in Cloud Computing]]> seamless scaling, many companies struggle following up with the amount of data generated in terms
of efficient processing and anomaly detection, which is a necessary part of the management of
modern applications. As the record of user behavior, weblogs surely become the research item
related to anomaly detection. Many anomaly detection methods based on automated log analysis
have been proposed. However, not in the context of big data applications where anomalous behavior
needs to be detected in understanding phases prior to modeling a system for such use. Big Data
Analytics often ignores anomalous point due to high volume of data. To address this problem, we
propose a complemented methodology for Big Data Analytics – the Exploratory Data Analysis,
which assists in gaining insight into data relationships without the classical hypothesis modeling. In
that way, we can gain better understanding of the patterns and spot anomalies. Results show that
Exploratory Data Analysis facilitates anomaly detection and the CRISP-DM Business
Understanding phase, making it one of the key steps in the Data Understanding phase.
]]> ]]> important role. Based on the feedback we can decide whether the desired item is good or not, get a
picture of the seller and so on. Many companies that have online shops display the most positive
feedback while hiding bad ones or display only a few of them. In this research, we will help people
by automating the process of deciding whether a feedback is positive or negative, which will give
them time for other jobs and save money for hiring people who will work on the feedback. Since
feedback on online articles is very important today, the process of determining positive and
negative feedback should be made as quick and easy as possible. In this research, we will show a
very simple and fast way to classify feedback as positive or negative, which means that the main
question of this research is how to facilitate and speed up the process of determining the polarity of
the feedback. We will use NLP using Python’s library called TextBlob. The used algorithm is called
Naïve Bayes, it gave the accuracy of around 80%.
]]> Selected Institutions in Southwestern Nigeria
]]> selected institutions from four states in Southwestern Nigeria. The three purposively selected institutions
were Federal, State and Private owned making twelve institutions. However, the administered
questionnaire was filled in by the ten (10) IT personnel, ten (10) lecturers and five (5) students from each
of the selected institutions making 300 respondents. The questionnaire elicited information on the forms
and models of cloud computing technology adopted and the extent of use of the adopted cloud computing
technologies in the selected institutions. Secondary data were obtained from relevant literature. Data
collected were analysed with descriptive and inferential statistics. The study concludes that the forms of
cloud computing technology adopted by the selected institutions in Southwestern Nigeria are
infrastructure-as-a-service (IaaS), software-as-a-service (SaaS) and platform-as-a-service (PaaS) while
software-as-a-service (SaaS) is often used by the institutions. Also, the models of adopted cloud computing
technology are private, public, hybrid and community cloud computing by the selected institutions in
Southwestern Nigeria. The adopted forms and models of cloud computing technology are used for
different business functions such as payroll, procurement, human resources, accounting and finance,
CRM, application development, and project management.
]]> population of Sarajevo, as a result of economic and social migrations. Consequently, this has caused
an increasing demand for new housing which is mainly profit-oriented without any beneficial social,
environmental or cultural implication. Primary objective of this research is to analyze the current
situation and to assess the quality of the buildings not only as a housing solution, but as a complex
that unites the community who inhabits it. This research will be conducted in a qualitative manner
in analysis and statistical approach over the data related to the urbanization, building standards
and positive effects of the building. Newly built parts of settlements Otoka and Stup will be used as
case studies, since these parts of the city are most influenced by the mass production of the new
housing solutions. This paper stresses out the correlation between high demand for the new housing
and decreased quality of the housing without respecting minimum spatial and environmental
standards, without basic amenities, social infrastructure and recreational and cultural activities.
There is a need for improvements in contemporary housing design that will reflect with positive
impacts on social, environmental, economic and cultural aspects of urban living.
]]> any modern communication system. The main role of the filter is to perform attenuation of certain frequencies
and pass only frequencies of interest. In a DSP system, sampled or discrete-time signals are processed by digital
filters using different mathematical operations. Digital filters are commonly categorized as Finite Impulse
Response (FIR) and Infinite Impulse Response (IIR). This research focuses on the full VHDL implementation
of digital second-order lowpass IIR filter for reducing the noisy frequencies on the FPGA board. The initial
step is to determine, from continuous time domain function, the transfer function in the complex {s} domain,
then map transfer function in complex {z} domain and finally calculate the difference equation in discrete-time
domain of the system with adequate coefficients. Prior to the FPGA implementation, the IIR filter is tested in
MATLAB using a signal with mixed frequencies and signal with randomly generated noise. The digital
implementation is completed by using fixed-point binary vectors and clocked processes.]]> machine learning]]> load capabilities we will develop a collection of machine learning methods for detecting buildings
with best cooling load capabilities. This collection will study the influence of 8 input variables (relative
compactness, surface area, wall area, roof area, overall height, orientation, glazing area, glazing area
distribution) on one output parameter, that is cooling load of buildings. The results of this study
support the practicability of using machine-learning software to estimate building parameters as a
convenient and accurate approach, as long as the methods chosen are well suited for the type of data
in question.]]> within IoT systems based on YANG]]> network management protocol, the Network Configuration Protocol (NETCONF), within IoT
systems based on YANG is presented. The practical realization of this idea requires the
implementation of the NETCONF protocol together with REpresentational State Transfer web
services (RESTful). Such an interesting and innovative practical realization like this opens new
additional possibilities in domotics systems and these possibilities will be discussed in this paper.]]> role in student success, as well as in the overall interest of the matter. The most productive way of
increasing the student attendance rate is to understand why it decreases, try to predict when it is
going to happen, and act on causing factors in order to prevent it. Many benefits of predicted and
increased attendance rate can be achieved, including better lecture organization (i.e. lecture time and
duration, lecture class choice, etc). This paper describes the steps in the extraction of knowledge from
the university's student database and making a model that predicts whether the student will attend
the class or not. Results show that the attendance patterns are best reflected when employing a
decision tree algorithm, a C4.5 model that is interpretable and able to predict the attendance with
0.81 AUC performance measure]]> located in the Western Balkan, with a very complex history. The earliest historical findings show that
its area was inhabited since the Paleolithic. From that time, this part of Europe, especially the region
of the Modern Bosnia and Herzegovina, could be recognized as the crossroad for the different human
migration and the meeting point for different cultures, religions and gene pools. Mitochondrial DNA
is being used for maternal lineage testing, while the Y chromosome is being used for paternal lineage
testing. Therefore, these markers are being referred to as lineage markers. Lineage markers are often
used for parental lineage monitoring in population genetics, human genetics, as well as in forensic
genetics. The main intention of this paper is to construct a short overview of the Y chromosome
studies performed in Bosnia and Herzegovina within the last two decades.]]> sentiment analysis topic became one of the important and essential fields for most. Collection of
people's feelings and sentiment and classifying the data attracted most businesses and companies.
Recently, twitter sentiment analysis has attracted much attention, because of Twitter's growth and
popularity. The solution for handling enormous amounts of data from social media is a new term
called Big data. Big data is not just for having a large amount of data, but also the importance of
processing and the usage of the data.]]>