Abstract: The article deals with technical support of intracranial single unit activity measurement. The parameters of the whole measuring set were tested in order to assure the optimal conditions of extracellular single-unit recording. Metal microelectrodes for measuring the single-unit were tested during animal experiments. From signals recorded during these experiments, requirements for the measuring set parameters were defined. The impedance parameters of the metal microelectrodes were measured. The frequency-gain and autonomous noise properties of preamplifier and amplifier were verified. The measurement and the description of the extracellular single unit activity could help in prognoses of brain tissue damage recovery.
Abstract: Availability of high dimensional biological datasets such as from gene expression, proteomic, and metabolic experiments can be leveraged for the diagnosis and prognosis of diseases. Many classification methods in this area have been studied to predict disease states and separate between predefined classes such as patients with a special disease versus healthy controls. However, most of the existing research only focuses on a specific dataset. There is a lack of generic comparison between classifiers, which might provide a guideline for biologists or bioinformaticians to select the proper algorithm for new datasets. In this study, we compare the performance of popular classifiers, which are Support Vector Machine (SVM), Logistic Regression, k-Nearest Neighbor (k-NN), Naive Bayes, Decision Tree, and Random Forest based on mock datasets. We mimic common biological scenarios simulating various proportions of real discriminating biomarkers and different effect sizes thereof. The result shows that SVM performs quite stable and reaches a higher AUC compared to other methods. This may be explained due to the ability of SVM to minimize the probability of error. Moreover, Decision Tree with its good applicability for diagnosis and prognosis shows good performance in our experimental setup. Logistic Regression and Random Forest, however, strongly depend on the ratio of discriminators and perform better when having a higher number of discriminators.
Abstract: Mathematical models can be used to describe the
transmission of disease. Dengue disease is the most significant
mosquito-borne viral disease of human. It now a leading cause of
childhood deaths and hospitalizations in many countries. Variations
in environmental conditions, especially seasonal climatic parameters,
effect to the transmission of dengue viruses the dengue viruses and
their principal mosquito vector, Aedes aegypti. A transmission model
for dengue disease is discussed in this paper. We assume that the
human and vector populations are constant. We showed that the local
stability is completely determined by the threshold parameter, 0 B . If
0 B is less than one, the disease free equilibrium state is stable. If
0 B is more than one, a unique endemic equilibrium state exists and
is stable. The numerical results are shown for the different values of
the transmission probability from vector to human populations.
Abstract: In this paper, we consider components of discrete event imitating model, implementing a simulation model by using JAVA and performing an input analysis of the data and an output analysis of the simulation results. Was lead development of imitating model of mass service system with n (n≥1) devices of service. On the basis of the developed process of a multithreading simulated the distributed processes with presence of synchronization. Was developed the algorithm of event-oriented simulation, was received results of system functioning with n devices of service.
Abstract: As business environments are rapidly changing,
the manufacturing system must be reconfigured to adapt to
various customer needs. In order to cope with this challenge, it
is quintessential to test industrial control logic rapidly and
easily in the design time, and monitor operational behavior in
the run time of automated manufacturing system. Proposed
integrated model for virtual prototyping and operational
monitoring of industrial control logic is to improve limitations
of current ladder programming practices and general discrete
event simulation method. Each plant layout model using HMI
package and object-oriented control logic model is designed
independently and is executed simultaneously in integrated
manner to reflect design practices of automation system in the
design time. Control logic is designed and executed using UML
activity diagram without considering complicated control
behavior to deal with current trend of reconfigurable
manufacturing. After the physical installation, layout model of
virtual prototype constructed in the design time is reused for
operational monitoring of system behavior during run time.
Abstract: System-level design based on high-level abstractions
is becoming increasingly important in hardware and embedded
system design. This paper analyzes meta-design techniques oriented
at developing meta-programs and meta-models for well-understood
domains. Meta-design techniques include meta-programming and
meta-modeling. At the programming level of design process, metadesign
means developing generic components that are usable in a
wider context of application than original domain components. At the
modeling level, meta-design means developing design patterns that
describe general solutions to the common recurring design problems,
and meta-models that describe the relationship between different
types of design models and abstractions. The paper describes and
evaluates the implementation of meta-design in hardware design
domain using object-oriented and meta-programming techniques.
The presented ideas are illustrated with a case study.
Abstract: A novel path planning approach is presented to solve
optimal path in stochastic, time-varying networks under priori traffic
information. Most existing studies make use of dynamic programming
to find optimal path. However, those methods are proved to
be unable to obtain global optimal value, moreover, how to design
efficient algorithms is also another challenge.
This paper employs a decision theoretic framework for defining
optimal path: for a given source S and destination D in urban transit
network, we seek an S - D path of lowest expected travel time
where its link travel times are discrete random variables. To solve
deficiency caused by the methods of dynamic programming, such as
curse of dimensionality and violation of optimal principle, an integer
programming model is built to realize assignment of discrete travel
time variables to arcs. Simultaneously, pruning techniques are also
applied to reduce computation complexity in the algorithm. The final
experiments show the feasibility of the novel approach.
Abstract: In modern distributed software systems, the issue of communication among composing parts represents a critical point, but the idea of extending conventional programming languages with general purpose communication constructs seems difficult to realize. As a consequence, there is a (growing) gap between the abstraction level required by distributed applications and the concepts provided by platforms that enable communication. This work intends to discuss how the Model Driven Software Development approach can be considered as a mature technology to generate in automatic way the schematic part of applications related to communication, by providing at the same time high level specialized languages useful in all the phases of software production. To achieve the goal, a stack of languages (meta-meta¬models) has been introduced in order to describe – at different levels of abstraction – the collaborative behavior of generic entities in terms of communication actions related to a taxonomy of messages. Finally, the generation of platforms for communication is viewed as a form of specification of language semantics, that provides executable models of applications together with model-checking supports and effective runtime environments.
Abstract: In the present work flow past circular cylinder and
cylinder with rectangular and triangular wake splitter is studied to
improve aerodynamic parameters. The Comparison of drag
coefficient is tabulated for bare cylinder, cylinder with rectangular
and triangular wake splitters. Flow past circular cylinder and cylinder
with triangular and rectangular wake splitter is performed at
Reynoldsnumber 5, 20, 40, 50,80, 100.An incompressible PISO finite
volume code employing a non-staggered grid arrangement is used, a
second order upwind scheme is used for convective terms. The time
discretization is implicit and a Second order Crank-Nicholson scheme
is employed. Length of wake splitter in both configurations is taken
to be equal to diameter of cylinder. Wake length is found to be less
with rectangular wake splitter when compared to bare cylinder and
cylinder with triangular wake splitter. Coefficient of drag is found to
be less for triangular wake splitter when compared to bare cylinder &
cylinder with rectangular wake splitter.
Abstract: This paper discusses a discrete event simulation model
for the availability analysis of weapon systems. This model
incorporates missions, operational tasks and system reliability
structures to analyze the availability of a weapon system. The
proposed simulation model consists of 5 modules: Simulation Engine,
Maintenance Organizations, System, its Mission Profile and RBD
which are based on missions and operational tasks. Simulation Engine
executes three kinds of discrete events in chronological order. The
events are mission events generated by Mission Profile, failure events
generated by System, and maintenance events executed by
Maintenance Organization. Finally, this paper shows the case study of
a system's availability analysis and mission reliability using the
simulation model.
Abstract: During this day a considerable amount of Leachate is produced with high amounts of organic material and nutrients needed plants. This study has done in order to scrutinize the effect of Leachate compost on the pH, EC and organic matter percentage in the form of statistical Factorial plan through randomizing block design with three main and two minor treatments and also three replications during three six month periods. Major treatments include N: Irrigation with the region-s well water as a control, I: Frequent irrigation with well water and Leachate, C: Mixing Leachate and water well (25 percent leachate + 75 percent ordinary well water) and secondary treatments, include DI: surface drip irrigation and SDI: sub surface drip irrigation. Results of this study indicated significant differences between treatments and also there were mixing up with the control treatment in the reduction of pH, increasing soluble salts and also increasing the organic matter percentage. This increase is proportional to the amount of added Leachate and in the treatment also proportional to higher mixture of frequent treatment. Therefore, since creating an acidic pH increases the ability to absorb some nutrient elements such as phosphorus, iron, zinc, copper and manganese are increased and the other hand, organic materials also improve many physical and chemical properties of soil are used in Leachate trash Consider health issues as refined in the green belts around cities as a liquid fertilizer recommended.
Abstract: Car failure detection is a complicated process and
requires high level of expertise. Any attempt of developing an expert
system dealing with car failure detection has to overcome various
difficulties. This paper describes a proposed knowledge-based
system for car failure detection. The paper explains the need for an
expert system and the some issues on developing knowledge-based
systems, the car failure detection process and the difficulties involved
in developing the system. The system structure and its components
and their functions are described. The system has about 150 rules for
different types of failures and causes. It can detect over 100 types of
failures. The system has been tested and gave promising results.
Abstract: This paper describes a system-level SoC energy
consumption estimation method based on a dynamic behavior of
embedded software in the early stages of the SoC development. A
major problem of SOC development is development rework caused by
unreliable energy consumption estimation at the early stages. The
energy consumption of an SoC used in embedded systems is strongly
affected by the dynamic behavior of the software. At the early stages
of SoC development, modeling with a high level of abstraction is
required for both the dynamic behavior of the software, and the
behavior of the SoC. We estimate the energy consumption by a UML
model-based simulation. The proposed method is applied for an actual
embedded system in an MFP. The energy consumption estimation of
the SoC is more accurate than conventional methods and this proposed
method is promising to reduce the chance of development rework in
the SoC development. ∈
Abstract: The purpose of this study was to explore the learning
effects on dance domain in Arts Curriculum at junior and senior high
levels. A total of 1,366 students from 9th to 11th grade of different
areas from Taiwan were administered a self-designed dance
achievement test. Data were analyzed through descriptive analysis,
independent sample t test, one-way ANOVA and Post hoc comparison
analysis using Scheffé Test. The results showed (1) female students
Abstract: Groups where the discrete logarithm problem (DLP) is believed to be intractable have proved to be inestimable building blocks for cryptographic applications. They are at the heart of numerous protocols such as key agreements, public-key cryptosystems, digital signatures, identification schemes, publicly verifiable secret sharings, hash functions and bit commitments. The search for new groups with intractable DLP is therefore of great importance.The goal of this article is to study elliptic curves over the ring Fq[], with Fq a finite field of order q and with the relation n = 0, n ≥ 3. The motivation for this work came from the observation that several practical discrete logarithm-based cryptosystems, such as ElGamal, the Elliptic Curve Cryptosystems . In a first time, we describe these curves defined over a ring. Then, we study the algorithmic properties by proposing effective implementations for representing the elements and the group law. In anther article we study their cryptographic properties, an attack of the elliptic discrete logarithm problem, a new cryptosystem over these curves.
Abstract: The term Enterprise 2.0 (E2.0) describes a collection of organizational and IT practices that help organizations establish flexible work models, visible knowledge-sharing practices, and higher levels of community participation. E2.0 parallels and builds on another term commonly being used in the industry – Web 2.0. E2.0 represents also new packaging for strategic collaboration and Knowledge Management (KM). Organizations rely on collaboration and KM initiatives to attain innovation, growth, productivity, and performance goals.
Abstract: Plasmodium vivax malaria differs from P. falciparum malaria in that a person suffering from P. vivax infection can suffer relapses of the disease. This is due the parasite being able to remain dormant in the liver of the patients where it is able to re-infect the patient after a passage of time. During this stage, the patient is classified as being in the dormant class. The model to describe the transmission of P. vivax malaria consists of a human population divided into four classes, the susceptible, the infected, the dormant and the recovered. The effect of a time delay on the transmission of this disease is studied. The time delay is the period in which the P. vivax parasite develops inside the mosquito (vector) before the vector becomes infectious (i.e., pass on the infection). We analyze our model by using standard dynamic modeling method. Two stable equilibrium states, a disease free state E0 and an endemic state E1, are found to be possible. It is found that the E0 state is stable when a newly defined basic reproduction number G is less than one. If G is greater than one the endemic state E1 is stable. The conditions for the endemic equilibrium state E1 to be a stable spiral node are established. For realistic values of the parameters in the model, it is found that solutions in phase space are trajectories spiraling into the endemic state. It is shown that the limit cycle and chaotic behaviors can only be achieved with unrealistic parameter values.
Abstract: We propose a fast and robust hierarchical face detection system which finds and localizes face images with a cascade of classifiers. Three modules contribute to the efficiency of our detector. First, heterogeneous feature descriptors are exploited to enrich feature types and feature numbers for face representation. Second, a PSO-Adaboost algorithm is proposed to efficiently select discriminative features from a large pool of available features and reinforce them into the final ensemble classifier. Compared with the standard exhaustive Adaboost for feature selection, the new PSOAdaboost algorithm reduces the training time up to 20 times. Finally, a three-stage hierarchical classifier framework is developed for rapid background removal. In particular, candidate face regions are detected more quickly by using a large size window in the first stage. Nonlinear SVM classifiers are used instead of decision stump functions in the last stage to remove those remaining complex nonface patterns that can not be rejected in the previous two stages. Experimental results show our detector achieves superior performance on the CMU+MIT frontal face dataset.
Abstract: In this paper, we propose a new approach to query-by-humming, focusing on MP3 songs database. Since MP3 songs are much more difficult in melody representation than symbolic performance data, we adopt to extract feature descriptors from the vocal sounds part of the songs. Our approach is based on signal filtering, sub-band spectral processing, MDCT coefficients analysis and peak energy detection by ignorance of the background music as much as possible. Finally, we apply dual dynamic programming algorithm for feature similarity matching. Experiments will show us its online performance in precision and efficiency.
Abstract: A bond graph model of a hydroelectric plant is
proposed. In order to analyze the system some structural properties
of a bond graph are used. The structural controllability of
the hydroelctric plant is described. Also, the steady state of the
state variables applying the bond graph in a derivative causality
assignment is obtained. Finally, simulation results of the system
are shown.