Abstract: The paper investigates downtrend algorithm and
trading strategy based on chart pattern recognition and technical
analysis in futures market. The proposed chart formation is a pattern
with the lowest low in the middle and one higher low on each side.
The contribution of this paper lies in the reinforcement of statements
about the profitability of momentum trend trading strategies.
Practical benefit of the research is a trading algorithm in falling
markets and back-test analysis in futures markets. When based on
daily data, the algorithm has generated positive results, especially
when the market had downtrend period. Downtrend algorithm can be
applied as a hedge strategy against possible sudden market crashes.
The proposed strategy can be interesting for futures traders, hedge
funds or scientific researchers performing technical or algorithmic
market analysis based on momentum trend trading.
Abstract: Taxation as a potent fiscal policy instrument through which infrastructures and social services that drive the development process of any society has been ineffective in Nigeria. The adoption of appropriate measures is, however, a requirement for the generation of adequate tax revenue. This study set out to investigates efficiency and effectiveness in the administration of tax in Nigeria, using Cross River State as a case-study. The methodology to achieve this objective is a qualitative technique using structured questionnaires to survey the three senatorial districts in the state; the central limit theory is adopted as our analytical technique. Result showed a significant degree of inefficiency in the administration of taxes. It is recommended that periodic review and update of tax policy will bring innovation and effectiveness in the administration of taxes. Also proper appropriation of tax revenue will drive development in needed infrastructural and social services.
Abstract: There has been a growing interest in implementing humanoid avatars in networked virtual environment. However, most existing avatar communication systems do not take avatars- social backgrounds into consideration. This paper proposes a novel humanoid avatar animation system to represent personalities and facial emotions of avatars based on culture, profession, mood, age, taste, and so forth. We extract semantic keywords from the input text through natural language processing, and then the animations of personalized avatars are retrieved and displayed according to the order of the keywords. Our primary work is focused on giving avatars runtime instruction from multiple natural languages. Experiments with Chinese, Japanese and English input based on the prototype show that interactive avatar animations can be displayed in real time and be made available online. This system provides a more natural and interesting means of human communication, and therefore is expected to be used for cross-cultural communication, multiuser online games, and other entertainment applications.
Abstract: We develop a three-step fuzzy logic-based algorithm for clustering categorical attributes, and we apply it to analyze cultural data. In the first step the algorithm employs an entropy-based clustering scheme, which initializes the cluster centers. In the second step we apply the fuzzy c-modes algorithm to obtain a fuzzy partition of the data set, and the third step introduces a novel cluster validity index, which decides the final number of clusters.
Abstract: With a development of Hybrid Electric Vehicle(HEV),
A photovoltaic(PV) generation system is used for charging batteries in many cases. A dc/dc converter using PV power for a battery charger
requires a high efficiency. In this paper, A ZVS boost converter using the renewable energies for HEV charger is proposed. Through the theoretical analysis and experimental result, operation modes and characteristics of the proposed topology are verified.
Abstract: This paper presents a perturbation based search method
to solve the unconstrained binary quadratic programming problem.
The proposed algorithm was tested with some of the standard test
problems and the results are reported for 10 instances of 50, 100, 250,
& 500 variable problems. A comparison of the performance of the
proposed algorithm with other heuristics and optimization software is
made. Based on the results, it was found that the proposed algorithm
is computationally inexpensive and the solutions obtained match the
best known solutions for smaller sized problems. For larger instances,
the algorithm is capable of finding a solution within 0.11% of the
best known solution. Apart from being used as a stand-alone method,
this algorithm could also be incorporated with other heuristics to find
better solutions.
Abstract: The 4G front-end transceiver needs a high
performance which can be obtained mainly with an optimal
architecture and a multi-band Local Oscillator. In this study, we
proposed and presented a new architecture of multi-band frequency
synthesizer based on an Inverse Sine Phase Detector Phase Locked
Loop (ISPD PLL) without any filters and any controlled gain block
and associated with adapted multi band LC tuned VCO using a
several numeric controlled capacitive branches but not binary
weighted. The proposed architecture, based on 0.35μm CMOS
process technology, supporting Multi-band GSM/DCS/DECT/
UMTS/WiMax application and gives a good performances: a phase
noise @1MHz -127dBc and a Factor Of Merit (FOM) @ 1MHz -
186dB and a wide band frequency range (from 0.83GHz to 3.5GHz),
that make the proposed architecture amenable for monolithic
integration and 4G multi-band application.
Abstract: Magnetic carbon nanotubes composites were obtained
by filling carbon nanotubes with paramagnetic iron oxide particles.
Detailed investigation of magnetic behaviour of resulting composites
was done at different temperatures. Measurements indicate that these
functionalized nanotubes are superparamagnetic at room temperature;
however, no superparamagnetism was observed at 125 K and 80 K.
The blocking temperature TB was estimated at 145 K. These magnetic
carbon nanotubes have the potential of being used in a wide range of
applications, in particular, the production of nanofluids, which can be
controlled and steered by appropriate magnetic fields.
Abstract: Predicting protein-protein interactions represent a key step in understanding proteins functions. This is due to the fact that proteins usually work in context of other proteins and rarely function alone. Machine learning techniques have been applied to predict protein-protein interactions. However, most of these techniques address this problem as a binary classification problem. Although it is easy to get a dataset of interacting proteins as positive examples, there are no experimentally confirmed non-interacting proteins to be considered as negative examples. Therefore, in this paper we solve this problem as a one-class classification problem using one-class support vector machines (SVM). Using only positive examples (interacting protein pairs) in training phase, the one-class SVM achieves accuracy of about 80%. These results imply that protein-protein interaction can be predicted using one-class classifier with comparable accuracy to the binary classifiers that use artificially constructed negative examples.
Abstract: Question answering (QA) aims at retrieving precise information from a large collection of documents. Most of the Question Answering systems composed of three main modules: question processing, document processing and answer processing. Question processing module plays an important role in QA systems to reformulate questions. Moreover answer processing module is an emerging topic in QA systems, where these systems are often required to rank and validate candidate answers. These techniques aiming at finding short and precise answers are often based on the semantic relations and co-occurrence keywords. This paper discussed about a new model for question answering which improved two main modules, question processing and answer processing which both affect on the evaluation of the system operations. There are two important components which are the bases of the question processing. First component is question classification that specifies types of question and answer. Second one is reformulation which converts the user's question into an understandable question by QA system in a specific domain. The objective of an Answer Validation task is thus to judge the correctness of an answer returned by a QA system, according to the text snippet given to support it. For validating answers we apply candidate answer filtering, candidate answer ranking and also it has a final validation section by user voting. Also this paper described new architecture of question and answer processing modules with modeling, implementing and evaluating the system. The system differs from most question answering systems in its answer validation model. This module makes it more suitable to find exact answer. Results show that, from total 50 asked questions, evaluation of the model, show 92% improving the decision of the system.
Abstract: In this research, the main aim is to investigate the
antimicrobial effectiveness of ammonyx solutions finishing on
Sweatshirt Sport with immersion method. 60 Male healthy subjects
(football player) participated in this study. They were dressed in a
Sweatshirt for 14 days and some microbes found on them were
investigated. The antimicrobial effect of different ammonyx
solutions(1/100, 1/500, 1/1000, 1/2000 v/v solutions of Ammonyx)
on the identified microbes was studied by the zone inhabitation
method in vitro. In the next step the Sweatshirt Sports were treated
with the same different solutions of ammonyx and the antimicrobial
effectiveness was assessed by colony count method in different times
and the results were compared whit untreated ones. Some mechanical
properties of treated cotton/polyester yarn that used in Sweatshirt
Sport were measured after 30 days and were compared with
untreated one. Finally after finishing, scanning electron microscopy
(SEM) was used to compare the surfaces of the finished and
unfinished specimens. The results showed the presence of five
pathogenic microbes on Sweatshirt Sports such as Escherichia coli,
Staphylococcus aureus, Aspergillus, Mucor and Candida. The
inhalation time for treated on Sweatshirt Sports improved. The
amount of colony growth on treated clothes reduced considerably
and moreover the mechanical tests results showed no significant
deterioration effect of studies properties in comparison to the
untreated yarn. The visual examination of the SEM indicated that the
antimicrobial treatments were applied usefully to fabrics.
Abstract: During the process of compaction in Hot-Mix Asphalt
(HMA) mixtures, the distance between aggregate particles decreases
as they come together and eliminate air-voids. By measuring the
inter-particle distances in a cut-section of a HMA sample the degree
of compaction can be estimated. For this, a calibration curve is
generated by computer simulation technique when the gradation and
asphalt content of the HMA mixture are known. A two-dimensional
cross section of HMA specimen was simulated using the mixture
design information (gradation, asphalt content and air-void content).
Nearest neighbor distance methods such as Delaunay triangulation
were used to study the changes in inter-particle distance and area
distribution during the process of compaction in HMA. Such
computer simulations would enable making several hundreds of
repetitions in a short period of time without the necessity to compact
and analyze laboratory specimens in order to obtain good statistics on
the parameters defined. The distributions for the statistical
parameters based on computer simulations showed similar trends as
those of laboratory specimens.
Abstract: This research study examines cases of Saudi Arabian
universities and female academics for work environment issues
within the context of design management applications. The study
proposes use of design research, ergonomics and systems design
thinking to develop the university design which facilitates removal of
physical and cognitive barriers for female academics. Review of
literature demonstrates that macro and micro ergonomic combined
with design management and system design strategies can
significantly improve the workplace design for female academics.
The university design model would be prepared based on the analyses
of primary data obtained from archived documents, participants'
observation logs, photo audits, focus groups and semi-structured
interviews of currently employed female academics in the selected
case universities.
Abstract: In this work, a characterization and modeling of
packet loss of a Voice over Internet Protocol (VoIP) communication
is developed. The distributions of the number of consecutive received
and lost packets (namely gap and burst) are modeled from the
transition probabilities of two-state and four-state model.
Measurements show that both models describe adequately the burst
distribution, but the decay of gap distribution for non-homogeneous
losses is better fit by the four-state model. The respective
probabilities of transition between states for each model were
estimated with a proposed algorithm from a set of monitored VoIP
calls in order to obtain representative minimum, maximum and
average values for both models.
Abstract: In this paper an alternative analysis in the time
domain is described and the results of the interpolation process are
presented by means of functions that are based on the rule of
conditional mathematical expectation and the covariance function. A
comparison between the interpolation error caused by low order
filters and the classic sinc(t) truncated function is also presented.
When fewer samples are used, low-order filters have less error. If the
number of samples increases, the sinc(t) type functions are a better
alternative. Generally speaking there is an optimal filter for each
input signal which depends on the filter length and covariance
function of the signal. A novel scheme of work for adaptive
interpolation filters is also presented.
Abstract: In this paper, we consider the analysis of the
acquisition process for a hybrid double-dwell system with antenna
diversity for DS-CDMA (direct sequence-code division multiple
access) using an adaptive threshold. Acquisition systems with a fixed
threshold value are unable to adapt to fast varying mobile
communications environments and may result in a high false alarm
rate, and/or low detection probability. Therefore, we propose an
adaptively varying threshold scheme through the use of a cellaveraging
constant false alarm rate (CA-CFAR) algorithm, which is
well known in the field of radar detection. We derive exact
expressions for the probabilities of detection and false alarm in
Rayleigh fading channels. The mean acquisition time of the system
under consideration is also derived. The performance of the system is
analyzed and compared to that of a hybrid single dwell system.
Abstract: In this paper, a new version of support vector regression (SVR) is presented namely Fuzzy Cost SVR (FCSVR). Individual property of the FCSVR is operation over fuzzy data whereas fuzzy cost (fuzzy margin and fuzzy penalty) are maximized. This idea admits to have uncertainty in the penalty and margin terms jointly. Robustness against noise is shown in the experimental results as a property of the proposed method and superiority relative conventional SVR.
Abstract: In this paper, enhanced ground proximity warning simulation and validation system is designed and implemented. First, based on square grid and sub-grid structure, the global digital terrain database is designed and constructed. Terrain data searching is implemented through querying the latitude and longitude bands and separated zones of global terrain database with the current aircraft position. A combination of dynamic scheduling and hierarchical scheduling is adopted to schedule the terrain data, and the terrain data can be read and delete dynamically in the memory. Secondly, according to the scope, distance, approach speed information etc. to the dangerous terrain in front, and using security profiles calculating method, collision threat detection is executed in real-time, and provides caution and warning alarm. According to this scheme, the implementation of the enhanced ground proximity warning simulation system is realized. Simulations are carried out to verify a good real-time in terrain display and alarm trigger, and the results show simulation system is realized correctly, reasonably and stable.
Abstract: Viscous heating becomes significant in the high speed
resin coating process of glass fibers for optical fiber manufacturing.
This study focuses on the coating resin flows inside the capillary
coating die of optical fiber coating applicator and they are numerically
simulated to examine the effects of viscous heating and subsequent
temperature increase in coating resin. Resin flows are driven by fast
moving glass fiber and the pressurization at the coating die inlet, while
the temperature dependent viscosity of liquid coating resin plays an
important role in the resin flow. It is found that the severe viscous
heating near the coating die wall profoundly alters the radial velocity
profiles and that the increase of final coating thickness by die
pressurization is amplified if viscous heating is present.
Abstract: In this paper three basic approaches and different
methods under each of them for extracting region of interest (ROI)
from stationary images are explored. The results obtained for each of
the proposed methods are shown, and it is demonstrated where each
method outperforms the other. Two main problems in ROI
extraction: the channel selection problem and the saliency reversal
problem are discussed and how best these two are addressed by
various methods is also seen. The basic approaches are 1) Saliency
based approach 2) Wavelet based approach 3) Clustering based
approach. The saliency approach performs well on images containing
objects of high saturation and brightness. The wavelet based
approach performs well on natural scene images that contain regions
of distinct textures. The mean shift clustering approach partitions the
image into regions according to the density distribution of pixel
intensities. The experimental results of various methodologies show
that each technique performs at different acceptable levels for
various types of images.