Abstract: Detection, feature extraction and pose estimation of
people in images and video is made challenging by the variability of
human appearance, the complexity of natural scenes and the high
dimensionality of articulated body models and also the important
field in Image, Signal and Vision Computing in recent years. In this
paper, four types of people in 2D dimension image will be tested and
proposed. The system will extract the size and the advantage of them
(such as: tall fat, short fat, tall thin and short thin) from image. Fat
and thin, according to their result from the human body that has been
extract from image, will be obtained. Also the system extract every
size of human body such as length, width and shown them in output.
Abstract: Un-doped GaN film of thickness 1.90 mm, grown on
sapphire substrate were uniformly implanted with 325 keV Mn+ ions
for various fluences varying from 1.75 x 1015 - 2.0 x 1016 ions cm-2 at
3500 C substrate temperature. The structural, morphological and
magnetic properties of Mn ion implanted gallium nitride samples
were studied using XRD, AFM and SQUID techniques. XRD of the
sample implanted with various ion fluences showed the presence of
different magnetic phases of Ga3Mn, Ga0.6Mn0.4 and Mn4N.
However, the compositions of these phases were found to be
depended on the ion fluence. AFM images of non-implanted sample
showed micrograph with rms surface roughness 2.17 nm. Whereas
samples implanted with the various fluences showed the presence of
nano clusters on the surface of GaN. The shape, size and density of
the clusters were found to vary with respect to ion fluence. Magnetic
moment versus applied field curves of the samples implanted with
various fluences exhibit the hysteresis loops. The Curie temperature
estimated from zero field cooled and field cooled curves for the
samples implanted with the fluence of 1.75 x 1015, 1.5 x 1016 and 2.0
x 1016 ions cm-2 was found to be 309 K, 342 K and 350 K
respectively.
Abstract: A neurofuzzy approach for a given set of input-output training data is proposed in two phases. Firstly, the data set is partitioned automatically into a set of clusters. Then a fuzzy if-then rule is extracted from each cluster to form a fuzzy rule base. Secondly, a fuzzy neural network is constructed accordingly and parameters are tuned to increase the precision of the fuzzy rule base. This network is able to learn and optimize the rule base of a Sugeno like Fuzzy inference system using Hybrid learning algorithm, which combines gradient descent, and least mean square algorithm. This proposed neurofuzzy system has the advantage of determining the number of rules automatically and also reduce the number of rules, decrease computational time, learns faster and consumes less memory. The authors also investigate that how neurofuzzy techniques can be applied in the area of control theory to design a fuzzy controller for linear and nonlinear dynamic systems modelling from a set of input/output data. The simulation analysis on a wide range of processes, to identify nonlinear components on-linely in a control system and a benchmark problem involving the prediction of a chaotic time series is carried out. Furthermore, the well-known examples of linear and nonlinear systems are also simulated under the Matlab/Simulink environment. The above combination is also illustrated in modeling the relationship between automobile trips and demographic factors.
Abstract: There are many automotive accidents due to blind spots and driver inattentiveness. Blind spot is the area that is invisible to the driver's viewpoint without head rotation. Several methods are available for assisting the drivers. Simplest methods are — rear mirrors and wide-angle lenses. But, these methods have a disadvantage of the requirement for human assistance. So, the accuracy of these devices depends on driver. Another approach called an automated approach that makes use of sensors such as sonar or radar. These sensors are used to gather range information. The range information will be processed and used for detecting the collision. The disadvantage of this system is — low angular resolution and limited sensing volumes. This paper is a panoramic sensor based automotive vehicle monitoring..
Abstract: This study was conducted published to investigate
there liability of the equation pressure-impulse (PI) reinforced
concrete column inprevious studies. Equation involves three different
levels of damage criteria known as D =0. 2, D =0. 5 and D =0. 8.The
damage criteria known as a minor when 0-0.2, 0.2-0.5is known as
moderate damage, high damage known as 0.5-0.8, and 0.8-1 of the
structure is considered a failure. In this study, two types of reliability
analyzes conducted. First, using pressure-impulse equation with
different parameters. The parameters involved are the concrete
strength, depth, width, and height column, the ratio of longitudinal
reinforcement and transverse reinforcement ratio. In the first analysis
of the reliability of this new equation is derived to improve the
previous equations. The second reliability analysis involves three
types of columns used to derive the PI curve diagram using the
derived equation to compare with the equation derived from other
researchers and graph minimum standoff versus weapon yield
Federal Emergency Management Agency (FEMA). The results
showed that the derived equation is more accurate with FEMA
standards than previous researchers.
Abstract: There are only limited studies that directly correlate
the increase in reinforced concrete (RC) panel structural capacities in
resisting the blast loads with different RC panel structural properties
in terms of blast loading characteristics, RC panel dimensions, steel
reinforcement ratio and concrete material strength. In this paper,
numerical analyses of dynamic response and damage of the one-way
RC panel to blast loads are carried out using the commercial software
LS-DYNA. A series of simulations are performed to predict the blast
response and damage of columns with different level and magnitude
of blast loads. The numerical results are used to develop pressureimpulse
(P-I) diagrams of one-way RC panels. Based on the
numerical results, the empirical formulae are derived to calculate the
pressure and impulse asymptotes of the P-I diagrams of RC panels.
The results presented in this paper can be used to construct P-I
diagrams of RC panels with different concrete and reinforcement
properties. The P-I diagrams are very useful to assess panel capacities
in resisting different blast loads.
Abstract: Type 2 diabetes mellitus (T2DM) is a complex
metabolic disorder that characterized by the presence of high glucose
in blood that cause from insulin resistance and insufficiency due to
deterioration β-cell Langerhans functions. T2DM is commonly
caused by the combination of inherited genetic variations as well as
our own lifestyle. Metallothionein (MT) is a known cysteine-rich
protein responsible in helping zinc homeostasis which is important in
insulin signaling and secretion as well as protection our body from
reactive oxygen species (ROS). MT scavenged ROS and free
radicals in our body happen to be one of the reasons of T2DM and its
complications. The objective of this study was to investigate the
association of MT1A and MT2A polymorphisms between T2DM and
control subjects among Malay populations. This study involved 150
T2DM and 120 Healthy individuals of Malay ethnic with mixed
genders. The genomic DNA was extracted from buccal cells and
amplified for MT1A and MT2A loci; the 347bp and 238bp banding
patterns were respectively produced by mean of the Polymerase
Chain Reaction (PCR). The PCR products were digested with Mlucl
and Tsp451 restriction enzymes respectively and producing
fragments lengths of (158/189/347bp) and (103/135/238bp)
respectively. The ANOVA test was conducted and it shown that there
was a significant difference between diabetic and control subjects for
age, BMI, WHR, SBP, FPG, HBA1C, LDL, TG, TC and family
history with (P0.05). The genotype
frequency for AA, AG and GG of MT1A polymorphisms was 72.7%,
22.7% and 4.7% in cases and 15%, 55% and 30% in control
respectively. As for MT2A, genotype frequency of GG, GC and CC
was 42.7%, 27.3% and 30% in case and 5%, 40% and 55% for
control respectively. Both polymorphisms show significant difference
between two investigated groups with (P=0.000). The Post hoc test
was conducted and shows a significant difference between the
genotypes within each polymorphism (P=0. 000). The MT1A and
MT2A polymorphisms were believed to be the reliable molecular
markers to distinguish the T2DM subjects from healthy individuals in
Malay populations.
Abstract: In this paper, Steam Assisted Gravity Drainage
(SAGD) is introduced and its advantages over ordinary steam
injection is demonstrated. A simple simulation model is built and
three scenarios of natural production, ordinary steam injection, and
SAGD are compared in terms of their cumulative oil production and
cumulative oil steam ratio. The results show that SAGD can
significantly enhance oil production in quite a short period of time.
However, since the distance between injection and production wells
is short, the oil to steam ratio decreases gradually through time.
Abstract: Forming a legal culture among citizens is a
complicated and lengthy process, influencing all spheres of social
life. It includes promoting justice, learning rights and duties, the
introduction of juridical norms and knowledge, and also a process of
developing a system of legal acts and constitutional norms. Currently,
the evaluative and emotional influence of attempts to establish a legal
culture among the citizens of Kazakhstan is limited by real legal
practice. As a result, the values essential to a sound civil society are
absent from the consciousness of the Kazakh people who are thus, in
turn, not able to develop respect for these values. One of the
disadvantages of the modern Kazakh educational system is a
tendency to underrate the actual forces shaping the worldview of
Kazakh youths. The mass-media, which are going through a
personnel crisis, cannot provide society with the legal and political
information necessary to form the sort of legal culture required for a
true civil society.
Abstract: A new code synchronization algorithm is proposed in
this paper for the secondary cell-search stage in wideband CDMA
systems. Rather than using the Cyclically Permutable (CP) code in the
Secondary Synchronization Channel (S-SCH) to simultaneously
determine the frame boundary and scrambling code group, the new
synchronization algorithm implements the same function with less
system complexity and less Mean Acquisition Time (MAT). The
Secondary Synchronization Code (SSC) is redesigned by splitting into
two sub-sequences. We treat the information of scrambling code group
as data bits and use simple time diversity BCH coding for further
reliability. It avoids involved and time-costly Reed-Solomon (RS)
code computations and comparisons. Analysis and simulation results
show that the Synchronization Error Rate (SER) yielded by the new
algorithm in Rayleigh fading channels is close to that of the
conventional algorithm in the standard. This new synchronization
algorithm reduces system complexities, shortens the average
cell-search time and can be implemented in the slot-based cell-search
pipeline. By taking antenna diversity and pipelining correlation
processes, the new algorithm also shows its flexible application in
multiple antenna systems.
Abstract: Load forecasting has become in recent years one of the major areas of research in electrical engineering. Most traditional forecasting models and artificial intelligence neural network techniques have been tried out in this task. Artificial neural networks (ANN) have lately received much attention, and a great number of papers have reported successful experiments and practical tests. This article presents the development of an ANN-based short-term load forecasting model with improved generalization technique for the Regional Power Control Center of Saudi Electricity Company, Western Operation Area (SEC-WOA). The proposed ANN is trained with weather-related data and historical electric load-related data using the data from the calendar years 2001, 2002, 2003, and 2004 for training. The model tested for one week at five different seasons, typically, winter, spring, summer, Ramadan and fall seasons, and the mean absolute average error for one hour-ahead load forecasting found 1.12%.
Abstract: In the multi objective optimization, in the case when generated set of Pareto optimal solutions is large, occurs the problem to select of the best solution from this set. In this paper, is suggested a method to order of Pareto set. Ordering the Pareto optimal set carried out in conformity with the introduced distance function between each solution and selected reference point, where the reference point may be adjusted to represent the preferences of a decision making agent. Preference information about objective weights from a decision maker may be expressed imprecisely. The developed elicitation procedure provides an opportunity to obtain surrogate numerical weights for the objectives, and thus, to manage impreciseness of preference. The proposed method is a scalable to many objectives and can be used independently or as complementary to the various visualization techniques in the multidimensional case.
Abstract: Recent developments in storage technology and
networking architectures have made it possible for broad areas of applications to rely on data streams for quick response and accurate
decision making. Data streams are generated from events of real world so existence of associations, which are among the occurrence of these events in real world, among concepts of data streams is
logical. Extraction of these hidden associations can be useful for prediction of subsequent concepts in concept shifting data streams. In this paper we present a new method for learning association among
concepts of data stream and prediction of what the next concept will be. Knowing the next concept, an informed update of data model will be possible. The results of conducted experiments show that the proposed method is proper for classification of concept shifting data
streams.
Abstract: In this paper, we present a system for content-based
retrieval of large database of classified satellite images, based on
user's relevance feedback (RF).Through our proposed system, we
divide each satellite image scene into small subimages, which stored
in the database. The modified radial basis functions neural network
has important role in clustering the subimages of database according
to the Euclidean distance between the query feature vector and the
other subimages feature vectors. The advantage of using RF
technique in such queries is demonstrated by analyzing the database
retrieval results.
Abstract: The use of Electronic Commerce (EC)
technologies enables Small Medium Enterprises (SMEs) to improve their efficiency and competitive position. Much of the literature proposes an extensive set of benefits for
organizations that choose to adopt and implement ECommerce
systems. Factors of Business –to-business (B2B)
E-Commerce adoption and implementation have been
extensively investigated. Despite enormous attention given to encourage Small Medium Enterprises (SMEs) to adopt and
implement E-Commerce, little research has been carried out in identifying the factors of Business-to-Consumer ECommerce adoption and implementation for SMEs. To conduct the study, Tornatsky and Fleischer model was adopted
and tested in four SMEs located in Christchurch, New
Zealand. This paper explores the factors that impact the
decision and method of adoption and implementation of ECommerce
systems in automobile industry. Automobile
industry was chosen because the product they deal with i.e.
cars are not a common commodity to be sold online, despite this fact the eCommerce penetration in automobile industry is
high. The factors that promote adoption and implementation of
E-Commerce technologies are discussed, together with the
barriers. This study will help SME owners to effectively
handle the adoption and implementation process and will also
improve the chance of successful E-Commerce
implementation. The implications of the findings for
managers, consultants, and government organizations engaged in promoting E-Commerce adoption and implementation in
small businesses and future research are discussed.
Abstract: An experiment was conducted with 80 unsexed
broilers of the Arbor Acress strain to determine the capability of a
carrot and fruit juice wastes mixture (carrot, apple, manggo, avocado,
orange, melon and Dutch egg plant) in the same proportion for
replacing corn in broiler diet. This study involved a completely
randomized design (CRD) with 5 treatments (0, 5, 10, 15, and 20% of
juice wastes mixture in diets) and 4 replicates per treatment. Diets
were isonitrogenous (22% crude protein) and isocaloric (3000 kcal/kg
diet). Measured variables were feed consumption, average daily
gain, feed conversion, as well as percentages of abdominal fat pad,
carcass, digestive organs (liver, pancreas and gizzard), and heart.
Data were analyzed by analysis of variance for CRD. Increasing
juice wastes mixture levels in diets increased feed consumption
(P
Abstract: The purpose of this paper is to introduce an interactive online case-study library website developed in a national project. The design goal of the website is to provide interactive, enhanced, case-based and online educational resource for educators through the purpose and within the scope of a national project. The ADDIE instructional design model was used in the development of the website for interactive case-based library. This library is developed on a web-based platform, which is important in terms of manageability, accessibility, and updateability of data. Users are able to sort the displayed case-studies by their titles, dates, ratings, view counts, etc. The usability test is used and the expert opinion is taken for the evaluation of the website. This website is a tool to integrate technology into education. It is believed that this website will be beneficial for pre-service and in-service teachers in terms of their professional developments.
Abstract: In this research, a mathematical model for integrated evaluation of green design and green manufacturing processes is presented. To design a product, there can be alternative options to design the detailed components to fulfill the same product requirement. In the design alternative cases, the components of the product can be designed with different materials and detailed specifications. If several design alternative cases are proposed, the different materials and specifications can affect the manufacturing processes. In this paper, a new concept for integrating green design and green manufacturing processes is presented. A green design can be determined based the manufacturing processes of the designed product by evaluating the green criteria including energy usage and environmental impact, in addition to the traditional criteria of manufacturing cost. With this concept, a mathematical model is developed to find the green design and the associated green manufacturing processes. In the mathematical model, the cost items include material cost, manufacturing cost, and green related cost. The green related cost items include energy cost and environmental cost. The objective is to find the decisions of green design and green manufacturing processes to achieve the minimized total cost. In practical applications, the decision-making can be made to select a good green design case and its green manufacturing processes. In this presentation, an example product is illustrated. It shows that the model is practical and useful for integrated evaluation of green design and green manufacturing processes.
Abstract: Numerous concrete structures projects are currently running in Libya as part of a US$50 billion government funding. The
quality of concrete used in 20 different construction projects were assessed based mainly on the concrete compressive strength achieved. The projects are scattered all over the country and are at
various levels of completeness. For most of these projects, the
concrete compressive strength was obtained from test results of a
150mm standard cube mold. Statistical analysis of collected concrete
compressive strengths reveals that the data in general followed a
normal distribution pattern. The study covers comparison and assessment of concrete quality aspects such as: quality control, strength range, data standard deviation, data scatter, and ratio of minimum strength to design strength. Site quality control for these projects ranged from very good to poor according to ACI214 criteria [1]. The ranges (Rg) of the strength (max. strength – min. strength) divided by average strength are from (34% to 160%). Data scatter is
measured as the range (Rg) divided by standard deviation () and is
found to be (1.82 to 11.04), indicating that the range is ±3σ.
International construction companies working in Libya follow
different assessment criteria for concrete compressive strength in lieu
of national unified procedure. The study reveals that assessments of
concrete quality conducted by these construction companies usually
meet their adopted (internal) standards, but sometimes fail to meet
internationally known standard requirements. The assessment of
concrete presented in this paper is based on ACI, British standards
and proposed Libyan concrete strength assessment criteria.
Abstract: This paper describes the design and fabrication of a clock and data recovery circuit (CDR). We propose a new clock and data recovery which is based on a 1/4-rate frequency detector (QRFD). The proposed frequency detector helps reduce the VCO frequency and is thus advantageous for high speed application. The proposed frequency detector can achieve low jitter operation and extend the pull-in range without using the reference clock. The proposed CDR was implemented using a 1/4-rate bang-bang type phase detector (PD) and a ring voltage controlled oscillator (VCO). The CDR circuit has been fabricated in a standard 0.18 CMOS technology. It occupies an active area of 1 x 1 and consumes 90 mW from a single 1.8V supply.