Abstract: A Distributed Denial of Service (DDoS) attack is a
major threat to cyber security. It originates from the network layer or
the application layer of compromised/attacker systems which are
connected to the network. The impact of this attack ranges from the
simple inconvenience to use a particular service to causing major
failures at the targeted server. When there is heavy traffic flow to a
target server, it is necessary to classify the legitimate access and
attacks. In this paper, a novel method is proposed to detect DDoS
attacks from the traces of traffic flow. An access matrix is created
from the traces. As the access matrix is multi dimensional, Principle
Component Analysis (PCA) is used to reduce the attributes used for
detection. Two classifiers Naive Bayes and K-Nearest neighborhood
are used to classify the traffic as normal or abnormal. The
performance of the classifier with PCA selected attributes and actual
attributes of access matrix is compared by the detection rate and
False Positive Rate (FPR).
Abstract: In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.
Abstract: Environmental impacts of six 3D printers using
various materials were compared to determine if material choice
drove sustainability, or if other factors such as machine type, machine
size, or machine utilization dominate. Cradle-to-grave life-cycle
assessments were performed, comparing a commercial-scale FDM
machine printing in ABS plastic, a desktop FDM machine printing in
ABS, a desktop FDM machine printing in PET and PLA plastics, a
polyjet machine printing in its proprietary polymer, an SLA machine
printing in its polymer, and an inkjet machine hacked to print in salt
and dextrose. All scenarios were scored using ReCiPe Endpoint H
methodology to combine multiple impact categories, comparing
environmental impacts per part made for several scenarios per
machine. Results showed that most printers’ ecological impacts were
dominated by electricity use, not materials, and the changes in
electricity use due to different plastics was not significant compared
to variation from one machine to another. Variation in machine idle
time determined impacts per part most strongly. However, material
impacts were quite important for the inkjet printer hacked to print in
salt: In its optimal scenario, it had up to 1/38th the impacts coreper
part as the worst-performing machine in the same scenario. If salt
parts were infused with epoxy to make them more physically robust,
then much of this advantage disappeared, and material impacts
actually dominated or equaled electricity use. Future studies should
also measure DMLS and SLS processes / materials.
Abstract: Measurements and quantitative analysis of kinematic
parameters of human hand movements have an important role in
different areas such as hand function rehabilitation, modeling of
multi-digits robotic hands, and the development of machine-man
interfaces. In this paper the assessment and evaluation of the reachto-
grasp movement by using computerized and robot-assisted method
is described. Experiment involved the measurements of hand
positions of seven healthy subjects during grasping three objects of
different shapes and sizes. Results showed that three dominant phases
of reach-to-grasp movements could be clearly identified.
Abstract: This paper presents optimization of makespan for ‘n’
jobs and ‘m’ machines flexible job shop scheduling problem with
sequence dependent setup time using genetic algorithm (GA)
approach. A restart scheme has also been applied to prevent the
premature convergence. Two case studies are taken into
consideration. Results are obtained by considering crossover
probability (pc = 0.85) and mutation probability (pm = 0.15). Five
simulation runs for each case study are taken and minimum value
among them is taken as optimal makespan. Results indicate that
optimal makespan can be achieved with more than one sequence of
jobs in a production order.
Abstract: The purpose of this study was to reduce patient
waiting times, improve system throughput and improve resources
utilization in radiology department. A discrete event simulation
model was developed using Arena simulation software to investigate
different alternatives to improve the overall system delivery based on
adding resource scenarios due to the linkage between patient waiting
times and resource availability. The study revealed that there is no
addition investment need to procure additional scanner but hospital
management deploy managerial tactics to enhance machine
utilization and reduce the long waiting time in the department.
Abstract: In this study which has been conducted in Akçasu
Forest Range District of Devrek Forest Directorate; 3 methods (weed
control with labourer power, cover removal with Hitachi F20
Excavator, and weed control with agricultural equipment mounted on
a Ferguson 240S agriculture tractor) were utilized in weed control
efforts in regeneration of degraded oriental beech forests have been
compared. In this respect, 3 methods have been compared by
determining certain work hours and standard durations of unit areas
(1 hectare). For this purpose, evaluating the tasks made with human
and machine force from the aspects of duration, productivity and
costs, it has been aimed to determine the most productive method in
accordance with the actual ecological conditions of research field.
Within the scope of the study, the time studies have been conducted
for 3 methods used in weed control efforts. While carrying out those
studies, the performed implementations have been evaluated by
dividing them into business stages. Also, the actual data have been
used while calculating the cost accounts. In those calculations, the
latest formulas and equations which are also used in developed
countries have been utilized. The variance of analysis (ANOVA) was
used in order to determine whether there is any statistically
significant difference among obtained results, and the Duncan test
was used for grouping if there is significant difference. According to
the measurements and findings carried out within the scope of this
study, it has been found during living cover removal efforts in
regeneration efforts in demolished oriental beech forests that the
removal of weed layer in 1 hectare of field has taken 920 hours with
labourer force, 15.1 hours with excavator and 60 hours with an
equipment mounted on a tractor. On the other hand, it has been
determined that the cost of removal of living cover in unit area (1
hectare) was 3220.00 TL for labourer power, 1250 TL for excavator
and 1825 TL for equipment mounted on a tractor.
According to the obtained results, it has been found that the
utilization of excavator in weed control effort in regeneration of
degraded oriental beech regions under actual ecological conditions of
research field has been found to be more productive from both of
aspects of duration and costs. These determinations carried out
should be repeated in weed control efforts in degraded forest fields
with different ecological conditions, it is compulsory for finding the
most efficient weed control method. These findings will light the way
of technical staff of forestry directorate in determination of the most
effective and economic weed control method. Thus, the more actual
data will be used while preparing the weed control budgets, and there
will be significant contributions to national economy. Also the results of this and similar studies are very important for developing the policies for our forestry in short and long term.
Abstract: Nowadays social media information, such as news,
links, images, or VDOs, is shared extensively. However, the
effectiveness of disseminating information through social media
lacks in quality: less fact checking, more biases, and several rumors.
Many researchers have investigated about credibility on Twitter, but
there is no the research report about credibility information on
Facebook. This paper proposes features for measuring credibility on
Facebook information. We developed the system for credibility on
Facebook. First, we have developed FB credibility evaluator for
measuring credibility of each post by manual human’s labelling. We
then collected the training data for creating a model using Support
Vector Machine (SVM). Secondly, we developed a chrome extension
of FB credibility for Facebook users to evaluate the credibility of
each post. Based on the usage analysis of our FB credibility chrome
extension, about 81% of users’ responses agree with suggested
credibility automatically computed by the proposed system.
Abstract: Machining parameters are very important in
determining the surface quality of any material. In the past decade,
some new engineering materials were developed for the
manufacturing industry which created a need to conduct an
investigation on the impact of the said parameters on their surface
roughness. Polyurethane (PU) block is widely used in the automotive
industry to manufacture parts such as checking fixtures that are used
to verify the dimensional accuracy of automotive parts. In this paper,
the design of experiment (DOE) was used to investigate on the effect
of the milling parameters on the PU block. Furthermore, an analysis
of the machined surface chemical composition was done using
scanning electron microscope (SEM). It was found that the surface
roughness of the PU block is severely affected when PU undergoes a
flood machining process instead of a dry condition. In addition the
stepover and the silicon content were found to be the most significant
parameters that influence the surface quality of the PU block.
Abstract: Bamboo is extensively used in construction industry.
Low durability of bamboo due to fungus infestation and termites
attack under storage puts certain constrains for it usage as modern
structural material. Looking at many chemical formulations for
bamboo treatment leading to severe harmful environment effects,
research on eco-friendly preservatives for bamboo treatment has been
initiated world-over. In the present studies, eco-friendly preservative
for bamboo treatment has been developed. To validate its application
for structural purposes, investigation of effect of treatment on
compressive strength has been investigated. Neemoil (25%)
integrated with copper naphthenate (0.3%) on dilution with kerosene
oil impregnated into bamboo culm at 2 bar pressure, has shown
weight loss of only 3.15% in soil block analysis method. The results
from compressive strength analysis using HEICO Automatic
Compression Testing Machine reveal that preservative treatment has
not altered the structural properties of bamboo culms. Compressive
strength of control (11.72 N/mm2) and above treated samples (11.71
N/mm2) was found to be comparable.
Abstract: Red blood cells (RBC) are the most common types of
blood cells and are the most intensively studied in cell biology. The
lack of RBCs is a condition in which the amount of hemoglobin level
is lower than normal and is referred to as “anemia”. Abnormalities in
RBCs will affect the exchange of oxygen. This paper presents a
comparative study for various techniques for classifying the RBCs as
normal or abnormal (anemic) using WEKA. WEKA is an open
source consists of different machine learning algorithms for data
mining applications. The algorithms tested are Radial Basis Function
neural network, Support vector machine, and K-Nearest Neighbors
algorithm. Two sets of combined features were utilized for
classification of blood cells images. The first set, exclusively consist
of geometrical features, was used to identify whether the tested blood
cell has a spherical shape or non-spherical cells. While the second
set, consist mainly of textural features was used to recognize the
types of the spherical cells. We have provided an evaluation based on
applying these classification methods to our RBCs image dataset
which were obtained from Serdang Hospital - Malaysia, and
measuring the accuracy of test results. The best achieved
classification rates are 97%, 98%, and 79% for Support vector
machines, Radial Basis Function neural network, and K-Nearest
Neighbors algorithm respectively.
Abstract: The edge waviness in hot rolled steel is a common
defect. Variables that affect such defect include raw material and
machine. These variables are necessary to consider to understand
such defect. This research studied the defect of edge waviness for SS
400 of metal sheet manufacture. Defect of metal sheets were divided
into two groups. The specimens were investigated on chemical
composition and mechanical properties to find the difference. The
results of investigation showed that the difference was not significant.
Therefore the roll mill machine should be used to adjust to support
another location on a roller to avoide edge waviness.
Abstract: The effect of a 3-dimensional (3D) blade on the turbine
characteristics of Wells turbine for wave energy conversion has been
investigated experimentally by model testing under steady flow
conditions in this study, in order to improve the peak efficiency and
stall characteristics. The aim of use of 3D blade is to prevent flow
separation on the suction surface near the tip. The chord length is
constant with radius and the blade profile changes gradually from the
mean radius to tip. The proposed blade profiles in the study are
NACA0015 from the hub to mean radius and NACA0025 at the tip.
The performances of Wells turbine with 3D blades has been compared
with those of the original Wells turbine, i.e., the turbine with
2-dimensional (2D) blades. As a result, it was concluded that although
the peak efficiency of Wells turbine can be improved by the use of the
proposed 3D blade, its blade does not overcome the weakness of
stalling.
Abstract: Today’s modern interconnected power system is
highly complex in nature. In this, one of the most important
requirements during the operation of the electric power system is the
reliability and security. Power and frequency oscillation damping
mechanism improve the reliability. Because of power system
stabilizer (PSS) low speed response against of major fault such as
three phase short circuit, FACTs devise that can control the network
condition in very fast time, are becoming popular. But FACTs
capability can be seen in a major fault present when nonlinear models
of FACTs devise and power system equipment are applied. To realize
this aim, the model of multi-machine power system with FACTs
controller is developed in MATLAB/SIMULINK using Sim Power
System (SPS) blockiest. Among the FACTs device, Static
synchronous series compensator (SSSC) due to high speed changes
its reactance characteristic inductive to capacitive, is effective power
flow controller. Tuning process of controller parameter can be
performed using different method. But Genetic Algorithm (GA)
ability tends to use it in controller parameter tuning process. In this
paper firstly POD controller is used to power oscillation damping.
But in this station, frequency oscillation dos not has proper damping
situation. So FOD controller that is tuned using GA is using that
cause to damp out frequency oscillation properly and power
oscillation damping has suitable situation.
Abstract: The dramatic rise in the use of Social Media (SM)
platforms such as Facebook and Twitter provide access to an
unprecedented amount of user data. Users may post reviews on
products and services they bought, write about their interests, share
ideas or give their opinions and views on political issues. There is a
growing interest in the analysis of SM data from organisations for
detecting new trends, obtaining user opinions on their products and
services or finding out about their online reputations. A recent
research trend in SM analysis is making predictions based on
sentiment analysis of SM. Often indicators of historic SM data are
represented as time series and correlated with a variety of real world
phenomena like the outcome of elections, the development of
financial indicators, box office revenue and disease outbreaks. This
paper examines the current state of research in the area of SM mining
and predictive analysis and gives an overview of the analysis
methods using opinion mining and machine learning techniques.
Abstract: Quality control helps industries in improvements of its
product quality and productivity. Statistical Process Control (SPC) is
one of the tools to control the quality of products that turning practice
in bringing a department of industrial engineering process under
control. In this research, the process control of a turning
manufactured at workshops machines. The varying measurements
have been recorded for a number of samples of a rice polished
cylinder obtained from a number of trials with the turning practice.
SPC technique has been adopted by the process is finally brought
under control and process capability is improved.
Abstract: Calcium phosphate cement (CPC) is one of the most
attractive bioceramics due to its moldable and shape ability to fill
complicated bony cavities or small dental defect positions. In this
study, CPC was produced by using mixture of tetracalcium phosphate
(TTCP, Ca4O(PO4)2) and dicalcium phosphate anhydrous (DCPA,
CaHPO4) in equimolar ratio (1/1) with aqueous solutions of acetic
acid (C2H4O2) and disodium hydrogen phosphate dehydrate
(Na2HPO4.2H2O) in combination with sodium alginate in order to
improve theirs moldable characteristic. The concentration of the
aqueous solutions and sodium alginate were varied to investigate the
effect of different aqueous solutions and alginate on properties of the
cements. The cement paste was prepared by mixing cement powder
(P) with aqueous solution (L) in a P/L ratio of 1.0g/0.35ml. X-ray
diffraction (XRD) was used to analyses phase formation of the
cements. Setting time and compressive strength of the set CPCs were
measured using the Gilmore apparatus and Universal testing
machine, respectively.
The results showed that CPCs could be produced by using both
basic (Na2HPO4.2H2O) and acidic (C2H4O2) solutions. XRD results
show the precipitation of hydroxyapatite in all cement samples. No
change in phase formation among cements using difference
concentrations of Na2HPO4.2H2O solutions. With increasing
concentration of acidic solutions, samples obtained less
hydroxyapatite with a high dicalcium phosphate dehydrate leaded to
a shorter setting time. Samples with sodium alginate exhibited higher
crystallization of hydroxyapatite than that of without alginate as a
result of shorten setting time in a basic solution but a longer setting
time in an acidic solution. The stronger cement was attained from
samples using the acidic solution with sodium alginate; however the
strength was lower than that of using the basic solution.
Abstract: In new energy development, wind power has boomed.
It is due to the proliferation of wind parks and their operation in
supplying the national electric grid with low cost and clean resources.
Hence, there is an increased need to establish a proactive
maintenance for wind turbine machines based on remote control and
monitoring. That is necessary with a real-time wireless connection in
offshore or inaccessible locations while the wired method has many
flaws. The objective of this strategy is to prolong wind turbine
lifetime and to increase productivity. The hardware of a remote
control and monitoring system for wind turbine parks is designed. It
takes advantage of GPRS or Wi-Max wireless module to collect data
measurements from different wind machine sensors through IP based
multi-hop communication. Computer simulations with Proteus ISIS
and OPNET software tools have been conducted to evaluate the
performance of the studied system. Study findings show that the
designed device is suitable for application in a wind park.
Abstract: This paper presents reliability indices evaluation of the
rotor core magnetization of the induction motor operated as a self
excited induction generator by using probability distribution approach
and Monte Carlo simulation. Parallel capacitors with calculated
minimum capacitive value across the terminals of the induction motor
operated as a SEIG with unregulated shaft speed have been connected
during the experimental study. A three phase, 4 poles, 50Hz, 5.5 hp,
12.3A, 230V induction motor coupled with DC Shunt Motor was
tested in the electrical machine laboratory with variable reactive loads.
Based on this experimental study, it is possible to choose a reliable
induction machines operated as a SEIG for unregulated renewable
energy application in remote area or where grid is not available.
Failure density function, cumulative failure distribution function,
survivor function, hazard model, probability of success and
probability of failure for reliability evaluation of the three phase
induction motor operating as a SEIG have been presented graphically
in this paper.
Abstract: A novel simulation method to determine the
displacements of machine tools due to thermal factors is presented.
The specific characteristic of this method is the employment of
original CAD data from the design process chain, which is
interpreted by an algorithm in terms of geometry-based allocation of
convection and radiation parameters. Furthermore analogous models
relating to the thermal behaviour of machine elements are
automatically implemented, which were gained by extensive
experimental testing with thermography imaging. With this a
transient simulation of the thermal field and in series of the
displacement of the machine tool is possible simultaneously during
the design phase. This method was implemented and is already used
industrially in the design of machining centres in order to improve
the quality of herewith manufactured workpieces.