Abstract: Deconstruction is an approach that is entirely incompatible with the traditional prevalent architecture. Considering the fact that this approach attempts to put architecture in sharp contrast with its opposite events and transpires with attending to the neglected and missing aspects of architecture and deconstructing its stable structures. It also recklessly proceeds beyond the existing frameworks and intends to create a different and more efficient prospect for space. The aim of deconstruction architecture is to satisfy both the prospective and retrospective visions as well as takes into account all tastes of the present in order to transcend time. Likewise, it ventures to fragment the facts and symbols of the past and extract new concepts from within their heart, which coincide with today’s circumstances. Since this approach is an attempt to surpass the limits of the prevalent architecture, it can be employed to design places in which creative events occur and imagination and ambition flourish. Thought-provoking artistic events can grow and mature in such places and be represented in the best way possible to all people. The concept of event proposed in the plan grows out of the interaction between space and creation. In addition to triggering surprise and high impressions, it is also considered as a bold journey into the suspended realms of the traditional conflicts in architecture such as architecture-landscape, interior-exterior, center-margin, product-process, and stability-instability. In this project, at first, through interpretive-historical research method and examining the inputs and data collection, recognition and organizing takes place. After evaluating the obtained data using deductive reasoning, the data is eventually interpreted. Given the fact that the research topic is in its infancy and there is not a similar case in Iran with limited number of corresponding instances across the world, the selected topic helps to shed lights on the unrevealed and neglected parts in architecture. Similarly, criticizing, investigating and comparing specific and highly prized cases in other countries with the project under study can serve as an introduction into this architecture style.
Abstract: During airport planning and design stages, the major issues of capacity and safety in construction and operation of an airport need to be taken into consideration. The airside of an airport is a major and critical infrastructure that usually consists of runway(s), taxiway system, and apron(s) etc., which have to be designed according to the international standards and recommendations, and local limitations to accommodate the forecasted demands. However, in many cases, airport airsides are suffering from unexpected risks that occurred during airport operations. Therefore, safety risk assessment should be applied in the planning and design of airsides to cope with the probability of risks and their consequences, and to make decisions to reduce the risks to as low as reasonably practicable (ALARP) based on safety risk assessment. This paper presents a combination approach of Failure Modes, Effect, and Criticality Analysis (FMECA), Fuzzy Reasoning Approach (FRA), and Fuzzy Analytic Hierarchy Process (FAHP) to develop a risk analysis model for safety risk assessment. An illustrated example is used to the demonstrate risk assessment process on how the design of an airside in an airport can be analysed by using the proposed safety design risk assessment model.
Abstract: Online Social Networks (OSNs) are nowadays being used widely and intensively for crime investigation and prevention activities. As they provide a lot of information they are used by the law enforcement and intelligence. An extensive review on existing solutions and models for collecting intelligence from this source of information and making use of it for solving crimes has been presented in this article. The main focus is on smart solutions and models where ontologies have been used as the main approach for representing criminal domain knowledge. A framework for a prototype ontology named SC-Ont will be described. This defines terms of the criminal domain ontology and the relations between them. The terms and the relations are extracted during both this review and the discussions carried out with domain experts. The development of SC-Ont is still ongoing work, where in this paper, we report mainly on the motivation for using smart ontology models and the possible benefits of using them for solving crimes.
Abstract: Information system risk management helps to reduce
or eliminate risk by implementing appropriate controls. In this paper,
we propose a quantification model of controls impact on information
system risks by automatizing the residual criticality estimation step of
FMECA which is based on a inductive reasoning. For this, we defined
three equations based on type and maturity of controls. For testing,
the values obtained with the model were compared to estimated
values given by interlocutors during different working sessions and
the result is satisfactory. This model allows an optimal assessment of
controls maturity and facilitates risk analysis of information system.
Abstract: Radio Frequency Identification (RFID) has become a
key technology in the emerging concept of Internet of Things (IoT).
Naturally, business applications would require the deployment of
various RFID systems developed by different vendors that use
different data formats and structures. This heterogeneity poses a
challenge in developing real-life IoT systems with RFID, as
integration is becoming very complex and challenging. Semantic
integration is a key approach to deal with this challenge. To do so,
ontology for RFID systems need to be developed in order to
annotated semantically RFID systems, and hence, facilitate their
integration. Accordingly, in this paper, we propose ontology for
RFID systems. The proposed ontology can be used to semantically
enrich RFID systems, and hence, improve their usage and reasoning.
Abstract: The last two decades witnessed a movement towards
harmonization of international financial reporting standards (IFRS)
throughout the global economy. This investigation seeks to identify
the factors that could explain the adoption of IFRS by poor
jurisdictions. While there has been a considerable amount of
literature published on the effects and key drivers of IFRS adoption
in both developed and developing countries, little attention has been
paid to jurisdictions with less developed capital markets and low
income levels exclusively. Drawing upon the Institutional Isomorphism theory and analyzing
a sample of 45 poor jurisdictions between 2008 and 2013, the study
empirically shows that poor jurisdictions are driven by legitimacy
concerns rather than by economic reasoning to adopt an international
accounting perspective. This in turn has implications for the IASB, as
it should seek to influence institutional pressures within a particular
jurisdiction in order to promote IFRS adoption.
Abstract: In order to be capable of dealing with uncertainties,
subjectivities, including vagueness arising in building construction
projects, the application of fuzzy reasoning technique based on fuzzy
set theory is proposed. This study contributes significantly to the
development of a fuzzy reasoning safety risk assessment model for
building construction projects that could be employed to assess the
risk magnitude of each hazardous event identified during
construction, and a third parameter of probability of consequence is
incorporated in the model. By using the proposed safety risk analysis
methodology, more reliable and less ambiguities, which provide the
safety risk management project team for decision-making purposes.
Abstract: Psychopathic disorders are taking an important part in
judge sentencing, especially in Canada. First, we will see how this
phenomenon can be illustrated by the high proportion of psychopath
offenders incarcerated in North American prisons. Many decisions in
Canadians courtrooms seem to point out that psychopathy is often
used as a strong argument by the judges to preserve public safety.
The fact that psychopathy is often associated with violence,
recklessness and recidivism, could explain why many judges consider
psychopathic disorders as an aggravating factor. Generally, the judge
reasoning is based on Article 753 of Canadian Criminal Code related
to dangerous offenders, which is used for individuals who show a
pattern of repetitive and persistent aggressive behaviour. Then we
will show how, with cognitive neurosciences, the psychopath’s
situation in courtrooms would probably change. Cerebral imaging
and news data provided by the neurosciences show that emotional
and volitional functions in psychopath’s brains are impaired.
Understanding these new issues could enable some judges to
recognize psychopathic disorders as a mitigating factor. Finally, two
important questions ought to be raised in this article: can exploring
psychopaths ‘brains really change the judge sentencing in Canadian
courtrooms? If yes, can judges consider psychopathy more as a
mitigating factor than an aggravating factor?
Abstract: A knowledge base stores facts and rules about the
world that applications can use for the purpose of reasoning. By
applying the concept of granular computing to a knowledge base,
several advantages emerge. These can be harnessed by applications
to improve their capabilities and performance. In this paper, the
concept behind such a construct, called a granular knowledge cube,
is defined, and its intended use as an instrument that manages to
cope with different data types and detect knowledge domains is
elaborated. Furthermore, the underlying architecture, consisting of the
three layers of the storing, representing, and structuring of knowledge,
is described. Finally, benefits as well as challenges of deploying it
are listed alongside application types that could profit from having
such an enhanced knowledge base.
Abstract: This study, for its research subjects, uses patients who
had undergone total knee replacement surgery from the database of the
National Health Insurance Administration. Through the review of
literatures and the interviews with physicians, important factors are
selected after careful screening. Then using Cross Entropy Method,
Genetic Algorithm Logistic Regression, and Particle Swarm
Optimization, the weight of each factor is calculated and obtained. In
the meantime, Excel VBA and Case Based Reasoning are combined
and adopted to evaluate the system. Results show no significant
difference found through Genetic Algorithm Logistic Regression and
Particle Swarm Optimization with over 97% accuracy in both
methods. Both ROC areas are above 0.87. This study can provide
critical reference to medical personnel as clinical assessment to
effectively enhance medical care quality and efficiency, prevent
unnecessary waste, and provide practical advantages to resource
allocation to medical institutes.
Abstract: This paper describes the main features of a knowledge-based system evaluation method. System evaluation is placed in the context of a hybrid legal decision-support system, Advisory Support for Home Settlement in Divorce (ASHSD). Legal knowledge for ASHSD is represented in two forms, as rules and previously decided cases. Besides distinguishing the two different forms of knowledge representation, the paper outlines the actual use of these forms in a computational framework that is designed to generate a plausible solution for a given case, by using rule-based reasoning (RBR) and case-based reasoning (CBR) in an integrated environment. The nature of suitability assessment of a solution has been considered as a multiple criteria decision-making process in ASHAD evaluation. The evaluation was performed by a combination of discussions and questionnaires with different user groups. The answers to questionnaires used in this evaluations method have been measured as a fuzzy linguistic term. The finding suggests that fuzzy linguistic evaluation is practical and meaningful in knowledge-based system development purpose.
Abstract: Ontology validation is an important part of web
applications’ development, where knowledge integration and
ontological reasoning play a fundamental role. It aims to ensure the
consistency and correctness of ontological knowledge and to
guarantee that ontological reasoning is carried out in a meaningful
way. Existing approaches to ontology validation address more or less
specific validation issues, but the overall process of validating web
ontologies has not been formally established yet. As the size and the
number of web ontologies continue to grow, more web applications’
developers will rely on the existing repository of ontologies rather
than develop ontologies from scratch. If an application utilizes
multiple independently created ontologies, their consistency must be
validated and eventually adjusted to ensure proper interoperability
between them. This paper presents a validation technique intended to
test the consistency of independent ontologies utilized by a common
application.
Abstract: Some plants of genus Schinus have been used in the
folk medicine as topical antiseptic, digestive, purgative, diuretic,
analgesic or antidepressant, and also for respiratory and urinary
infections. Chemical composition of essential oils of S. molle and S.
terebinthifolius had been evaluated and presented high variability
according with the part of the plant studied and with the geographic
and climatic regions. The pharmacological properties, namely
antimicrobial, anti-tumoural and anti-inflammatory activities are
conditioned by chemical composition of essential oils. Taking into
account the difficulty to infer the pharmacological properties of
Schinus essential oils without hard experimental approach, this work
will focus on the development of a decision support system, in terms
of its knowledge representation and reasoning procedures, under a
formal framework based on Logic Programming, complemented with
an approach to computing centered on Artificial Neural Networks
and the respective Degree-of-Confidence that one has on such an
occurrence.
Abstract: This paper contains the description of argumentation
approach for the problem of inductive concept formation. It is
proposed to use argumentation, based on defeasible reasoning with
justification degrees, to improve the quality of classification models,
obtained by generalization algorithms. The experiment’s results on
both clear and noisy data are also presented.
Abstract: In this paper the problem of the application of
temporal reasoning and case-based reasoning in intelligent decision
support systems is considered. The method of case-based reasoning
with temporal dependences for the solution of problems of real-time
diagnostics and forecasting in intelligent decision support systems is
described. This paper demonstrates how the temporal case-based
reasoning system can be used in intelligent decision support systems
of the car access control. This work was supported by RFBR.
Abstract: The aim of this paper is to understand emerging
learning conditions, when a visual analytics is implemented and used
in K 12 (education). To date, little attention has been paid to the role
visual analytics (digital media and technology that highlight visual
data communication in order to support analytical tasks) can play in
education, and to the extent to which these tools can process
actionable data for young students. This study was conducted in three
public K 12 schools, in four social science classes with students aged
10 to 13 years, over a period of two to four weeks at each school.
Empirical data were generated using video observations and analyzed
with help of metaphors within Actor-network theory (ANT). The
learning conditions are found to be distinguished by broad
complexity, characterized by four dimensions. These emerge from
the actors’ deeply intertwined relations in the activities. The paper
argues in relation to the found dimensions that novel approaches to
teaching and learning could benefit students’ knowledge building as
they work with visual analytics, analyzing visualized data.
Abstract: This paper introduces a proposal scheme for an
Intelligent System applied to Pedagogical Advising using Case-Based
Reasoning, to find consolidated solutions before used for the new
problems, making easier the task of advising students to the
pedagogical staff. We do intend, through this work, introduce the
motivation behind the choices for this system structure, justifying the
development of an incremental and smart web system who learns
bests solutions for new cases when it’s used, showing technics and
technology.
Abstract: Content Based Image Retrieval (CBIR) coupled with
Case Based Reasoning (CBR) is a paradigm that is becoming
increasingly popular in the diagnosis and therapy planning of medical
ailments utilizing the digital content of medical images. This paper
presents a survey of some of the promising approaches used in the
detection of abnormalities in retina images as well in
mammographic screening and detection of regions of interest
in MRI scans of the brain. We also describe our proposed
algorithm to detect hard exudates in fundus images of the
retina of Diabetic Retinopathy patients.
Abstract: A knowledge-based expert system with the acronym
RASPE is developed as an application tool to help decision makers in
construction companies make informed decisions about managing
risks in pipeline construction projects. Choosing to use expert
systems from all available artificial intelligence techniques is due to
the fact that an expert system is more suited to representing a
domain’s knowledge and the reasoning behind domain-specific
decisions. The knowledge-based expert system can capture the
knowledge in the form of conditional rules which represent various
project scenarios and potential risk mitigation/response actions. The
built knowledge in RASPE is utilized through the underlying
inference engine that allows the firing of rules relevant to a project
scenario into consideration. Paper provides an overview of the
knowledge acquisition process and goes about describing the
knowledge structure which is divided up into four major modules.
The paper shows one module in full detail for illustration purposes
and concludes with insightful remarks.
Abstract: Food as perishable goods represents a specific and
sensitive part in the supply chain theory, since changing physical or
chemical characteristics considerably influence the approach to stock
management. The most delicate phase of this process is
transportation, where it becomes difficult to ensure the stable
conditions which limit deterioration, since the value of the
deterioration rate could be easily influenced by the mode of
transportation. The fuzzy definition of variables allows one to take
these variations into account. Furthermore, an appropriate choice of
the defuzzification method permits one to adapt results to real
conditions as far as possible. In this article those methods which take
into account the relationship between the deterioration rate of
perishable goods and transportation by ship will be applied with the
aim of (a) minimizing the total cost function, defined as the sum of
the ordering cost, holding cost, disposing cost and transportation
costs, and (b) improving the supply chain sustainability by reducing
environmental impact and waste disposal costs.