Abstract: High redundancy and strong uncertainty are two main characteristics for underwater robotic manipulators with unlimited workspace and mobility, but they also make the motion planning and control difficult and complex. In order to setup the groundwork for the research on control schemes, the mathematical representation is built by using the Denavit-Hartenberg (D-H) method [9]&[12]; in addition to the geometry of the manipulator which was studied for establishing the direct and inverse kinematics. Then, the dynamic model is developed and used by employing the Lagrange theorem. Furthermore, derivation and computer simulation is accomplished using the MATLAB environment. The result obtained is compared with mechanical system dynamics analysis software, ADAMS. In addition, the creation of intelligent artificial skin using Interlink Force Sensing ResistorTM technology is presented as groundwork for future work
Abstract: In this paper the development of a software to
encrypt messages with asymmetric cryptography is presented. In
particular, is used the RSA (Rivest, Shamir and Adleman) algorithm
to encrypt alphanumeric information. The software allows to
generate different public keys from two prime numbers provided by
the user, the user must then select a public-key to generate the
corresponding private-key. To encrypt the information, the user must
provide the public-key of the recipient as well as the message to be
encrypted. The generated ciphertext can be sent through an insecure
channel, so that would be very difficult to be interpreted by an
intruder or attacker. At the end of the communication, the recipient
can decrypt the original message if provide his/her public-key and
his/her corresponding private-key.
Abstract: Pineapples can be classified using an index with seven
levels of maturity based on the green and yellow color of the skin. As
the pineapple ripens, the skin will change from pale green to a golden
or yellowish color. The issues that occur in agriculture nowadays are
to do with farmers being unable to distinguish between the indexes of
pineapple maturity correctly and effectively. There are several
reasons for why farmers cannot properly follow the guideline provide
by Federal Agriculture Marketing Authority (FAMA) and one of
reason is that due to manual inspection done by experts, there are no
specific and universal guidelines to be adopted by farmers due to the
different points of view of the experts when sorting the pineapples
based on their knowledge and experience. Therefore, an automatic
system will help farmers to identify pineapple maturity effectively
and will become a universal indicator to farmers.
Abstract: This paper discusses the causal explanation capability
of QRIOM, a tool aimed at supporting learning of organic chemistry
reactions. The development of the tool is based on the hybrid use of
Qualitative Reasoning (QR) technique and Qualitative Process
Theory (QPT) ontology. Our simulation combines symbolic,
qualitative description of relations with quantity analysis to generate
causal graphs. The pedagogy embedded in the simulator is to both
simulate and explain organic reactions. Qualitative reasoning through
a causal chain will be presented to explain the overall changes made
on the substrate; from initial substrate until the production of final
outputs. Several uses of the QPT modeling constructs in supporting
behavioral and causal explanation during run-time will also be
demonstrated. Explaining organic reactions through causal graph
trace can help improve the reasoning ability of learners in that their
conceptual understanding of the subject is nurtured.
Abstract: Turbulent forced convection flow in a 2-dimensional channel over periodic grooves is numerically investigated. Finite volume method is used to study the effect of turbulence model. The range of Reynolds number varied from 10000 to 30000 for the ribheight to channel-height ratio (B/H) of 2. The downstream wall is heated by a uniform heat flux while the upstream wall is insulated. The investigation is analyzed with different types of nanoparticles such as SiO2, Al2O3, and ZnO, with water as a base fluid are used. The volume fraction is varied from 1% to 4% and the nanoparticle diameter is utilized between 20nm to 50nm. The results revealed 114% heat transfer enhancement compared to the water in a grooved channel by using SiO2 nanoparticle with volume fraction and nanoparticle diameter of 4% and 20nm respectively.
Abstract: This paper is focused on issues of nonlinear dynamic process modeling and model-based predictive control of a fed-batch sugar crystallization process applying the concept of artificial neural networks as computational tools. The control objective is to force the operation into following optimal supersaturation trajectory. It is achieved by manipulating the feed flow rate of sugar liquor/syrup, considered as the control input. A feed forward neural network (FFNN) model of the process is first built as part of the controller structure to predict the process response over a specified (prediction) horizon. The predictions are supplied to an optimization procedure to determine the values of the control action over a specified (control) horizon that minimizes a predefined performance index. The control task is rather challenging due to the strong nonlinearity of the process dynamics and variations in the crystallization kinetics. However, the simulation results demonstrated smooth behavior of the control actions and satisfactory reference tracking.
Abstract: The evolution of current modeling specifications gives rise to the problem of generating automated test cases from a variety of application tools. Past endeavours on behavioural testing of UML statecharts have not systematically leveraged the potential of existing graph theory for testing of objects. Therefore there exists a need for a simple, tool-independent, and effective method for automatic test generation. An architecture, codenamed ACUTE-J (Automated stateChart Unit Testing Engine for Java), for automating the unit test generation process is presented. A sequential approach for converting UML statechart diagrams to JUnit test classes is described, with the application of existing graph theory. Research byproducts such as a universal XML Schema and API for statechart-driven testing are also proposed. The result from a Java implementation of ACUTE-J is discussed in brief. The Chinese Postman algorithm is utilised as an illustration for a run-through of the ACUTE-J architecture.
Abstract: Quasigroups are algebraic structures closely related to
Latin squares which have many different applications. The
construction of block cipher is based on quasigroup string
transformation. This article describes a block cipher based
Quasigroup of order 256, suitable for fast software encryption of
messages written down in universal ASCII code. The novelty of this
cipher lies on the fact that every time the cipher is invoked a new set
of two randomly generated quasigroups are used which in turn is
used to create a pair of quasigroup of dual operations. The
cryptographic strength of the block cipher is examined by calculation
of the xor-distribution tables. In this approach some algebraic
operations allows quasigroups of huge order to be used without any
requisite to be stored.
Abstract: To define or predict incipient motion in an alluvial
channel, most of the investigators use a standard or modified form of
Shields- diagram. Shields- diagram does give a process to determine
the incipient motion parameters but an iterative one. To design
properly (without iteration), one should have another equation for
resistance. Absence of a universal resistance equation also magnifies
the difficulties in defining the model. Neural network technique,
which is particularly useful in modeling a complex processes, is
presented as a tool complimentary to modeling incipient motion.
Present work develops a neural network model employing the RBF
network to predict the average velocity u and water depth y based on
the experimental data on incipient condition. Based on the model,
design curves have been presented for the field application.
Abstract: In this paper, we proposed a novel receiver algorithm
for coherent underwater acoustic communications. The proposed
receiver is composed of three parts: (1) Doppler tracking and
correction, (2) Time reversal channel estimation and combining, and
(3) Joint iterative equalization and decoding (JIED). To reduce
computational complexity and optimize the equalization algorithm,
Time reversal (TR) channel estimation and combining is adopted to
simplify multi-channel adaptive decision feedback equalizer (ADFE)
into single channel ADFE without reducing the system performance.
Simultaneously, the turbo theory is adopted to form joint iterative
ADFE and convolutional decoder (JIED). In JIED scheme, the ADFE
and decoder exchange soft information in an iterative manner, which
can enhance the equalizer performance using decoding gain. The
simulation results show that the proposed algorithm can reduce
computational complexity and improve the performance of equalizer.
Therefore, the performance of coherent underwater acoustic
communications can be improved greatly.
Abstract: In wavelet regression, choosing threshold value is a crucial issue. A too large value cuts too many coefficients resulting in over smoothing. Conversely, a too small threshold value allows many coefficients to be included in reconstruction, giving a wiggly estimate which result in under smoothing. However, the proper choice of threshold can be considered as a careful balance of these principles. This paper gives a very brief introduction to some thresholding selection methods. These methods include: Universal, Sure, Ebays, Two fold cross validation and level dependent cross validation. A simulation study on a variety of sample sizes, test functions, signal-to-noise ratios is conducted to compare their numerical performances using three different noise structures. For Gaussian noise, EBayes outperforms in all cases for all used functions while Two fold cross validation provides the best results in the case of long tail noise. For large values of signal-to-noise ratios, level dependent cross validation works well under correlated noises case. As expected, increasing both sample size and level of signal to noise ratio, increases estimation efficiency.
Abstract: In this paper, we are going to determine the threshold levels of adaptive modulation in a burst by burst CDMA system by a suboptimum method so that the above method attempts to increase the average bit per symbol (BPS) rate of transceiver system by switching between the different modulation modes in variable channel condition. In this method, we choose the minimum values of average bit error rate (BER) and maximum values of average BPS on different values of average channel signal to noise ratio (SNR) and then calculate the relative threshold levels of them, so that when the instantaneous SNR increases, a higher order modulation be employed for increasing throughput and vise-versa when the instantaneous SNR decreases, a lower order modulation be employed for improvement of BER. In transmission step, by this adaptive modulation method, in according to comparison between obtained estimation of pilot symbols and a set of above suboptimum threshold levels, above system chooses one of states no transmission, BPSK, 4QAM and square 16QAM for modulation of data. The expected channel in this paper is a slow Rayleigh fading.
Abstract: The study of morphometric and histologic evolutions
of the Bursa of Fabricus during 27 weeks of post-hashing age,
realized on 88 subjects of broiler chicken they permitted to collect
information about the morpho-histological aspect according to their
post-hashing age; showed the size and the weight of the Bursa of
Fabricius which reach their maximum between the 10th and the 11th
week of age and the physiologic involution phenomena. These
variations are in close relationship to the sexual maturity. These
results can be used in the diagnosis of viral disease such as the
Gumboro disease, Marek disease.
Abstract: The aim of this paper is to compare the effectiveness and electrochemical behavior of typical oilfield corrosion inhibitors with previous oilfield corrosion inhibitors under the same electrochemical techniques to control preferential weld corrosion of X65 pipeline steel in artificial seawater saturated with carbon dioxide at a pressure of one bar. A secondary aim is to investigate the conditions under which current reversal takes place. A flow channel apparatus was used in the laboratory to simulate the actual condition that occurs in marine pipelines. Different samples from the parent metal, the weld metal and the heat affected zone in the pipeline steel were galvanically coupled. The galvanic currents flowing between the weld regions were recorded using zero-resistance ammeters and tested under static and flowing conditions in both inhibited and uninhibited media. The results show that a current reversal took place when 30ppm of both green oilfield inhibitors were present, resulting in accelerated weld corrosion.
Abstract: The evaluation of conversational agents or chatterbots question answering systems is a major research area that needs much attention. Before the rise of domain-oriented conversational agents based on natural language understanding and reasoning, evaluation is never a problem as information retrieval-based metrics are readily available for use. However, when chatterbots began to become more domain specific, evaluation becomes a real issue. This is especially true when understanding and reasoning is required to cater for a wider variety of questions and at the same time to achieve high quality responses. This paper discusses the inappropriateness of the existing measures for response quality evaluation and the call for new standard measures and related considerations are brought forward. As a short-term solution for evaluating response quality of conversational agents, and to demonstrate the challenges in evaluating systems of different nature, this research proposes a blackbox approach using observation, classification scheme and a scoring mechanism to assess and rank three example systems, AnswerBus, START and AINI.
Abstract: Where renewable energy sources, solar, hydro, wind are available the remote communities and businesses can be provided with the most reliable and affordable source of electrical energy. This paper presents a model of safari rest contains all the necessary services for the interested tourists who visit the safari Sinai desert. The PV energy system provides the rural energy needs of remote communities. A photovoltaic renewable energy system is designed to feed the global Ac and Dc electrical required load of this safari rest . The benefits of photovoltaic renewable energy at rural applications are its versatility and convenience. This model of safari rest must be taken in consideration by Egyptian Government as it will provide the tourism plane by new interested tourism field which put a big spot on Red sea area: El Ghordaka.
Abstract: This paper addresses the problem of recognizing and
interpreting the behavior of human workers in industrial
environments for the purpose of integrating humans in software
controlled manufacturing environments. In this work we propose a
generic concept in order to derive solutions for task-related manual
production applications. Thus, we are able to use a versatile concept
providing flexible components and being less restricted to a specific
problem or application. We instantiate our concept in a spot welding
scenario in which the behavior of a human worker is interpreted
when performing a welding task with a hand welding gun. We
acquire signals from inertial sensors, video cameras and triggers and
recognize atomic actions by using pose data from a marker based
video tracking system and movement data from inertial sensors.
Recognized atomic actions are analyzed on a higher evaluation level
by a finite state machine.
Abstract: The toxicity of aqueous extracts of two plants,
Nicotiana tobacum and Eucalyptus globulus were investigated against second instar larvae of Lycoriella auripila, one of the most
important pests of button mushroom, using agar dilution technique.
Seven concentrations of aqueous extracts of both plants were applied
on second instar larvae and their mortality were evaluated after 24, 48 and 72 h. The obtained results revealed that aqueous extracts of N.
tabacum and E. globulus caused 77.55 and 72.5% mortality of larvae
of L. auripila at concentration of 4000 ppm after 72h, respectively. Toxicities of tobacco extract after 24, 48 and 72 h were 1.52, 1.85
and 1.70 times greather than eucalyptus, respectively. The estimated LC50 after 24, 48 and 72 h were 7316.5, 2468.5 and 2013.1 ppm for
tobacco and 64870.0, 6839.5 and 3326.4 ppm for eucalyptus, respectively. These plants merit further study as potential insecticides
for the control of L. auripila.
Abstract: Fuel cells have become one of the major areas of
research in the academia and the industry. The goal of most fish
farmers is to maximize production and profits while holding labor
and management efforts to the minimum. Risk of fish kills, disease
outbreaks, poor water quality in most pond culture operations,
aeration offers the most immediate and practical solution to water
quality problems encountered at higher stocking and feeding rates.
Many units of aeration system are electrical units so using a
continuous, high reliability, affordable, and environmentally friendly
power sources is necessary. Aeration of water by using PEM fuel cell
power is not only a new application of the renewable energy, but
also, it provides an affordable method to promote biodiversity in
stagnant ponds and lakes. This paper presents a new design and
control of PEM fuel cell powered a diffused air aeration system for a
shrimp farm in Mersa Matruh in Egypt. Also Artificial intelligence
(AI) techniques control is used to control the fuel cell output power
by control input gases flow rate. Moreover the mathematical
modeling and simulation of PEM fuel cell is introduced. A
comparison study is applied between the performance of fuzzy logic
control (FLC) and neural network control (NNC). The results show
the effectiveness of NNC over FLC.
Abstract: This paper is devoted to present and discuss a model that allows a local segmentation by using statistical information of a given image. It is based on Chan-Vese model, curve evolution, partial differential equations and binary level sets method. The proposed model uses the piecewise constant approximation of Chan-Vese model to compute Signed Pressure Force (SPF) function, this one attracts the curve to the true object(s)-s boundaries. The implemented model is used to extract weld defects from weld radiographic images in the aim to calculate the perimeter and surfaces of those weld defects; encouraged resultants are obtained on synthetic and real radiographic images.