Abstract: Adaptive e-learning today gives the student a central
role in his own learning process. It allows learners to try things out,
participate in courses like never before, and get more out of learning
than before. In this paper, an adaptive e-learning model for logic
design, simplification of Boolean functions and related fields is
presented. Such model presents suitable courses for each student in a
dynamic and adaptive manner using existing database and workflow
technologies. The main objective of this research work is to provide
an adaptive e-learning model based learners' personality using
explicit and implicit feedback. To recognize the learner-s, we develop
dimensions to decide each individual learning style in order to
accommodate different abilities of the users and to develop vital
skills. Thus, the proposed model becomes more powerful, user
friendly and easy to use and interpret. Finally, it suggests a learning
strategy and appropriate electronic media that match the learner-s
preference.
Abstract: Climate change causes severe effects on natural
habitats, especially wetlands. These challenges require the adaptation
of their management to probable effects of climate change. A
compilation of necessary changes in land management was collected
in a Hungarian area being both national park and Natura 2000 SAC
and SCI site in favor of increasing the resilience and reducing
vulnerability. Several factors, such as ecological aspects, nature
conservation and climatic adaptation should be combined with social
and economic factors during the process of developing climate
change adapted management on vulnerable wetlands. Planning
adaptive management should be determined by a priority order of
conservation aims and evaluation of factors at the determined
planning unit. Mowing techniques, frequency and exact date should
be observed as well as grazing species and their breed, due to
different grazing, group forming and trampling habits. Integrating
landscape history and historical land development into the planning
process is essential.
Abstract: In this paper we present a Adaptive Neuro-Fuzzy
System (ANFIS) with inputs the lagged dependent variable for the
prediction of Gross domestic Product growth rate in six countries.
We compare the results with those of Autoregressive (AR) model.
We conclude that the forecasting performance of neuro-fuzzy-system
in the out-of-sample period is much more superior and can be a very
useful alternative tool used by the national statistical services and the
banking and finance industry.
Abstract: Stegnography is a new way of secret
communication the most widely used mechanism on account
of its simplicity is the use of the least significant bit. We have
used the least significant bit (2 LSB and 4 LSB) substitution
method. Depending upon the characteristics of the individual
portions of cover image we decide whether to use 2 LSB or 4
LSB thus it is an adaptive stegnography technique. We used
one of the three channels to behave as indicator to indicate the
presence of hidden data in other two channels. The module
showed impressive results in terms of capacity to hide the
data. In proposed method, instead of using RGB color space
directly, YCbCr color space is used to make use of human
visual system characteristic.
Abstract: The objective of this study was to investigate the effects of dietary supplementation with raw or heat-treated sunflower oil seed with two levels of 7.5% or 15% on unsaturated fatty acids in milk fat and performances of high-yielding lactating cows. Twenty early lactating Holstein cows were used in a complete randomized design. Treatments included: 1) CON, control (without sunflower oil seed). 2) LS-UT, 7.5% raw sunflower oil seed. 3) LS-HT, 7.5% heat-treated sunflower oil seed. 4) HS-UT, 15% raw sunflower oil seed. 5) HS-HT, 15% heat-treated sunflower oil seed. Experimental period lasted for 4 wk, with first 2 wk used for adaptation to the diets. Supplementation with 7.5% raw sunflower seed (LS-UT) tended to decrease milk yield, with 28.37 kg/d compared with the control (34.75 kg/d). Milk fat percentage was increased with the HS-UT treatment that obtained 3.71% compared with CON that was 3.39% and without significant different. Milk protein percent was decreased high level sunflower oil seed treatments (15%) with 3.18% whereas CON treatment is caused 3.40% protein. The cows fed added low sunflower heat-treated (LS-HT) produced milk with the highest content of total unsaturated fatty acid with 32.59 g/100g of milk fat compared with the HS-UT with 23.59 g/100g of milk fat. Content of C18 unsaturated fatty acids in milk fat increased from 21.68 g/100g of fat in the HS-UT to 22.50, 23.98, 27.39 and 30.30 g/100g of fat from the cow fed HS-HT, CON, LS-UT and LS-HT treatments, respectively. C18:2 isomers of fatty acid in milk were greater by LSHT supplementation with significant effect (P < 0.05). Total of C18 unsaturated fatty acids content was significantly higher in milk of animal fed added low heat-treated sunflower (7.5%) than those fed with high sunflower. In all, results of this study showed that diet cow's supplementation with sunflower oil seed tended to reduce milk production of lactating cows but can improve C18 UFA (Unsaturated Fatty Acid) content in milk fat. 7.5% level of sunflower oil seed that heated seemed to be the optimal source to increase UFA production.
Abstract: Removing noise from the any processed images is very important. Noise should be removed in such a way that important information of image should be preserved. A decisionbased nonlinear algorithm for elimination of band lines, drop lines, mark, band lost and impulses in images is presented in this paper. The algorithm performs two simultaneous operations, namely, detection of corrupted pixels and evaluation of new pixels for replacing the corrupted pixels. Removal of these artifacts is achieved without damaging edges and details. However, the restricted window size renders median operation less effective whenever noise is excessive in that case the proposed algorithm automatically switches to mean filtering. The performance of the algorithm is analyzed in terms of Mean Square Error [MSE], Peak-Signal-to-Noise Ratio [PSNR], Signal-to-Noise Ratio Improved [SNRI], Percentage Of Noise Attenuated [PONA], and Percentage Of Spoiled Pixels [POSP]. This is compared with standard algorithms already in use and improved performance of the proposed algorithm is presented. The advantage of the proposed algorithm is that a single algorithm can replace several independent algorithms which are required for removal of different artifacts.
Abstract: In this paper, an adaptive polarized Multiple-Input
Multiple-Output (MIMO) Multicarrier Spread Spectrum Code Division Multiple Access (MC-SS-CDMA) system is designed for downlink mobile communications. The proposed system will be
examined in Frequency Division Duplex (FDD) mode for both macro urban and suburban environments. For the same transmission
bandwidth, a performance comparison between both nonoverlapped and orthogonal Frequency Division Multiplexing (FDM) schemes will be presented. Also, the proposed system will be compared with
both the closed loop vertical MIMO MC-SS-CDMA system and the
synchronous vertical STBC-MIMO MC-SS-CDMA system. As will
be shown, the proposed system introduces a significant performance
gain as well as reducing the spatial dimensions of the MIMO system
and simplifying the receiver implementation. The effect of the
polarization diversity characteristics on the BER performance will be
discussed. Also, the impact of excluding the cross-polarization MCSS-
CDMA blocks in the base station will be investigated. In addition,
the system performance will be evaluated under different Feedback
Information (FBI) rates for slowly-varying channels. Finally, a
performance comparison for vehicular and pedestrian environments
will be presented
Abstract: Hospital staff and managers are under pressure and
concerned for effective use and management of scarce resources. The
hospital admissions require many decisions that have complex and
uncertain consequences for hospital resource utilization and patient
flow. It is challenging to predict risk of admissions and length of stay
of a patient due to their vague nature. There is no method to capture
the vague definition of admission of a patient. Also, current methods
and tools used to predict patients at risk of admission fail to deal with
uncertainty in unplanned admission, LOS, patients- characteristics.
The main objective of this paper is to deal with uncertainty in
health system variables, and handles uncertain relationship among
variables. An introduction of machine learning techniques along with
statistical methods like Regression methods can be a proposed
solution approach to handle uncertainty in health system variables. A
model that adapts fuzzy methods to handle uncertain data and
uncertain relationships can be an efficient solution to capture the
vague definition of admission of a patient.
Abstract: The story of Alibaba demonstrates a credible example of how a small start-up company can eventually make it big in the global economy through the Internet. This case study does not attempt to present Alibaba as a perfect formula; rather, it discusses the strategies carried out by the firm and, in the process, culls out the important lessons that can guide start-ups and aspiring entrepreneurs in the complex world of online trading. Similar to the interesting and exotic Asian cuisine that continuously evolves from the diversity of Asia-s people and their unique culture and personality, Alibaba has successfully transformed itself over the years, adapting to the changes in and demands of online businessto- business (B2B) commerce.
Abstract: In this work, we study the problem of determining
the minimum scheduling length that can satisfy end-to-end (ETE)
traffic demand in scheduling-based multihop WSNs with cooperative
multiple-input multiple-output (MIMO) transmission scheme. Specifically,
we present a cross-layer formulation for the joint routing,
scheduling and stream control problem by incorporating various
power and rate adaptation schemes, and taking into account an
antenna beam pattern model and the signal-to-interference-and-noise
(SINR) constraint at the receiver. In the context, we also propose
column generation (CG) solutions to get rid of the complexity
requiring the enumeration of all possible sets of scheduling links.
Abstract: Using Internet communication, new home electronics
have functions of monitoring and control from remote. However in
many case these electronics work as standalone, and old electronics
are not followed. Then, we developed the total remote system include
not only new electronics but olds. This systems node is a adapter of
electrical power plug that embed relay switch and some sensors, and
these nodes communicate with each other. the system server was build
on the Internet, and users access to this system from web browsers.
To reduce the cost to set up of this system, communication between
adapters are used ZigBee wireless network instead of wired LAN
cable[3]. From measured RSSI(received signal strength indicator)
information between each nodes, the system can estimate roughly
adapters were mounted on which room, and where in the room. So
also it reduces the cost of mapping nodes. Using this system, energy
saving and house monitoring are expected.
Abstract: Workflow Management Systems (WfMS) alloworganizations to streamline and automate business processes and reengineer their structure. One important requirement for this type of system is the management and computation of the Quality of Service(QoS) of processes and workflows. Currently, a range of Web processes and workflow languages exist. Each language can be characterized by the set of patterns they support. Developing andimplementing a suitable and generic algorithm to compute the QoSof processes that have been designed using different languages is a difficult task. This is because some patterns are specific to particular process languages and new patterns may be introduced in future versions of a language. In this paper, we describe an adaptive algorithm implemented to cope with these two problems. The algorithm is called adaptive since it can be dynamically changed as the patterns of a process language also change.
Abstract: Microstrip lines, widely used for good reason, are
broadband in frequency and provide circuits that are compact and
light in weight. They are generally economical to produce since they
are readily adaptable to hybrid and monolithic integrated circuit (IC)
fabrication technologies at RF and microwave frequencies. Although,
the existing EM simulation models used for the synthesis and
analysis of microstrip lines are reasonably accurate, they are
computationally intensive and time consuming. Neural networks
recently gained attention as fast and flexible vehicles to microwave
modeling, simulation and optimization. After learning and
abstracting from microwave data, through a process called training,
neural network models are used during microwave design to provide
instant answers to the task learned.This paper presents simple and
accurate ANN models for the synthesis and analysis of Microstrip
lines to more accurately compute the characteristic parameters and
the physical dimensions respectively for the required design
specifications.
Abstract: In the paper an effective context based lossless coding
technique is presented. Three principal and few auxiliary contexts are
defined. The predictor adaptation technique is an improved CoBALP
algorithm, denoted CoBALP+. Cumulated predictor error combining
8 bias estimators is calculated. It is shown experimentally that
indeed, the new technique is time-effective while it outperforms the
well known methods having reasonable time complexity, and is
inferior only to extremely computationally complex ones.
Abstract: A direct adaptive controller for a class of unknown nonlinear discrete-time systems is presented in this article. The proposed controller is constructed by fuzzy rules emulated network (FREN). With its simple structure, the human knowledge about the plant is transferred to be if-then rules for setting the network. These adjustable parameters inside FREN are tuned by the learning mechanism with time varying step size or learning rate. The variation of learning rate is introduced by main theorem to improve the system performance and stabilization. Furthermore, the boundary of adjustable parameters is guaranteed through the on-line learning and membership functions properties. The validation of the theoretical findings is represented by some illustrated examples.
Abstract: This paper presents an adaptive motion estimator
that can be dynamically reconfigured by the best algorithm
depending on the variation of the video nature during the lifetime
of an application under running. The 4 Step Search (4SS) and the
Gradient Search (GS) algorithms are integrated in the estimator in
order to be used in the case of rapid and slow video sequences
respectively. The Full Search Block Matching (FSBM) algorithm
has been also integrated in order to be used in the case of the
video sequences which are not real time oriented.
In order to efficiently reduce the computational cost while
achieving better visual quality with low cost power, the proposed
motion estimator is based on a Variable Block Size (VBS) scheme
that uses only the 16x16, 16x8, 8x16 and 8x8 modes.
Experimental results show that the adaptive motion estimator
allows better results in term of Peak Signal to Noise Ratio
(PSNR), computational cost, FPGA occupied area, and dissipated
power relatively to the most popular variable block size schemes
presented in the literature.
Abstract: In the paper we discuss the influence of the route
flexibility degree, the open rate of operations and the production type
coefficient on makespan. The flexible job-open shop scheduling
problem FJOSP (an extension of the classical job shop scheduling) is
analyzed. For the analysis of the production process we used a
hybrid heuristic of the GRASP (greedy randomized adaptive search
procedure) with simulated annealing algorithm. Experiments with
different levels of factors have been considered and compared. The
GRASP+SA algorithm has been tested and illustrated with results for
the serial route and the parallel one.
Abstract: The “conveyor belt" as a product represents a
complex high performance component with a wide range of different
applications. Further development of these highly complex
components demands an integration of new technologies and new
enhanced materials. In this context nanostructured fillers appear to
have a more promising effect on the performance of the conveyor
belt composite than conventional micro-scaled fillers.
Within the project “DotTrans" nanostructured fillers, for example
silicon dioxide, are used to optimize performance parameters of
conveyor belt systems. The objective of the project includes
operating parameters like energy consumption or friction
characteristics as well as adaptive parameters like cut or wear
resistance.
Abstract: Creativity is often based on an unorthodox
recombination of knowledge; in fact: 80% of all innovations use
given knowledge and put it into a new combination. Cross-industry
innovations follow this way of thinking and bring together problems
and solution ideas from different industries. Therefore analogies and
search strategies have to be developed. Taking this path, the
questions where to search, what to search and how to search have to
be answered. Afterwards, the gathered information can be used
within a planned search process. Identified solution ideas have to be
assessed and analyzed in detail for the success promising adaption
planning.
Abstract: Springback is a significant problem in the sheet metal
forming process. When the tools are released after the stage of
forming, the product springs out, because of the action of the internal
stresses. In many cases the deviation of form is too large and the
compensation of the springback is necessary. The precise prediction
of the springback of product is increasingly significant for the design
of the tools and for compensation because of the higher ratio of the
yield stress to the elastic modulus.
The main object in this paper was to study the effect of the
anisotropy on the springback for three directions of rolling: 0°, 45°
and 90°. At the same time, we highlighted the influence of three
different metallic materials: Aluminum, Steel and Galvanized steel.
The original of our purpose consist on tests which are ensured by
adapting a U-type stretching-bending device on a tensile testing
machine, where we studied and quantified the variation of the
springback according to the direction of rolling. We also showed the
role of lubrication in the reduction of the springback.
Moreover, in this work, we have studied important characteristics
in deep drawing process which is a springback. We have presented
defaults that are showed in this process and many parameters
influenced a springback.
Finally, our results works lead us to understand the influence of
grains orientation with different metallic materials on the springback
and drawing some conclusions how to concept deep drawing tools. In
addition, the conducted work represents a fundamental contribution
in the discussion the industry application.