four different theories/models: Use and Gratification
Theory, Technology Acceptance 3 Model, Health Belief Model, and
Multi-level Model of Information Seeking. The relevant constructs
and research hypotheses are also presented in this paper. The
framework will be tested in order for it to be used successfully to
identify Malaysian women-s preferences of online health information
resources and health information seeking activities.
Abstract: Software reliability, defined as the probability of a
software system or application functioning without failure or errors
over a defined period of time, has been an important area of research
for over three decades. Several research efforts aimed at developing
models to improve reliability are currently underway. One of the
most popular approaches to software reliability adopted by some of
these research efforts involves the use of operational profiles to
predict how software applications will be used. Operational profiles
are a quantification of usage patterns for a software application. The
research presented in this paper investigates an innovative multiagent
framework for automatic creation and management of
operational profiles for generic distributed systems after their release
into the market. The architecture of the proposed Operational Profile
MAS (Multi-Agent System) is presented along with detailed
descriptions of the various models arrived at following the analysis
and design phases of the proposed system. The operational profile in
this paper is extended to comprise seven different profiles. Further,
the criticality of operations is defined using a new composed metrics
in order to organize the testing process as well as to decrease the time
and cost involved in this process. A prototype implementation of the
proposed MAS is included as proof-of-concept and the framework is
considered as a step towards making distributed systems intelligent
and self-managing.