Abstract: Secure computations are essential while performing privacy preserving data mining. Distributed privacy preserving data mining involve two to more sites that cannot pool in their data to a third party due to the violation of law regarding the individual. Hence in order to model the private data without compromising privacy and information loss, secure multiparty computations are used. Secure computations of product, mean, variance, dot product, sigmoid function using the additive and multiplicative homomorphic property is discussed. The computations are performed on vertically partitioned data with a single site holding the class value.
Abstract: Human faces, as important visual signals, express a significant amount of nonverbal info for usage in human-to-human communication. Age, specifically, is more significant among these properties. Human age estimation using facial image analysis as an automated method which has numerous potential real‐world applications. In this paper, an automated age estimation framework is presented. Support Vector Regression (SVR) strategy is utilized to investigate age prediction. This paper depicts a feature extraction taking into account Gray Level Co-occurrence Matrix (GLCM), which can be utilized for robust face recognition framework. It applies GLCM operation to remove the face's features images and Active Appearance Models (AAMs) to assess the human age based on image. A fused feature technique and SVR with GA optimization are proposed to lessen the error in age estimation.
Abstract: In the current mine air compressors monitoring system, there are some difficulties in the installation and maintenance because of the wired connection. To solve the problem, this paper introduces a new air compressors monitoring system based on ZigBee in which the monitoring parameters are transmitted wirelessly. The collecting devices are designed to form a cluster network to collect vibration, temperature, and pressure of air cylinders and other parameters. All these devices are battery-powered. Besides, the monitoring software in PC is developed using MFC. Experiments show that the designed wireless sensor network works well in the site environmental condition and the system is very convenient to be installed since the wireless connection. This monitoring system will have a wide application prospect in the upgrade of the old monitoring system of the air compressors.
Abstract: Following the current economic challenges and competition, all systems, whatever their field, must be efficient and operational during their activity. In this context, it is imperative to anticipate, identify, eliminate and estimate the failures of systems, which may lead to an interruption of their function. This need requires the management of possible risks, through an assessment of the failures criticality following a dependability approach. On the other hand, at the time of new information technologies and considering the networks field evolution, the data transmission has evolved towards a multipoint communication, which can simultaneously transmit information from a sender to multiple receivers. This article proposes the failures criticality assessment of a multipoint communication network, integrates a database of network failures and their quantifications. The proposed approach is validated on a case study and the final result allows having the criticality matrix associated with failures on the considered network, giving the identification of acceptable risks.
Abstract: Fiber-Wireless (FiWi) networks are a promising candidate for future broadband access networks. These networks combine the optical network as the back end where different passive optical network (PON) technologies are realized and the wireless network as the front end where different wireless technologies are adopted, e.g. LTE, WiMAX, Wi-Fi, and Wireless Mesh Networks (WMNs). The convergence of both optical and wireless technologies requires designing architectures with robust efficient and effective bandwidth allocation schemes. Different bandwidth allocation algorithms have been proposed in FiWi networks aiming to enhance the different segments of FiWi networks including wireless and optical subnetworks. In this survey, we focus on the differentiating between the different bandwidth allocation algorithms according to their enhancement segment of FiWi networks. We classify these techniques into wireless, optical and Hybrid bandwidth allocation techniques.
Abstract: Currently, the field of data migration is very topical. As the number of applications developed rapidly, the ever-increasing volume of data collected has driven the architectural migration from Relational Database Management System (RDBMS) to NoSQL (Not Only SQL) database. This very recent technology is important enough in the field of database management. The main aim of this paper is to present a methodology for data migration from RDBMS to NoSQL database. To illustrate this methodology, we implement a software prototype using MySQL as a RDBMS and MongoDB as a NoSQL database. Although this is a hard engineering work, our results show that the proposed methodology can successfully accomplish the goal of this study.
Abstract: Automatic program generation saves time, human resources, and allows receiving syntactically clear and logically correct modules. The 4-th generation programming languages are related to drawing the data and the processes of the subject area, as well as, to obtain a frame of the respective information system. The application can be separated in interface and business logic. That means, for an interactive generation of the needed system to be used an already existing toolkit or to be created a new one.
Abstract: This paper discusses the intake of combining multi-criteria
decision analysis (MCDA) with OLAP systems, to generate
an integrated analysis process dealing with complex multi-criteria
decision-making situations. In this context, a multi-agent modeling is
presented for decision support systems by combining multi-criteria
decision analysis (MCDA) with OLAP systems. The proposed
modeling which consists in performing the multi-agent system
(MAS) architecture, procedure and protocol of the negotiation model
is elaborated as a decision support tool for complex decision-making
environments. Our objective is to take advantage from the multi-agent
system which distributes resources and computational
capabilities across interconnected agents, and provide a problem
modeling in terms of autonomous interacting component-agents.
Thus, the identification and evaluation of criteria as well as the
evaluation and ranking of alternatives in a decision support situation
will be performed by organizing tasks and user preferences between
different agents in order to reach the right decision. At the end, an
illustrative example is conducted to demonstrate the function and
effectiveness of our MAS modeling.
Abstract: Data fusion technology can be the best way to extract
useful information from multiple sources of data. It has been widely
applied in various applications. This paper presents a data fusion
approach in multimedia data for event detection in twitter by using
Dempster-Shafer evidence theory. The methodology applies a mining
algorithm to detect the event. There are two types of data in the
fusion. The first is features extracted from text by using the bag-ofwords
method which is calculated using the term frequency-inverse
document frequency (TF-IDF). The second is the visual features
extracted by applying scale-invariant feature transform (SIFT). The
Dempster - Shafer theory of evidence is applied in order to fuse the
information from these two sources. Our experiments have indicated
that comparing to the approaches using individual data source, the
proposed data fusion approach can increase the prediction accuracy
for event detection. The experimental result showed that the proposed
method achieved a high accuracy of 0.97, comparing with 0.93 with
texts only, and 0.86 with images only.
Abstract: Introduction: To update ourselves and understand the
concept of latest electronic formats available for Health care
providers and how it could be used and developed as per standards.
The idea is to correlate between the patients Manual Medical Records
keeping and maintaining patients Electronic Information in a Health
care setup in this world. Furthermore, this stands with adapting to the
right technology depending upon the organization and improve our
quality and quantity of Healthcare providing skills. Objective: The
concept and theory is to explain the terms of Electronic Medical
Record (EMR), Electronic Health Record (EHR) and Personal Health
Record (PHR) and selecting the best technical among the available
Electronic sources and software before implementing. It is to guide
and make sure the technology used by the end users without any
doubts and difficulties. The idea is to evaluate is to admire the uses
and barriers of EMR-EHR-PHR. Aim and Scope: The target is to
achieve the health care providers like Physicians, Nurses, Therapists,
Medical Bill reimbursements, Insurances and Government to assess
the patient’s information on easy and systematic manner without
diluting the confidentiality of patient’s information. Method: Health
Information Technology can be implemented with the help of
Organisations providing with legal guidelines and help to stand by
the health care provider. The main objective is to select the correct
embedded and affordable database management software and
generating large-scale data. The parallel need is to know how the
latest software available in the market. Conclusion: The question lies
here is implementing the Electronic information system with
healthcare providers and organization. The clinicians are the main
users of the technology and manage us to “go paperless”. The fact is
that day today changing technologically is very sound and up to date.
Basically, the idea is to tell how to store the data electronically safe
and secure. All three exemplifies the fact that an electronic format
has its own benefit as well as barriers.
Abstract: Ambient Computing or Ambient Intelligence (AmI) is
emerging area in computer science aiming to create intelligently
connected environments and Internet of Things. In this paper, we
propose communication middleware architecture for AmI. This
middleware architecture addresses problems of communication,
networking, and abstraction of applications, although there are other
aspects (e.g. HCI and Security) within general AmI framework.
Within this middleware architecture, any application developer might
address HCI and Security issues with extensibility features of this
platform.
Abstract: In this research, we propose to conduct diagnostic and
predictive analysis about the key factors and consequences of urban
population relocation. To achieve this goal, urban simulation models
extract the urban development trends as land use change patterns from
a variety of data sources. The results are treated as part of urban big
data with other information such as population change and economic
conditions. Multiple data mining methods are deployed on this data to
analyze nonlinear relationships between parameters. The result
determines the driving force of population relocation with respect to
urban sprawl and urban sustainability and their related parameters.
This work sets the stage for developing a comprehensive urban
simulation model for catering to specific questions by targeted users. It
contributes towards achieving sustainability as a whole.
Abstract: The current web has become a modern encyclopedia,
where people share their thoughts and ideas on various topics around
them. This kind of encyclopedia is very useful for other people who
are looking for answers to their questions. However, with the
growing popularity of social networking and blogging and ever
expanding network services, there has also been a growing diversity
of technologies along with a different structure of individual web
sites. It is therefore difficult to directly find a relevant answer for a
common Internet user. This paper presents a web application for the
real-time end-to-end analysis of selected Internet trends where the
trend can be whatever the people post online. The application
integrates fully configurable tools for data collection and analysis
using selected webometric algorithms, and for its chronological
visualization to user. It can be assumed that the application facilitates
the users to evaluate the quality of various products that are
mentioned online.
Abstract: We investigate the large scale of networks in the
context of network survivability under attack. We use appropriate
techniques to evaluate and the attacker-based- and the defenderbased-
network survivability. The attacker is unaware of the operated
links by the defender. Each attacked link has some pre-specified
probability to be disconnected. The defender choice is so that to
maximize the chance of successfully sending the flow to the
destination node. The attacker however will select the cut-set with
the highest chance to be disabled in order to partition the network.
Moreover, we extend the problem to the case of selecting the best p
paths to operate by the defender and the best k cut-sets to target by
the attacker, for arbitrary integers p,k>1. We investigate some
variations of the problem and suggest polynomial-time solutions.
Abstract: Advances in spatial and spectral resolution of satellite
images have led to tremendous growth in large image databases. The
data we acquire through satellites, radars, and sensors consists of
important geographical information that can be used for remote
sensing applications such as region planning, disaster management.
Spatial data classification and object recognition are important tasks
for many applications. However, classifying objects and identifying
them manually from images is a difficult task. Object recognition is
often considered as a classification problem, this task can be
performed using machine-learning techniques. Despite of many
machine-learning algorithms, the classification is done using
supervised classifiers such as Support Vector Machines (SVM) as the
area of interest is known. We proposed a classification method,
which considers neighboring pixels in a region for feature extraction
and it evaluates classifications precisely according to neighboring
classes for semantic interpretation of region of interest (ROI). A
dataset has been created for training and testing purpose; we
generated the attributes by considering pixel intensity values and
mean values of reflectance. We demonstrated the benefits of using
knowledge discovery and data-mining techniques, which can be on
image data for accurate information extraction and classification from
high spatial resolution remote sensing imagery.
Abstract: In this paper, an attempt has been made for the design
of a robotic library using an intelligent system. The robot works on
the ARM microprocessor, motor driver circuit with 5 degrees of
freedom with Wi-Fi and GPS based communication protocol. The
authenticity of the library books is controlled by RFID. The proposed
robotic library system is facilitated with embedded system and ARM.
In this library issuance system, the previous potential readers’
authentic review reports have been taken into consideration for
recommending suitable books to the deserving new users and the
issuance of books or periodicals is based on the users’ decision. We
have conjectured that the Wi-Fi based robotic library management
system would allow fast transaction of books issuance and it also
produces quality readers.
Abstract: Test automation allows performing difficult and time
consuming manual software testing tasks efficiently, quickly and
repeatedly. However, development and maintenance of automated
tests is expensive, so it needs a proper prioritization what to automate
first. This paper describes a simple yet efficient approach for such
prioritization of test cases based on the effort needed for both manual
execution and software test automation. The suggested approach is
very flexible because it allows working with a variety of assessment
methods, and adding or removing new candidates at any time. The
theoretical ideas presented in this article have been successfully
applied in real world situations in several software companies by the
authors and their colleagues including testing of real estate websites,
cryptographic and authentication solutions, OSGi-based middleware
framework that has been applied in various systems for smart homes,
connected cars, production plants, sensors, home appliances, car head
units and engine control units (ECU), vending machines, medical
devices, industry equipment and other devices that either contain or
are connected to an embedded service gateway.
Abstract: Currently, there are few user friendly Weigh-in-
Motion (WIM) data analysis softwares available which can produce
traffic input data for the recently developed AASHTOWare pavement
Mechanistic-Empirical (ME) design software. However, these
softwares have only rudimentary Quality Control (QC) processes.
Therefore, they cannot properly deal with erroneous WIM data. As
the pavement performance is highly sensible to the quality of WIM
data, it is highly recommended to use more refined QC process on
raw WIM data to get a good result. This study develops a userfriendly
software, which can produce traffic input for the ME design
software. This software takes the raw data (Class and Weight data)
collected from the WIM station and processes it with a sophisticated
QC procedure. Traffic data such as traffic volume, traffic distribution,
axle load spectra, etc. can be obtained from this software; which can
directly be used in the ME design software.
Abstract: The Internet of Things (IoT) field has been applied in
industries with different purposes. Sensing Enterprise (SE) is an
attribute of an enterprise or a network that allows it to react to
business stimuli originating on the Internet. These fields have come
into focus recently on the enterprises, and there is some evidence of
the use and implications in supply chain management, while
finding it as an interesting aspect to work on. This paper presents a
revision and proposals of IoT applications in supply chain
management.
Abstract: Recently, Job Recommender Systems have gained
much attention in industries since they solve the problem of
information overload on the recruiting website. Therefore, we
proposed Extended Personalized Job System that has the capability of
providing the appropriate jobs for job seeker and recommending
some suitable information for them using Data Mining Techniques
and Dynamic User Profile. On the other hands, company can also
interact to the system for publishing and updating job information.
This system have emerged and supported various platforms such as
web application and android mobile application. In this paper, User
profiles, Implicit User Action, User Feedback, and Clustering
Techniques in WEKA libraries were applied and implemented. In
additions, open source tools like Yii Web Application Framework,
Bootstrap Front End Framework and Android Mobile Technology
were also applied.