Abstract: Dichotomization of the outcome by a single cut-off point is an important part of various medical studies. Usually the relationship between the resulted dichotomized dependent variable and explanatory variables is analyzed with linear regression, probit regression or logistic regression. However, in many real-life situations, a certain cut-off point dividing the outcome into two groups is unknown and can be specified only approximately, i.e. surrounded by some (small) uncertainty. It means that in order to have any practical meaning the regression model must be robust to this uncertainty. In this paper, we show that neither the beta in the linear regression model, nor its significance level is robust to the small variations in the dichotomization cut-off point. As an alternative robust approach to the problem of uncertain medical categories, we propose to use the linear regression model with the fuzzy membership function as a dependent variable. This fuzzy membership function denotes to what degree the value of the underlying (continuous) outcome falls below or above the dichotomization cut-off point. In the paper, we demonstrate that the linear regression model of the fuzzy dependent variable can be insensitive against the uncertainty in the cut-off point location. In the paper we present the modeling results from the real study of low hemoglobin levels in infants. We systematically test the robustness of the binomial regression model and the linear regression model with the fuzzy dependent variable by changing the boundary for the category Anemia and show that the behavior of the latter model persists over a quite wide interval.
Abstract: Human perceives color in categories, which may be
identified using color name such as red, blue, etc. The categorization
is unique for each human being. However despite the individual
differences, the categorization is shared among members in society.
This allows communication among them, especially when using
color name. Sociable robot, to live coexist with human and become
part of human society, must also have the shared color
categorization, which can be achieved through learning. Many
works have been done to enable computer, as brain of robot, to learn
color categorization. Most of them rely on modeling of human color
perception and mathematical complexities. Differently, in this work,
the computer learns color categorization through interaction with
humans. This work aims at developing the innate ability of the
computer to learn the human-like color categorization. It focuses on
the representation of color categorization and how it is built and
developed without much mathematical complexity.
Abstract: A Matlab based software for logistic regression is developed to enhance the process of teaching quantitative topics and assist researchers with analyzing wide area of applications where categorical data is involved. The software offers an option of performing stepwise logistic regression to select the most significant predictors. The software includes a feature to detect influential observations in data, and investigates the effect of dropping or misclassifying an observation on a predictor variable. The input data may consist either as a set of individual responses (yes/no) with the predictor variables or as grouped records summarizing various categories for each unique set of predictor variables' values. Graphical displays are used to output various statistical results and to assess the goodness of fit of the logistic regression model. The software recognizes possible convergence constraints when present in data, and the user is notified accordingly.
Abstract: This study aimed to explore future life orientation and
support that needed to accomplish it. A total of 258 participants are
Javanese high school student. The age of the sample ranges from 14
to 18 years old. Participants were asked about their future aspiration,
their reason of choosing them as important goals in their life, and
support that they need to accomplished their goals using open ended
questionnaire. The responses were categorized through content
analysis into four main categories. They are: (1) Self Fulfillment
(72.1%) (2) Parents and Family (16.7%) (3) Altruism (8.1%) (4)
Social and Economy Status (3.1%). Meanwhile, the categories for
support that they needed are shown as follows: (1) Affection Support
(64.7%) (2) Spiritual support (17.4%) (3) Material Support (10.9%)
(4) Guidance Support (7.0%). The research found that affection
support always gets the highest number in every future orientation
categories. It can be concluded that although Javanese adolescents
have different future orientation, they basically need affection
support.
Abstract: Wimax (Worldwide Interoperability for Microwave Access)
is a promising technology which can offer high speed data,
voice and video service to the customer end, which is presently, dominated
by the cable and digital subscriber line (DSL) technologies.
The performance assessment of Wimax systems is dealt with. The
biggest advantage of Broadband wireless application (BWA) over its
wired competitors is its increased capacity and ease of deployment.
The aims of this paper are to model and simulate the fixed OFDM
IEEE 802.16d physical layer under variant combinations of digital
modulation (BPSK, QPSK, and 16-QAM) over diverse combination
of fading channels (AWGN, SUIs). Stanford University Interim (SUI)
Channel serial was proposed to simulate the fixed broadband wireless
access channel environments where IEEE 802.16d is to be deployed.
It has six channel models that are grouped into three categories
according to three typical different outdoor Terrains, in order to give
a comprehensive effect of fading channels on the overall performance
of the system.
Abstract: The understanding of the system level of biological behavior and phenomenon variously needs some elements such as gene sequence, protein structure, gene functions and metabolic pathways. Challenging problems are representing, learning and reasoning about these biochemical reactions, gene and protein structure, genotype and relation between the phenotype, and expression system on those interactions. The goal of our work is to understand the behaviors of the interactions networks and to model their evolution in time and in space. We propose in this study an ontological meta-model for the knowledge representation of the genetic regulatory networks. Ontology in artificial intelligence means the fundamental categories and relations that provide a framework for knowledge models. Domain ontology's are now commonly used to enable heterogeneous information resources, such as knowledge-based systems, to communicate with each other. The interest of our model is to represent the spatial, temporal and spatio-temporal knowledge. We validated our propositions in the genetic regulatory network of the Aarbidosis thaliana flower
Abstract: Segmentation of Magnetic Resonance Imaging (MRI) images is the most challenging problems in medical imaging. This paper compares the performances of Seed-Based Region Growing (SBRG), Adaptive Network-Based Fuzzy Inference System (ANFIS) and Fuzzy c-Means (FCM) in brain abnormalities segmentation. Controlled experimental data is used, which designed in such a way that prior knowledge of the size of the abnormalities are known. This is done by cutting various sizes of abnormalities and pasting it onto normal brain tissues. The normal tissues or the background are divided into three different categories. The segmentation is done with fifty seven data of each category. The knowledge of the size of the abnormalities by the number of pixels are then compared with segmentation results of three techniques proposed. It was proven that the ANFIS returns the best segmentation performances in light abnormalities, whereas the SBRG on the other hand performed well in dark abnormalities segmentation.
Abstract: The explosion of interest in online gaming and
virtual worlds is leading many universities to investigate
possible educational applications of the new environments.
In this paper we explore the possibilities of 3D online worlds
for teacher education, particularly the field experience
component. Drawing upon two pedagogical examples, we
suggest that virtual simulations may, with certain limitations,
create safe spaces that allow preservice teachers to adopt
alternate identities and interact safely with the “other." In so
doing they may become aware of the constructed nature of
social categories and gain the essential pedagogical skill of
perspective-taking. We suggest that, ultimately, the ability to
be the principal creators of themselves in virtual environments
can increase their ability to do the same in the real world.
Abstract: This paper attempts to investigate the factors that influence hotel managers- attitudes towards sustainable tourism practices (STP) in Kuala Lumpur and the state of Selangor in Malaysia. The study distributes 104 questionnaires to hotels ranging from one star to five-star categories including budget hotels. Out of this figure, 60 copies of the questionnaires were returned and analyzed. The finding revealed that of all the seven factors investigated, only the variables measuring incentives and knowledge have significantly influenced sustainable tourism practices in the country. Therefore, government and other green bodies within the country should continue to provide hotels with incentives for sound technologies. Moreover, the government agencies should continue to educate hoteliers on the relevance of environmental protection for the successful implementation of sustainable tourism practices.
Abstract: Mounds are one of the most valuable sources of
information on various aspects of life, household skills, rituals and
beliefs of the ancient peoples of Kazakhstan. Moreover, the objects
associated with the cult of the burial of the dead are the most
informative, and often the only source of knowledge about past eras.
The present study is devoted to some results of the excavations
carried out on the mound "Baygetobe" of Shilikti burial ground. The
purpose of the work is associated with certain categories of grave
goods and reading "Fine Text" of Shilikti graves, whose structure is
the same for burials of nobles and ordinary graves. The safety of a
royal burial mounds, the integrity and completeness of the source are
of particular value for studying.
Abstract: Modern culture, based on disinhibition of cultural trends and on heterodirection, is promoting openmindedness attitudes towards ethnic diversity, but on the other hand also new forms of social representations of the foreigner. Social representation is situated between the psychic field and the social one; it is the representation of oneself and of the other one, hanging between social categories and individual inner world. We will produce the results of a research on the representation of the foreigner, built on the type of prejudice prevailing among middle-low or middle-high educational qualification subjects, in which prejudicial attitudes seem to descend from precise mental images of the foreigner.
Abstract: Classification of electroencephalogram (EEG) signals
extracted during mental tasks is a technique that is actively pursued
for Brain Computer Interfaces (BCI) designs. In this paper, we
compared the classification performances of univariateautoregressive
(AR) and multivariate autoregressive (MAR) models
for representing EEG signals that were extracted during different
mental tasks. Multilayer Perceptron (MLP) neural network (NN)
trained by the backpropagation (BP) algorithm was used to classify
these features into the different categories representing the mental
tasks. Classification performances were also compared across
different mental task combinations and 2 sets of hidden units (HU): 2
to 10 HU in steps of 2 and 20 to 100 HU in steps of 20. Five different
mental tasks from 4 subjects were used in the experimental study and
combinations of 2 different mental tasks were studied for each
subject. Three different feature extraction methods with 6th order
were used to extract features from these EEG signals: AR
coefficients computed with Burg-s algorithm (ARBG), AR
coefficients computed with stepwise least square algorithm (ARLS)
and MAR coefficients computed with stepwise least square
algorithm. The best results were obtained with 20 to 100 HU using
ARBG. It is concluded that i) it is important to choose the suitable
mental tasks for different individuals for a successful BCI design, ii)
higher HU are more suitable and iii) ARBG is the most suitable
feature extraction method.
Abstract: Aggression is a behavior that cannot be approved by
the society. Vandalism which is aggression towards objects is an
action that tends to damage public or personal property. The
behaviors that are described as vandalism can often be observed in
the schools as well. According to Zwier and Vaughan (1)
previous research about the reasons of and precautionary measures
for vandalism in schools can be grouped in three tendency categories:
conservative, liberal and radical. In this context, the main aim of this
study is to discover which ideological tendency of the reasons of
school vandalism is adopted by the teachers and what are their
physical, environmental, school system and societal solutions for
vandalism. A total of 200 teachers participated in this study, and the
mean age was 34.20 years (SD = 6.54). The sample was made up of
109 females and 91 males. For the analysis of the data, SPSS 15.00,
frequency, percentage, and t-test were used. The research showed
that the teachers have tendencies in the order of conservative, liberal
and radical for the reasons of vandalism. The research also showed
that the teachers do not have any tendency for eliminating vandalism
physically and general solutions on the level of society; on the other
hand they mostly adopt a conservative tendency in terms of
precautions against vandalism in the school system. Second most,
they adopt the liberal tendency in terms of precautions against
vandalism in the school system. . It is observed that the findings of
this study are comparable to the existing literature on the subject.
Future studies should be conducted with multiple variants and
bigger sampling.
Abstract: We depend upon explanation in order to “make sense"
out of our world. And, making sense is all the more important when
dealing with change. But, what happens if our explanations are
wrong? This question is examined with respect to two types of
explanatory model. Models based on labels and categories we shall
refer to as “representations." More complex models involving
stories, multiple algorithms, rules of thumb, questions, ambiguity we
shall refer to as “compressions." Both compressions and
representations are reductions. But representations are far more
reductive than compressions. Representations can be treated as a set
of defined meanings – coherence with regard to a representation is
the degree of fidelity between the item in question and the definition
of the representation, of the label. By contrast, compressions contain
enough degrees of freedom and ambiguity to allow us to make
internal predictions so that we may determine our potential actions in
the possibility space. Compressions are explanatory via mechanism.
Representations are explanatory via category. Managers are often
confusing their evocation of a representation (category inclusion) as
the creation of a context of compression (description of mechanism).
When this type of explanatory error occurs, more errors follow. In
the drive for efficiency such substitutions are all too often proclaimed
– at the manager-s peril..
Abstract: Flexible manufacturing system is a system that is able to respond to changed conditions. In general, this flexibility is divided into two key categories and several subcategories. The first category is the so called machine flexibility which enables to make various products by the given machinery. The second category is routing flexibility enabling to execute the same operation by various machines. Flexible manufacturing systems usually consist of three main parts: CNC machine tools, transport system and control system. A higher level of flexible manufacturing systems is represented by the so called intelligent manufacturing systems.
Abstract: In construction of any structure, the aesthetic and utility values should be considered in such a way as to make the structure cost-effective. Most structures are composed of elements and joints which are very critical in any skeletal space structure because they majorly determine the performance of the structure. In early times, most space structures were constructed using rigid joints which had the advantage of better performing structures as compared to pin-jointed structures but with the disadvantage of requiring all the construction work to be done on site. The discovery of semi-rigid joints now enables connections to be prefabricated and quickly assembled on site while maintaining good performance. In this paper, cost-effective is discussed basing on strength of connectors at the joints, buckling of joints and overall structure, and the effect of initial geometrical imperfections. Several existing joints are reviewed by classifying them into categories and discussing where they are most suited and how they perform structurally. Also, finite element modeling using ABAQUS is done to determine the buckling behavior. It is observed that some joints are more economical than others. The rise to span ratio and imperfections are also found to affect the buckling of the structures. Based on these, general principles that guide the design of cost-effective joints and structures are discussed.
Abstract: In this paper we propose a new approach for flexible document categorization according to the document type or genre instead of topic. Our approach implements two homogenous classifiers: contextual classifier and logical classifier. The contextual classifier is based on the document URL, whereas, the logical classifier use the logical structure of the document to perform the categorization. The final categorization is obtained by combining contextual and logical categorizations. In our approach, each document is assigned to all predefined categories with different membership degrees. Our experiments demonstrate that our approach is best than other genre categorization approaches.
Abstract: Adolescents in Northern Uganda are at risk of teenage
pregnancies, unsafe abortions and sexually transmitted infections
(STIs). There is silence on sex both at home and school. This cross
sectional descriptive analytical study interviews a random sample of
827 students and 13 teachers on knowledge, perception and
acceptability to a comprehensive adolescent sexual and reproductive
health education in “O” and “A” level secondary schools in Gulu
District. Quantitative data was analyzed using SPSS 16.0. Directed
content analysis of themes of transcribed qualitative data was
conducted manually for common codes, sub-categories and
categories. Of the 827 students; 54.3% (449) reported being in a
sexual relationship especially those aged 15-17 years. Majority
96.1% (807) supported the teaching of a comprehensive ASRHE,
citing no negative impact 71.5% (601). Majority 81.6% (686) agreed
that such education could help prevention of STIs, abortions and
teenage pregnancies, and that it should be taught by health workers
69.0% (580). Majority 76.6% (203) reported that ASRHE was not
currently being taught in their schools. Students had low knowledge
levels and misconceptions about ASRHE. ASRHE was highly
acceptable though not being emphasized; its success in school
settings requires multidisciplinary culturally sensitive approaches
amongst which health workers should be frontiers.
Abstract: This paper proposes an auto-classification algorithm
of Web pages using Data mining techniques. We consider the
problem of discovering association rules between terms in a set of
Web pages belonging to a category in a search engine database, and
present an auto-classification algorithm for solving this problem that
are fundamentally based on Apriori algorithm. The proposed
technique has two phases. The first phase is a training phase where
human experts determines the categories of different Web pages, and
the supervised Data mining algorithm will combine these categories
with appropriate weighted index terms according to the highest
supported rules among the most frequent words. The second phase is
the categorization phase where a web crawler will crawl through the
World Wide Web to build a database categorized according to the
result of the data mining approach. This database contains URLs and
their categories.
Abstract: Healthcare providers sometimes use the power of
humor as a treatment and therapy for buffering mental health or easing
mental disorders because humor can provide relief from distress and
conflict. Humor is also very suitable for advertising because of similar
benefits. This study carefully examines humor's widespread use in
advertising and identifies relationships among humor mechanisms,
female depictions, and product types. The purpose is to conceptualize
how humor theories can be used not only to successfully define a
product as fitting within one of four color categories of the product
color matrix, but also to identify compelling contemporary female
depictions through humor in ads. The results can offer an idealization
for marketing managers and consumers to help them understand how
female role depictions can be effectively used with humor in ads. The
four propositions developed herein are derived from related literature,
through the identification of marketing strategy formulations that
achieve product memory enhancement by adopting humor
mechanisms properly matched with female role depictions.