Abstract: The wellbeing of urban dwellers is strongly associated with the quality and quantity of green infrastructure. Nevertheless, urban green infrastructure is still lagging in many Arab cities, and Jordan is no exception. The capital city of Jordan, Amman, is becoming more urban dense with limited green spaces. The unplanned urban growth in Amman has caused several environmental problems such as urban heat islands, air pollution and lack of green spaces. This study aims to investigate the most suitable drivers to leverage the implementation of urban green infrastructure in Jordan through qualitative and quantitative analysis. The qualitative research includes an extensive literature review to discuss the most common drivers used internationally to promote urban green infrastructure implementation in the literature. The quantitative study employs a questionnaire survey to rank the suitability of each driver. Consultants, contractors and policymakers were invited to fill the research questionnaire according to their judgments and opinions. Relative Importance Index has been used to calculate the weighted average of all drivers and the Kruskal-Wallis test to check the degree of agreement among groups. This study finds that research participants agreed that indirect financial incentives (i.e., tax reductions, reduction in stormwater utility fee, reduction of interest rate, density bonus etc.) are the most effective incentive policy whilst granting sustainability certificate policy is the least effective driver to ensure widespread of UGI is elements in Jordan.
Abstract: Conformity is defined as one in a social group changing his or her behavior to match the others’ behavior in the group. It is used to find that people show a higher level of online conformity behavior than offline. However, as anonymity can decrease the level of online conformity behavior, the difference between online and offline conformity behavior among Chinese college students still needs to be tested. In this study, college students (N = 60) have been randomly assigned into three groups: control group, offline experimental group, and online experimental group. Through comparing the results of offline experimental group and online experimental group with the Mann-Whitney U test, this study verified the results of Asch’s experiment, and found out that people show a lower level of online conformity behavior than offline, which contradicted the previous finding found in China. These results can be used to explain why some people make a lot of vicious remarks and radical ideas on the Internet but perform normally in their real life: the anonymity of the network makes the online group pressure less than offline, so people are less likely to conform to social norms and public opinions on the Internet. What is more, these results support the importance and relevance of online voting, because fewer online group pressures make it easier for people to expose their true ideas, thus gathering more comprehensive and truthful views and opinions.
Abstract: Uncontrolled growth of abnormal cells in the lung in the form of tumor can be either benign (non-cancerous) or malignant (cancerous). Patients with Lung Cancer (LC) have an average of five years life span expectancy provided diagnosis, detection and prediction, which reduces many treatment options to risk of invasive surgery increasing survival rate. Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI) for earlier detection of cancer are common. Gaussian filter along with median filter used for smoothing and noise removal, Histogram Equalization (HE) for image enhancement gives the best results without inviting further opinions. Lung cavities are extracted and the background portion other than two lung cavities is completely removed with right and left lungs segmented separately. Region properties measurements area, perimeter, diameter, centroid and eccentricity measured for the tumor segmented image, while texture is characterized by Gray-Level Co-occurrence Matrix (GLCM) functions, feature extraction provides Region of Interest (ROI) given as input to classifier. Two levels of classifications, K-Nearest Neighbor (KNN) is used for determining patient condition as normal or abnormal, while Artificial Neural Networks (ANN) is used for identifying the cancer stage is employed. Discrete Wavelet Transform (DWT) algorithm is used for the main feature extraction leading to best efficiency. The developed technology finds encouraging results for real time information and on line detection for future research.
Abstract: Cardiologists perform cardiac auscultation to detect
abnormalities in heart sounds. Since accurate auscultation is
a crucial first step in screening patients with heart diseases,
there is a need to develop computer-aided detection/diagnosis
(CAD) systems to assist cardiologists in interpreting heart sounds
and provide second opinions. In this paper different algorithms
are implemented for automated heart sound classification using
unsegmented phonocardiogram (PCG) signals. Support vector
machine (SVM), artificial neural network (ANN) and cartesian
genetic programming evolved artificial neural network (CGPANN)
without the application of any segmentation algorithm has been
explored in this study. The signals are first pre-processed to remove
any unwanted frequencies. Both time and frequency domain features
are then extracted for training the different models. The different
algorithms are tested in multiple scenarios and their strengths and
weaknesses are discussed. Results indicate that SVM outperforms
the rest with an accuracy of 73.64%.
Abstract: Twitter is a microblogging platform, where millions of users daily share their attitudes, views, and opinions. Using a probabilistic Latent Dirichlet Allocation (LDA) topic model to discern the most popular topics in the Twitter data is an effective way to analyze a large set of tweets to find a set of topics in a computationally efficient manner. Sentiment analysis provides an effective method to show the emotions and sentiments found in each tweet and an efficient way to summarize the results in a manner that is clearly understood. The primary goal of this paper is to explore text mining, extract and analyze useful information from unstructured text using two approaches: LDA topic modelling and sentiment analysis by examining Twitter plain text data in English. These two methods allow people to dig data more effectively and efficiently. LDA topic model and sentiment analysis can also be applied to provide insight views in business and scientific fields.
Abstract: Accounting scandals and auditing frauds are perceived to be driven by aggressive companies and misrepresentation of audit reports. However, local legal systems and law enforcements may affect the services auditors provide to their ‘important’ clients. Under the civil law and common law jurisdictions, the standard setters, the government, and the regulatory bodies treat cases differently. As such, whether or not different forms of legal systems and extent of law enforcement plays an important role in auditor’s Audit Quality is a question this paper attempts to explore. The paper focuses on the investigation in Asia, where Hong Kong represents the common-law jurisdiction, while Taiwan and China represent the civil law jurisdiction. Only the ten reputable accounting firms are used in this study due to the differences in rankings and establishments of some of the small local audit firms. This will also contribute to the data collected between the years 2007-2013. By focusing on the use of multiple regression based on the dependent (Audit Quality) and independent variables (Client Importance, Law Enforcement, and Press Freedom), six different models are established. Results demonstrate that since different jurisdictions have different legal systems and market regulations, auditor’s treatment on ‘important’ clients will vary. However, with the moderators in place (law enforcement and press freedom), the relationship between client importance and audit quality may be smoothed out. With that in mind, this study contributes to local governments and standard setters’ consideration on legal reform and proper law enforcement in the market. Perhaps, with such modifications on the economic systems, collusion between companies and auditors can finally be put to a halt.
Abstract: Learning outcomes of a course (CLOs) and the abilities at the time of graduation referred to as Student Outcomes (SOs) are required to be assessed for ABET accreditation. A question in an assessment must target a CLO as well as an SO and must represent a required level of competence. This paper presents the idea of an Expert System (ES) to select a proper question to satisfy ABET accreditation requirements. For ES implementation, seven attributes of a question are considered including the learning outcomes and Bloom’s Taxonomy level. A database contains all the data about a course including course content topics, course learning outcomes and the CLO-SO relationship matrix. The knowledge base of the presented ES contains a pool of questions each with tags of the specified attributes. Questions and the attributes represent expert opinions. With implicit rule base the inference engine finds the best possible question satisfying the required attributes. It is shown that the novel idea of such an ES can be implemented and applied to a course with success. An application example is presented to demonstrate the working of the proposed ES.
Abstract: With the increasing number of people reviewing
products online in recent years, opinion sharing websites has become
the most important source of customers’ opinions. Unfortunately,
spammers generate and post fake reviews in order to promote or
demote brands and mislead potential customers. These are notably
destructive not only for potential customers, but also for business
holders and manufacturers. However, research in this area is not
adequate, and many critical problems related to spam detection have
not been solved to date. To provide green researchers in the domain
with a great aid, in this paper, we have attempted to create a highquality
framework to make a clear vision on review spam-detection
methods. In addition, this report contains a comprehensive collection
of detection metrics used in proposed spam-detection approaches.
These metrics are extremely applicable for developing novel
detection methods.
Abstract: This research focused on comparing the critical
thinking of the teacher students before and after using Miller’s Model
learning activities and investigating their opinions. The sampling
groups were (1) fourth year 33 student teachers majoring in Early
Childhood Education and enrolling in semester 1 of academic year
2013 (2) third year 28 student teachers majoring in English and
enrolling in semester 2 of academic year 2013 and (3) third year 22
student teachers majoring in Thai and enrolling in semester 2 of
academic year 2013. The research instruments were (1) lesson plans
where the learning activities were settled based on Miller’s Model (2)
critical thinking assessment criteria and (3) a questionnaire on
opinions towards Miller’s Model based learning activities. The
statistical treatment was mean, deviation, different scores and T-test.
The result unfolded that (1) the critical thinking of the students after
the assigned activities was better than before and (2) the students’
opinions towards the critical thinking improvement activities based
on Miller’s Model ranged from the level of high to highest.
Abstract: Safety is one of the most important considerations
when buying a new car. While active safety aims at avoiding
accidents, passive safety systems such as airbags and seat belts
protect the occupant in case of an accident. In addition to legal
regulations, organizations like Euro NCAP provide consumers with
an independent assessment of the safety performance of cars and
drive the development of safety systems in automobile industry.
Those ratings are mainly based on injury assessment reference values
derived from physical parameters measured in dummies during a car
crash test.
The components and sub-systems of a safety system are designed
to achieve the required restraint performance. Sled tests and other
types of tests are then carried out by car makers and their suppliers
to confirm the protection level of the safety system. A Knowledge
Discovery in Databases (KDD) process is proposed in order to
minimize the number of tests. The KDD process is based on the
data emerging from sled tests according to Euro NCAP specifications.
About 30 parameters of the passive safety systems from different data
sources (crash data, dummy protocol) are first analysed together with
experts opinions. A procedure is proposed to manage missing data
and validated on real data sets. Finally, a procedure is developed to
estimate a set of rough initial parameters of the passive system before
testing aiming at reducing the number of tests.
Abstract: The presence of endocrine-disrupting compounds,
such as bisphenol A (BPA), in the environment can cause serious
health problems. However, there are controversial opinions. This
study investigated the reproductive, metabolic, oxidative and
immunologic-disrupting effects of bisphenol A in male rabbits.
Rabbits were divided into five groups. The first four rabbit groups
were administered oral BPA (1, 10, 50, or 100 mg/kg/day) for ten
weeks. The fifth group was administered corn oil as the vehicle. BPA
significantly decreased serum testosterone, estradiol and the free
androgen index (FAI) and significantly increased sex hormone
binding globulin (SHBG) compared with the placebo group. The
higher doses of BPA showed a significant decrease in follicular
stimulating hormone (FSH) and luteinizing hormone (LH). A
significant increase in blood glucose levels was identified in the BPA
groups. The non-significant difference in insulin levels is a novel
finding. The cumulative testicular toxicity of BPA was clearly
demonstrated by the dose-dependent decrease in absolute testes
weight, primary measures of semen quality and a significant increase
in testicular malonaldehyde (MDA). Moreover, BPA significantly
decreased total antioxidant capacity (TAC) and significantly
increased immunoglobulin G (IgG) at the highest concentration. Our
results suggest that BPA, especially at higher doses, is associated
with many adverse effects on metabolism, oxidative stress, immunity,
sperm quality and markers of androgenic action.
Abstract: Online forum is part of a Learning Management
System (LMS) environment in which students share their opinions.
This study attempts to investigate the perceptions of students towards
online forum and their patterns of listening behavior during the forum
interaction. The students’ perceptions were measured using a
questionnaire, in which seven dimensions were used involving online
experience, benefits of forum participation, cost of participation,
perceived ease of use, usefulness, attitude, and intention. Meanwhile,
their patterns of listening behaviors were obtained using the log file
extracted from the LMS. A total of 25 postgraduate students
undertaking a course were involved in this study, and their activities
in the forum session were recorded by the LMS and used as a log file.
The results from the questionnaire analysis indicated that the students
perceived that the forum is easy to use, useful, and bring benefits to
them. Also, they showed positive attitude towards online forum, and
they have the intention to use it in future. Based on the log data, the
participants were also divided into six clusters of listening behavior,
in which they are different in terms of temporality, breadth, depth and
speaking level. The findings were compared to previous clusters
grouping and future recommendations are also discussed.
Abstract: The paper presents the method developed to assess
rating points of objects with qualitative indexes. The novelty of the
method lies in the fact that the authors use linguistic scales that allow
to formalize the values of the indexes with the help of fuzzy sets. As
a result it is possible to operate correctly with dissimilar indexes on
the unified basis and to get stable final results. The obtained rating
points are used in decision making based on fuzzy expert opinions.
Abstract: The issue of human anthropology took an important
role in the last epochs and still hasn-t lost its importance. Scientists of
different countries were interested in investigating the appearance of
human being and the idea of life after death. While writing this article
we noticed that scientists who made research in this issue, despite of
the different countries and different epochs in which they lived, had
similarities in their opinions. In given article we wrote great Kazakh
poet AbaiKunanbayev-s philosophical view to the problem of human
anthropology.
Abstract: This article analyses the peculiarities of Japan’s policy toward the countries of Central Asia. The increasing role of Central Asia in the system of international relations engendered an objective need for understanding of the policy of leading states, including Japan, in the region in the twenty-first century. The purpose of the study is to investigate the peculiarities of the formation and development of Japan policy in Central Asia and to identify the problems and prospects of Japan’s policy toward the countries of the region on the basis of experts’ opinions. In this article, the method of analysis of the situation and a systematic method were used. Prognostic methods, the collective expert assessment and scenarios were used in the study to determine the prospects of Japan’s policy toward the countries of Central Asia.
Abstract: One of the main research methods in humanistic studies is the collection and process of data through questionnaires. This paper reports our experiences of localizing and adapting the phpESP package of electronic surveys, which led to a friendly on-line questionnaire environment offered through our department web site. After presenting the characteristics of this environment, we identify the expected benefits and present a questionnaire carried out through both the traditional and electronic way. We present the respondents' feedback and then we report the researchers' opinions.Finally, we propose ideas we intend to implement in order to further assist and enhance the research based on this web accessed,electronic questionnaire environment.
Abstract: It is difficult to judge ripeness by outward
characteristics such as size or external color. In this paper a nondestructive
method was studied to determine watermelon (Crimson
Sweet) quality. Responses of samples to excitation vibrations were
detected using laser Doppler vibrometry (LDV) technology. Phase
shift between input and output vibrations were extracted overall
frequency range. First and second were derived using frequency
response spectrums. After nondestructive tests, watermelons were
sensory evaluated. So the samples were graded in a range of ripeness
based on overall acceptability (total desired traits consumers).
Regression models were developed to predict quality using obtained
results and sample mass. The determination coefficients of the
calibration and cross validation models were 0.89 and 0.71
respectively. This study demonstrated feasibility of information
which is derived vibration response curves for predicting fruit
quality. The vibration response of watermelon using the LDV method
is measured without direct contact; it is accurate and timely, which
could result in significant advantage for classifying watermelons
based on consumer opinions.