Abstract: Finger spelling is an art of communicating by signs
made with fingers, and has been introduced into sign language to serve
as a bridge between the sign language and the verbal language.
Previous approaches to finger spelling recognition are classified into
two categories: glove-based and vision-based approaches. The
glove-based approach is simpler and more accurate recognizing work
of hand posture than vision-based, yet the interfaces require the user to
wear a cumbersome and carry a load of cables that connected the
device to a computer. In contrast, the vision-based approaches provide
an attractive alternative to the cumbersome interface, and promise
more natural and unobtrusive human-computer interaction. The
vision-based approaches generally consist of two steps: hand
extraction and recognition, and two steps are processed independently.
This paper proposes real-time vision-based Korean finger spelling
recognition system by integrating hand extraction into recognition.
First, we tentatively detect a hand region using CAMShift algorithm.
Then fill factor and aspect ratio estimated by width and height
estimated by CAMShift are used to choose candidate from database,
which can reduce the number of matching in recognition step. To
recognize the finger spelling, we use DTW(dynamic time warping)
based on modified chain codes, to be robust to scale and orientation
variations. In this procedure, since accurate hand regions, without
holes and noises, should be extracted to improve the precision, we use
graph cuts algorithm that globally minimize the energy function
elegantly expressed by Markov random fields (MRFs). In the
experiments, the computational times are less than 130ms, and the
times are not related to the number of templates of finger spellings in
database, as candidate templates are selected in extraction step.
Abstract: Social bookmarking is an environment in which
the user gradually changes interests over time so that the tag
data associated with the current temporal period is usually more
important than tag data temporally far from the current period.
This implies that in the social tagging system, the newly tagged
items by the user are more relevant than older items. This study
proposes a novel recommender system that considers the users-
recent tag preferences. The proposed system includes the
following stages: grouping similar users into clusters using an
E-M clustering algorithm, finding similar resources based on
the user-s bookmarks, and recommending the top-N items to
the target user. The study examines the system-s information
retrieval performance using a dataset from del.icio.us, which is
a famous social bookmarking web site. Experimental results
show that the proposed system is better and more effective than
traditional approaches.
Abstract: The control of sprayer boom undesired vibrations pose a great challenge to investigators due to various disturbances and conditions. Sprayer boom movements lead to reduce of spread efficiency and crop yield. This paper describes the design of a novel control method for an active suspension system applying proportional-integral-derivative (PID) controller with an active force control (AFC) scheme integration of an iterative learning algorithm employed to a sprayer boom. The iterative learning as an intelligent method is principally used as a method to calculate the best value of the estimated inertia of the sprayer boom needed for the AFC loop. Results show that the proposed AFC-based scheme performs much better than the standard PID control technique. Also, this shows that the system is more robust and accurate.
Abstract: Sparse representation has long been studied and several
dictionary learning methods have been proposed. The dictionary
learning methods are widely used because they are adaptive. In this
paper, a new dictionary learning method for audio is proposed. Signals
are at first decomposed into different degrees of Intrinsic Mode
Functions (IMF) using Empirical Mode Decomposition (EMD)
technique. Then these IMFs form a learned dictionary. To reduce the
size of the dictionary, the K-means method is applied to the dictionary
to generate a K-EMD dictionary. Compared to K-SVD algorithm, the
K-EMD dictionary decomposes audio signals into structured
components, thus the sparsity of the representation is increased by
34.4% and the SNR of the recovered audio signals is increased by
20.9%.
Abstract: The purpose of this study is to revisit the concept of
rape as represented by professionals in the literature as well as its
perception (beliefs and attitudes) in the population at large and to
propose methodological improvements to its measurement tool. Rape
is a serious crime threatening its victim-s physical and mental health
and integrity; and as such is legally prosecuted in all modern
societies. The problem is not in accepting or rejecting rape as a
criminal act, but rather in the vagueness of its interpretations and
“justifications" maintained in the mentality of modern societies -
known in the literature as the phenomenon of "rape-myth". The rapemyth
can be studied from different perspectives: criminology,
sociology, ethics, medicine and psychology. Its investigation requires
rigorous scientific objectivity, free of passion (victims of rape are at
risk of emotional bias), free of activism (social activists, even if wellintentioned
are also biased), free of any pre-emptive assumptions or
prejudices. To apply a rigorous scientific procedure, we need a solid,
valid and reliable measurement. Rape is a form of heterosexual or
homosexual aggression, violently forcing the victim to give-in in the
sexual activity of the aggressor against her/his will. Human beings
always try to “understand" or find a reason justifying their acts.
Psychological literature provides multiple clinical and experimental
examples of it; just to mention the famous studies by Milgram on the
level of electroshock delivered by the “teacher" towards the “learner"
if “scientifically justifiable" or the studies on the behavior of
“prisoners" and the “guards" and many other experiments and field
observations. Sigmund Freud presented the phenomenon of
unconscious justification and called it rationalization. The multiple
justifications, rationalizations and repeated opinions about sexual
behavior contribute to a myth maintained in the society. What kind of
“rationale" our societies apply to “understand" the non-consensual
sexual behavior? There are many, just to mention few:
• Sex is a ludistic activity for both participants, therefore –
even if not consented – it should bring pleasure to both.
• Everybody wants sex, but only men are allowed to manifest
it openly while women have to pretend the opposite, thus men have
to initiate sexual behavior and women would follow.
• A person who strongly needs sex is free to manifest it and
struggle to get it; the person who doesn-t want it must not reveal
her/his sexual attraction and avoid risky situations; otherwise she/he
is perceived as a promiscuous seducer.
• A person who doesn-t fight against the sexual initiator
unconsciously accepts the rape (does it explain why homosexual
rapes are reported less frequently than rapes against women?).
• Women who are raped deserve it because their wardrobe is
very revealing and seducing and they ''willingly'' go to highly risky
places (alleys, dark roads, etc.).
• Men need to ventilate their sexual energy and if they are
deprived of a partner their urge to have sex is difficult to control.
• Men are supposed to initiate and insist even by force to have
sex (their testosterone makes them both sexual and aggressive).
The paper overviews numerous cultural beliefs about masculine
versus feminine behavior and their impact on the “rape myth".
Abstract: Preprocessing of speech signals is considered a crucial step in the development of a robust and efficient speech or speaker recognition system. In this paper, we present some popular statistical outlier-detection based strategies to segregate the silence/unvoiced part of the speech signal from the voiced portion. The proposed methods are based on the utilization of the 3 σ edit rule, and the Hampel Identifier which are compared with the conventional techniques: (i) short-time energy (STE) based methods, and (ii) distribution based methods. The results obtained after applying the proposed strategies on some test voice signals are encouraging.
Abstract: Many measures have been proposed for machine
translation evaluation (MTE) while little research has been done on
the performance of MTE methods. This paper is an effort for MTE
performance analysis. A general frame is proposed for the description
of the MTE measure and the test suite, including whether the
automatic measure is consistent with human evaluation, whether
different results from various measures or test suites are consistent,
whether the content of the test suite is suitable for performance
evaluation, the degree of difficulty of the test suite and its influence
on the MTE, the relationship of MTE result significance and the size
of the test suite, etc. For a better clarification of the frame, several
experiment results are analyzed relating human evaluation, BLEU
evaluation, and typological MTE. A visualization method is
introduced for better presentation of the results. The study aims for
aid in construction of test suite and method selection in MTE
practice.
Abstract: This paper considers a multi criteria cell formation
problem in Cellular Manufacturing System (CMS). Minimizing the
number of voids and exceptional elements in cells simultaneously are
two proposed objective functions. This problem is an Np-hard
problem according to the literature, and therefore, we can-t find the
optimal solution by an exact method. In this paper we developed two
ant algorithms, Ant Colony Optimization (ACO) and Max-Min Ant
System (MMAS), based on Data Envelopment Analysis (DEA). Both
of them try to find the efficient solutions based on efficiency concept
in DEA. Each artificial ant is considered as a Decision Making Unit
(DMU). For each DMU we considered two inputs, the values of
objective functions, and one output, the value of one for all of them.
In order to evaluate performance of proposed methods we provided
an experimental design with some empirical problem in three
different sizes, small, medium and large. We defined three different
criteria that show which algorithm has the best performance.
Abstract: In this paper, we consider a designed and
implemented phase-cutting dimmer. In fact, the dimmer is closed
loop and a microcontroller calculates and then regulates the firing
delay angles of each channel. Depending on the firing angle, the
harmonic distortion in the input current will not comply with
international standards, such as IEC 61000-3-2 (class C equipments).
For solving this problem, eight harmonic compensators have been
added to the dimmer. So, the proposed dimmer has a little harmonic
distortion in the input current whereas conventional phase-cutting
dimmers are not so. Sensitivity and removed THD of the proposed
dimmer will be presented.
Abstract: A. niger XP isolated from Vietnam produces very low amount of acidic phytase with optimal pH at 2.5 and 5.5. The phytase production of this strain was successfully improved through gene cloning and expression. A 1.4 - kb DNA fragment containing the coding region of the phyA gene was amplified by PCR and inserted into the expression vector pPICZαA with a signal peptide α- factor, under the control of AOX1 promoter. The recombined plasmid was transformed into the host strain P. pastoris KM71H and X33 by electroporation. Both host strains could efficiently express and secret phytase. The multicopy strains were screened for over expression of phytase. All the selected multicopy strains of P. pastoris X33 were examined for phytase activity, the maximum phytase yield of 1329 IU/ml was obtained after 4 days of incubation in medium BMM. The recombinant protein with MW of 97.4 KW showed to be the only one protein secreted in the culture broth. Multicopy transformant P. pastoris X33 supposed to be potential candidate for producing the commercial preparation of phytase.
Abstract: In this paper, we propose an improved 3D star skeleton
technique, which is a suitable skeletonization for human posture representation
and reflects the 3D information of human posture.
Moreover, the proposed technique is simple and then can be performed
in real-time. The existing skeleton construction techniques, such as
distance transformation, Voronoi diagram, and thinning, focus on the
precision of skeleton information. Therefore, those techniques are not
applicable to real-time posture recognition since they are computationally
expensive and highly susceptible to noise of boundary. Although
a 2D star skeleton was proposed to complement these problems,
it also has some limitations to describe the 3D information of the
posture. To represent human posture effectively, the constructed skeleton
should consider the 3D information of posture. The proposed 3D
star skeleton contains 3D data of human, and focuses on human action
and posture recognition. Our 3D star skeleton uses the 8 projection
maps which have 2D silhouette information and depth data of human
surface. And the extremal points can be extracted as the features of 3D
star skeleton, without searching whole boundary of object. Therefore,
on execution time, our 3D star skeleton is faster than the “greedy" 3D
star skeleton using the whole boundary points on the surface. Moreover,
our method can offer more accurate skeleton of posture than the
existing star skeleton since the 3D data for the object is concerned.
Additionally, we make a codebook, a collection of representative 3D
star skeletons about 7 postures, to recognize what posture of constructed
skeleton is.
Abstract: Deployment of pneumatic muscles in various
industrial applications is still in its early days, considering the relative
newness of these components. The field of robotics holds particular
future potential for pneumatic muscles, especially in view of their
specific behaviour known as compliance. The paper presents and
discusses an innovative constructive solution for a gripper system
mountable on an industrial robot, based on actuation by a linear
pneumatic muscle and transmission of motion by gear and rack
mechanism. The structural, operational and constructive models of
the new gripper are presented, along with some of the experimental
results obtained subsequently to the testing of a prototype. Further
presented are two control variants of the gripper system, one by
means of a 3/2-way fast-switching solenoid valve, the other by means
of a proportional pressure regulator. Advantages and disadvantages
are discussed for both variants.
Abstract: All the available algorithms for blind estimation namely constant modulus algorithm (CMA), Decision-Directed Algorithm (DDA/DFE) suffer from the problem of convergence to local minima. Also, if the channel drifts considerably, any DDA looses track of the channel. So, their usage is limited in varying channel conditions. The primary limitation in such cases is the requirement of certain overhead bits in the transmit framework which leads to wasteful use of the bandwidth. Also such arrangements fail to use channel state information (CSI) which is an important aid in improving the quality of reception. In this work, the main objective is to reduce the overhead imposed by the pilot symbols, which in effect reduces the system throughput. Also we formulate an arrangement based on certain dynamic Artificial Neural Network (ANN) topologies which not only contributes towards the lowering of the overhead but also facilitates the use of the CSI. A 2×2 Multiple Input Multiple Output (MIMO) system is simulated and the performance variation with different channel estimation schemes are evaluated. A new semi blind approach based on dynamic ANN is proposed for channel tracking in varying channel conditions and the performance is compared with perfectly known CSI and least square (LS) based estimation.
Abstract: Discharges in hydrogen, ignited by wire explosion, with current amplitude up to 1.5 MA were investigated. Channel diameter oscillations were observed on the photostreaks. Voltage and current curves correlated with the photostreaks. At initial gas pressure of 5-35 MPa the oscillation period was proportional to square root of atomic number of the initiating wire material. These oscillations were associated with aligned magnetic and gas-kinetic pressures. At initial pressure of 80-160 MPa acoustic pressure fluctuations on the discharge chamber wall were increased up to 150 MPa and there were the growth of voltage fluctuations on the discharge gap up to 3 kV simultaneously with it. In some experiments it was observed abrupt increase in the oscillation amplitude, which can be caused by the resonance of the acoustic oscillations in discharge chamber volume and the oscillations connected with alignment of the gaskinetic pressure and the magnetic pressure, as far as frequencies of these oscillations are close to each other in accordance with the estimates and the experimental data. Resonance of different type oscillations can produce energy density increasing in the discharge channel. Thus, the appropriate initial conditions in the experiment allow to increase the energy density in the discharge channel
Abstract: In this paper we present high performance
dynamically allocated multi-queue (DAMQ) buffer schemes for fault
tolerance systems on chip applications that require an interconnection
network. Two virtual channels shared the same buffer space. Fault
tolerant mechanisms for interconnection networks are becoming a
critical design issue for large massively parallel computers. It is also
important to high performance SoCs as the system complexity keeps
increasing rapidly. On the message switching layer, we make
improvement to boost system performance when there are faults
involved in the components communication. The proposed scheme is
when a node or a physical channel is deemed as faulty, the previous
hop node will terminate the buffer occupancy of messages destined
to the failed link. The buffer usage decisions are made at switching
layer without interactions with higher abstract layer, thus buffer
space will be released to messages destined to other healthy nodes
quickly. Therefore, the buffer space will be efficiently used in case
fault occurs at some nodes.
Abstract: At present, intelligent planning in the Graphplan framework is a focus of artificial intelligence. While the Creating or Destroying Objects Planning (CDOP) is one unsolved problem of this field, one of the difficulties, too. In this paper, we study this planning problem and bring forward the idea of transforming objects to propositions, based on which we offer an algorithm, Creating or Destroying Objects in the Graphplan framework (CDOGP). Compared to Graphplan, the new algorithm can solve not only the entire problems that Graphplan do, but also a part of CDOP. It is for the first time that we introduce the idea of object-proposition, and we emphasize the discussion on the representations of creating or destroying objects operator and an algorithm in the Graphplan framework. In addition, we analyze the complexity of this algorithm.
Abstract: Owing the fact that optimization of business process
is a crucial requirement to navigate, survive and even thrive in
today-s volatile business environment, this paper presents a
framework for selecting a best-fit optimization package for solving
complex business problems. Complexity level of the problem and/or
using incorrect optimization software can lead to biased solutions of
the optimization problem. Accordingly, the proposed framework
identifies a number of relevant factors (e.g. decision variables,
objective functions, and modeling approach) to be considered during
the evaluation and selection process. Application domain, problem
specifications, and available accredited optimization approaches are
also to be regarded. A recommendation of one or two optimization
software is the output of the framework which is believed to provide
the best results of the underlying problem. In addition to a set of
guidelines and recommendations on how managers can conduct an
effective optimization exercise is discussed.
Abstract: Designing a simulated system and training it to optimize its tasks in simulated environment helps the designers to avoid problems that may appear when designing the system directly in real world. These problems are: time consuming, high cost, high errors percentage and low efficiency and accuracy of the system. The proposed system will investigate and improve the efficiency and accuracy of a simulated robot to choose correct behavior to perform its task. In this paper, machine learning, which uses genetic algorithm, is adopted. This type of machine learning is called genetic-based machine learning in which a distributed classifier system is used to improve the efficiency and accuracy of the robot. Consequently, it helps the robot to achieve optimal action.
Abstract: In order to evaluate the relationship between the sulphur (S), glucose (G), nitrogen (N) and plant residues (st), sulphur immobilization and microbial transformation were monitored in five soil samples from 0-30 cm of Bastam farmers fields of Shahrood area following 11 treatments with different levels of Sulphur (S), glucose (G), N and plant residues (wheat straw) in a randomized block design with three replications and incubated over 20, 45 and 60 days, the immobilization of SO4 -2-S presented as a percentage of that added, was inversely related to its addition rate. Additions of glucose and plant residues increased with the C-to-S ratio of the added amendments, irrespective of their origins (glucose and plant residues). In the presence of C sources (glucose or plant residues). N significantly increased the immobilization of SO4 -2-S, whilst the effect of N was insignificant in the absence of a C amendment. In first few days the amounts of added SO4 -2-S immobilized were linearly correlated with the amounts of added S recovered in the soil microbial biomass. With further incubation the proportions of immobilized SO4 -2-S remaining as biomass-S decreased. Decrease in biomass-S was thought to be due to the conversion of biomass-S into soil organic-S. Glucose addition increased the immobilization (microbial utilization and incorporation into the soil organic matter) of native soil SO4 -2-S. However, N addition enhance the mineralization of soil organic-S, increasing the concentration of SO4 - 2-S in soil.
Abstract: The geometric errors in the manufacturing process can
be reduced by optimal positioning of the fixture elements in the
fixture to make the workpiece stiff. We propose a new fixture layout
optimization method N-3-2-1 for large metal sheets in this paper that
combines the genetic algorithm and finite element analysis. The
objective function in this method is to minimize the sum of the nodal
deflection normal to the surface of the workpiece. Two different
kinds of case studies are presented, and optimal position of the
fixturing element is obtained for different cases.