Abstract: the research was conducted using the self report of
shoplifters who apprehended in the supermarket while stealing. 943
shoplifters in three years were interviewed right after the stealing act
and before calling the police. The aim of the study is to know the
shoplifting characteristics in Saudi Arabia, including the trait of
shoplifters and the situation of the supermarkets where the stealing
takes place. The analysis based on the written information about each
thief as the documentary research method. Descriptive statistics as
well as some inferential statistics were employed. The result shows
that there are differences between genders, age groups, occupations,
time of the day, days of the week, months, way of stealing, individual
or group of thieves and other supermarket situations in the type of
items stolen, total price and the count of items. The result and the
recommendation will serve as a guide for retailers where, when and
who to look at to prevent shoplifting.
Abstract: This paper proposes a smart design strategy for a sequential detector to reliably detect the primary user-s signal, especially in fast fading environments. We study the computation of the log-likelihood ratio for coping with a fast changing received signal and noise sample variances, which are considered random variables. First, we analyze the detectability of the conventional generalized log-likelihood ratio (GLLR) scheme when considering fast changing statistics of unknown parameters caused by fast fading effects. Secondly, we propose an efficient sensing algorithm for performing the sequential probability ratio test in a robust and efficient manner when the channel statistics are unknown. Finally, the proposed scheme is compared to the conventional method with simulation results with respect to the average number of samples required to reach a detection decision.
Abstract: According to the statistics, the prevalence of congenital hearing loss in Taiwan is approximately six thousandths; furthermore, one thousandths of infants have severe hearing impairment. Hearing ability during infancy has significant impact in the development of children-s oral expressions, language maturity, cognitive performance, education ability and social behaviors in the future. Although most children born with hearing impairment have sensorineural hearing loss, almost every child more or less still retains some residual hearing. If provided with a hearing aid or cochlear implant (a bionic ear) timely in addition to hearing speech training, even severely hearing-impaired children can still learn to talk. On the other hand, those who failed to be diagnosed and thus unable to begin hearing and speech rehabilitations on a timely manner might lose an important opportunity to live a complete and healthy life. Eventually, the lack of hearing and speaking ability will affect the development of both mental and physical functions, intelligence, and social adaptability. Not only will this problem result in an irreparable regret to the hearing-impaired child for the life time, but also create a heavy burden for the family and society. Therefore, it is necessary to establish a set of computer-assisted predictive model that can accurately detect and help diagnose newborn hearing loss so that early interventions can be provided timely to eliminate waste of medical resources. This study uses information from the neonatal database of the case hospital as the subjects, adopting two different analysis methods of using support vector machine (SVM) for model predictions and using logistic regression to conduct factor screening prior to model predictions in SVM to examine the results. The results indicate that prediction accuracy is as high as 96.43% when the factors are screened and selected through logistic regression. Hence, the model constructed in this study will have real help in clinical diagnosis for the physicians and actually beneficial to the early interventions of newborn hearing impairment.
Abstract: For over a decade, the Pulse Coupled Neural Network
(PCNN) based algorithms have been successfully used in image
interpretation applications including image segmentation. There are
several versions of the PCNN based image segmentation methods,
and the segmentation accuracy of all of them is very sensitive to the
values of the network parameters. Most methods treat PCNN
parameters like linking coefficient and primary firing threshold as
global parameters, and determine them by trial-and-error. The
automatic determination of appropriate values for linking coefficient,
and primary firing threshold is a challenging problem and deserves
further research. This paper presents a method for obtaining global as
well as local values for the linking coefficient and the primary firing
threshold for neurons directly from the image statistics. Extensive
simulation results show that the proposed approach achieves
excellent segmentation accuracy comparable to the best accuracy
obtainable by trial-and-error for a variety of images.
Abstract: Petrol Fuel Station (PFS) has potential hazards to the
people, asset, environment and reputation of an operating company.
Fire hazards, static electricity air pollution evoked by aliphatic and
aromatic organic compounds are major causes of accident/incident
occurrence at fuel station. Activities such as carelessness,
maintenance, housekeeping, slips trips and falls, transportation
hazard, major and minor injuries, robbery and snake bites has a
potential to create unsafe conditions. The level of risk of these
hazards varies according to location and country. The emphasis on
safety considerations by the government is variable all around the
world. Developed countries safety records are much better as
compared to developing countries safety statistics. There is no
significant approach available to highlight the unsafe acts and unsafe
conditions during operation and maintenance of fuel station. Fuel
station is the most commonly available facilities that contain
flammable and hazardous materials. Due to continuous operation of
fuel station they pose various hazards to people, environment and
assets of an organization. To control these hazards, there is a need for
specific approach. PFS operation is unique as compared to other
businesses. For smooth operations it demands an involvement of
operating company, contractor and operator group. This study will
focus to address hazard contributing factors that have a potential to
make PFS operation risky. One year data collected, 902 activities
analyzed, comparisons were made to highlight significant
contributing factors. The study will provide help and assistance to
PFS outlet marketing companies to make their fuel station operation
safer. It will help health safety and environment (HSE) professionals
to arrest the gap available related to safety matters at PFS.
Abstract: A new approach based on the consideration that electroencephalogram (EEG) signals are chaotic signals was presented for automated diagnosis of electroencephalographic changes. This consideration was tested successfully using the nonlinear dynamics tools, like the computation of Lyapunov exponents. This paper presented the usage of statistics over the set of the Lyapunov exponents in order to reduce the dimensionality of the extracted feature vectors. Since classification is more accurate when the pattern is simplified through representation by important features, feature extraction and selection play an important role in classifying systems such as neural networks. Multilayer perceptron neural network (MLPNN) architectures were formulated and used as basis for detection of electroencephalographic changes. Three types of EEG signals (EEG signals recorded from healthy volunteers with eyes open, epilepsy patients in the epileptogenic zone during a seizure-free interval, and epilepsy patients during epileptic seizures) were classified. The selected Lyapunov exponents of the EEG signals were used as inputs of the MLPNN trained with Levenberg- Marquardt algorithm. The classification results confirmed that the proposed MLPNN has potential in detecting the electroencephalographic changes.
Abstract: Fast development of technologies, economic globalization and many other external circumstances stimulate company’s competitiveness. One of the major trends in today’s business is the shift to the exploitation of the Internet and electronic environment for entrepreneurial needs. Latest researches confirm that e-environment provides a range of possibilities and opportunities for companies, especially for micro-, small- and medium-sized companies, which have limited resources. The usage of e-tools raises the effectiveness and the profitability of an organization, as well as its competitiveness.
In the electronic market, as in the classic one, there are factors, such as globalization, development of new technology, price sensitive consumers, Internet, new distribution and communication channels that influence entrepreneurship. As a result of eenvironment development, e-commerce and e-marketing grow as well.
Objective of the paper: To describe and identify factors influencing company’s competitiveness in e-environment.
Research methodology: The authors employ well-established quantitative and qualitative methods of research: grouping, analysis, statistics method, factor analysis in SPSS 20 environment, etc. The theoretical and methodological background of the research is formed by using scientific researches and publications, such as that from mass media and professional literature; statistical information from legal institutions as well as information collected by the authors during the surveying process.
Research result: The authors detected and classified factors influencing competitiveness in e-environment.
In this paper, the authors presented their findings based on theoretical, scientific, and field research. Authors have conducted a research on e-environment utilization among Latvian enterprises.
Abstract: Recently, the health of retired National Football
League players, particularly lineman has been investigated. A number of studies have reported increased cardiometabolic risk, premature ardiovascular disease and incidence of type 2 diabetes. Rugby union players have somatotypes very similar
to National Football league players which suggest that rugby players may have similar health risks. The International Golden Oldies World Rugby Festival (GORF) provided a
unique opportunity to investigate the demographics of veteran rugby players. METHODOLOGIES: A cross-sectional, observational study was completed using an online web-based
questionnaire that consisted of medical history and
physiological measures. Data analysis was completed using a one sample t-test (50yrs) and Chi-square test. RESULTS: A total of 216 veteran rugby competitors
(response rate = 6.8%) representing 10 countries, aged 35-72 yrs (mean 51.2, S.D. ±8.0), participated in the online survey. As a group, the incidence of current smokers was low at 8.8%
(avg 72.4 cigs/wk) whilst the percentage consuming alcohol
was high (93.1% (avg 11.2 drinks/wk). Competitors reported
the following top six chronic diseases/disorders; hypertension
(18.6%), arthritis (OA/RA, 11.5%), asthma (9.3%),
hyperlipidemia (8.2%), diabetes (all types, 7.5%) and gout (6%), there were significant differences between groups with
regard to cancer (all types) and migraines. When compared to
the Australian general population (Australian Bureau of Statistics data, n=18,000), GORF competitors had a
Climstein Mike, Walsh Joe (corresponding author) and Burke Stephen
School of Exercise Science, Australian Catholic University, 25A Barker Road,
Strathfield, Sydney, NSW, 2016, Australia (e-mail:
[email protected], [email protected],
[email protected]).
John Best is with Orthosports, 160 Belmore Rd., Randwick, Sydney,NSW
2031, Australia (e-mail: [email protected]).
Heazlewood, Ian Timothy is with School of Environmental and Life
Sciences, Faculty Education, Health and Science, Charles Darwin University,
Precinct Yellow Building 2, Charles Darwin University, NT 0909, Australia
(e-mail: [email protected]).
Kettunen Jyrki Arcada University of Applied Sciences, Jan-Magnus
Janssonin aukio 1, FI-00550, Helsinki, Finland (e-mail:
[email protected]).
Adams Kent is with California State University Monterey Bay, Kinesiology Department, 100 Campus Center, Seaside, CA., 93955, USA (email: [email protected]).
DeBeliso Mark is with Department of Physical Education and Human
Performance, Southern Utah University, 351 West University Blvd, Cedar
City, Utah, USA (e-mail: [email protected]).
significantly lower incidence of anxiety (p
Abstract: In this paper is shown that the probability-statistic methods application, especially at the early stage of the aviation gas turbine engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence is considered the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods. Training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. Thus for GTE technical condition more adequate model making are analysed dynamics of skewness and kurtosis coefficients' changes. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes- dynamics of GTE work parameters allows to draw conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines' technical condition. Researches of correlation coefficients values- changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. For checking of models adequacy is considered the Fuzzy Multiple Correlation Coefficient of Fuzzy Multiple Regression. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-bystage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine temperature condition was made.
Abstract: We present in this paper a new approach for specific JPEG steganalysis and propose studying statistics of the compressed DCT coefficients. Traditionally, steganographic algorithms try to preserve statistics of the DCT and of the spatial domain, but they cannot preserve both and also control the alteration of the compressed data. We have noticed a deviation of the entropy of the compressed data after a first embedding. This deviation is greater when the image is a cover medium than when the image is a stego image. To observe this deviation, we pointed out new statistic features and combined them with the Multiple Embedding Method. This approach is motivated by the Avalanche Criterion of the JPEG lossless compression step. This criterion makes possible the design of detectors whose detection rates are independent of the payload. Finally, we designed a Fisher discriminant based classifier for well known steganographic algorithms, Outguess, F5 and Hide and Seek. The experiemental results we obtained show the efficiency of our classifier for these algorithms. Moreover, it is also designed to work with low embedding rates (< 10-5) and according to the avalanche criterion of RLE and Huffman compression step, its efficiency is independent of the quantity of hidden information.
Abstract: As the global climate changes, the threat from
landslides and debris flows increases. Learning how a watershed
initiates landslides under abnormal rainfall conditions and predicting
landslide magnitude and frequency distribution is thus important.
Landslides show a power-law distribution in the frequency-area
distribution. The distribution curve shows an exponent gradient 1.0 in
the Sandpile model test. Will the landslide frequency-area statistics
show a distribution similar to the Sandpile model under extreme
rainfall conditions? The purpose of the study is to identify the extreme
rainfall-induced landslide frequency-area distribution in the Laonong
River Basin in southern Taiwan. Results of the analysis show that a
lower gradient of landslide frequency-area distribution could be
attributed to the transportation and deposition of debris flow areas that
are included in the landslide area.
Abstract: It is an important task in Korean-English machine
translation to classify the gender of names correctly. When a sentence
is composed of two or more clauses and only one subject is given as a proper noun, it is important to find the gender of the proper noun
for correct translation of the sentence. This is because a singular pronoun has a gender in English while it does not in Korean. Thus,
in Korean-English machine translation, the gender of a proper noun should be determined. More generally, this task can be expanded into the classification of the general Korean names. This paper proposes a statistical method for this problem. By considering a name as just
a sequence of syllables, it is possible to get a statistics for each name from a collection of names. An evaluation of the proposed method
yields the improvement in accuracy over the simple looking-up of the
collection. While the accuracy of the looking-up method is 64.11%, that of the proposed method is 81.49%. This implies that the proposed
method is more plausible for the gender classification of the Korean names.
Abstract: Sweet potato products are necessary for the provision
of essential nutrients in every household, regardless of their poverty
status. Their consumption appears to be highly influenced by socioeconomic
factors, such as malnutrition, food insecurity and
unemployment. Therefore, market availability is crucial for these
cultivars to resolve some of the socio-economic factors. The aim of
the study was to investigate market availability of sweet potato
cultivars in the North West Province. In this study, both qualitative
and quantitative research methodologies were used. Qualitative
methodology was used to explain the quantitative outcomes of the
variables. On the other hand, quantitative results were used to test the
hypothesis. The study used SPSS software to analyse the data. Crosstabulation
and Chi-square statistics were used to obtain the
descriptive and inferential analyses, respectively. The study found
that the Blesbok cultivar is dominating the markets of the North West
Province, with the Monate cultivar dominating in the Bojanala
Platinum (75%) and Dr Ruth Segomotsi Mompati (25%) districts. It
is also found that a unit increase in the supply of sweet potato
cultivars in both local and district municipal markets is accompanied
by a reduced demand of 28% and 33% at district and local markets,
respectively. All these results were found to be significant at p
Abstract: The objective of this research is to study the people’s level of participation in activities of the community, their satisfaction towards the community, the attachment they have to the community, factors that influence the attachment, as well as the characteristics of the relationships of military families’ of the Royal Guards community of Dusit District. The method used was non-probability sampling by quota sampling according to people’s age. The determined age group was 18 years or older.
One set of a sample group was done per family. The questionnaires were conducted by 287 people. Snowball sampling was also used by interviewing people of the community, starting from the Royal Guards Community’s leader, then by 20 of the community’s well-respected persons. The data was analyzed by using descriptive statistics, such as arithmetic mean and standard deviation, as well as by inferential statistics, such as Independent - Samples T test (T-test), One-Way ANOVA (F-test), Chi-Square. Descriptive analysis according to the structure of the interview content was also used. The results of the research is that the participation of the population in the Royal Guards Community in various activities is at a medium level, with the average participation level during Mother’s and Father’s Days. The people’s general level of satisfaction towards the premises of the Royal Guards Community is at the highest level.
The people were most satisfied with the transportation within the community and in contacting with people from outside the premises. The access to the community is convenient and there are various entrances. The attachment of the people to the Royal Guards Community in general and by each category is at a high level. The feeling that the community is their home rated the highest average. Factors that influence the attachment of the people of the Royal Guards Community are age, status, profession, income, length of stay in the community, membership of social groups, having neighbors they feel close and familiar with, and as well as the benefits they receive from the community. In addition, it was found that people that participate in activities have a high level of positive relationship towards the attachment of the people to the Royal Guards Community. The satisfaction of the community has a very high level of positive relationship with the attachment of the people to the Royal Guards Community.
The characteristics of the attachment of military families’ is that they live in big houses that everyone has to protect and care for, starting from the leader of the family as well as all members. Therefore, they all love the community they live in. The characteristics that show the participation of activities within the community and the high level of satisfaction towards the premises of the community will enable the people to be more attached to the community. The people feel that everyone is close neighbors within the community, as if they are one big family.
Abstract: Textures are replications, symmetries and
combinations of various basic patterns, usually with some random
variation one of the gray-level statistics. This article proposes a
new approach to Segment texture images. The proposed approach
proceeds in 2 stages. First, in this method, local texture information
of a pixel is obtained by fuzzy texture unit and global texture
information of an image is obtained by fuzzy texture spectrum.
The purpose of this paper is to demonstrate the usefulness of fuzzy
texture spectrum for texture Segmentation.
The 2nd Stage of the method is devoted to a decision process,
applying a global analysis followed by a fine segmentation,
which is only focused on ambiguous points. The above Proposed
approach was applied to brain image to identify the components
of brain in turn, used to locate the brain tumor and its Growth
rate.
Abstract: Distant-talking voice-based HCI system suffers from
performance degradation due to mismatch between the acoustic
speech (runtime) and the acoustic model (training). Mismatch is
caused by the change in the power of the speech signal as observed at
the microphones. This change is greatly influenced by the change in
distance, affecting speech dynamics inside the room before reaching
the microphones. Moreover, as the speech signal is reflected, its
acoustical characteristic is also altered by the room properties. In
general, power mismatch due to distance is a complex problem. This
paper presents a novel approach in dealing with distance-induced
mismatch by intelligently sensing instantaneous voice power variation
and compensating model parameters. First, the distant-talking speech
signal is processed through microphone array processing, and the
corresponding distance information is extracted. Distance-sensitive
Gaussian Mixture Models (GMMs), pre-trained to capture both
speech power and room property are used to predict the optimal
distance of the speech source. Consequently, pre-computed statistic
priors corresponding to the optimal distance is selected to correct
the statistics of the generic model which was frozen during training.
Thus, model combinatorics are post-conditioned to match the power
of instantaneous speech acoustics at runtime. This results to an
improved likelihood in predicting the correct speech command at
farther distances. We experiment using real data recorded inside two
rooms. Experimental evaluation shows voice recognition performance
using our method is more robust to the change in distance compared
to the conventional approach. In our experiment, under the most
acoustically challenging environment (i.e., Room 2: 2.5 meters), our
method achieved 24.2% improvement in recognition performance
against the best-performing conventional method.
Abstract: Kish Islands in South of Iran is located in coastal
water near Hormozgan Province. Based on the wind 3-hour statistics
in Kish station, the mean annual windspeed in this Island is 8.6 knot
(4.3 m/s). The maximum windspeed recorded in this stations 47 knot
(23.5 m/s). In 45.7 percent of recorded times, windspeed has been
Zero or less than 8 knot which is not suitable to use the wind energy.
But in 54.3 percent of recorded times, windspeed has been more than
8 knot and suitable to use wind energy to run turbines. In 40.2
percent of recorded times, windspeed has been between 8 to 16 knot,
in 13 percent of times between 16 to 24 knot and in 1 percent of
times it has been higher than 24 knot. In this station, the direction of
winds higher than 8 is west and wind direction in Kish station is
stable in most times of the year.With regard to high – speed and
stable direction winds during the year and also shallow coasts near
this is land, it is possible to build offshore wind farms near Kish
Island and utilize wind energy produce the electricity required in this
Island during most of the year.
Abstract: Eukaryotic protein-coding genes are interrupted by spliceosomal introns, which are removed from the RNA transcripts before translation into a protein. The exon-intron structures of different eukaryotic species are quite different from each other, and the evolution of such structures raises many questions. We try to address some of these questions using statistical analysis of whole genomes. We go through all the protein-coding genes in a genome and study correlations between the net length of all the exons in a gene, the number of the exons, and the average length of an exon. We also take average values of these features for each chromosome and study correlations between those averages on the chromosomal level. Our data show universal features of exon-intron structures common to animals, plants, and protists (specifically, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Cryptococcus neoformans, Homo sapiens, Mus musculus, Oryza sativa, and Plasmodium falciparum). We have verified linear correlation between the number of exons in a gene and the length of a protein coded by the gene, while the protein length increases in proportion to the number of exons. On the other hand, the average length of an exon always decreases with the number of exons. Finally, chromosome clustering based on average chromosome properties and parameters of linear regression between the number of exons in a gene and the net length of those exons demonstrates that these average chromosome properties are genome-specific features.
Abstract: Statistics indicate that more than 1000 phishing attacks are launched every month. With 57 million people hit by the fraud so far in America alone, how do we combat phishing?This publication aims to discuss strategies in the war against Phishing. This study is an examination of the analysis and critique found in the ways adopted at various levels to counter the crescendo of phishing attacks and new techniques being adopted for the same. An analysis of the measures taken up by the varied popular Mail servers and popular browsers is done under this study. This work intends to increase the understanding and awareness of the internet user across the globe and even discusses plausible countermeasures at the users as well as the developers end. This conceptual paper will contribute to future research on similar topics.
Abstract: There is a complex situation on the transport environment in the cities of the world. For the analysis and prevention of environmental problems an accurate calculation hazardous substances concentrations at each point of the investigated area is required. In the turbulent atmosphere of the city the wellknown methods of mathematical statistics for these tasks cannot be applied with a satisfactory level of accuracy. Therefore, to solve this class of problems apparatus of mathematical physics is more appropriate. In such models, because of the difficulty as a rule the influence of uneven land surface on streams of air masses in the turbulent atmosphere of the city are not taken into account. In this paper the influence of the surface roughness, which can be quite large, is mathematically shown. The analysis of this problem under certain conditions identified the possibility of areas appearing in the atmosphere with pressure tending to infinity, i.e. so-called "wall effect".