Abstract: This paper discusses the use of a computerized test to measure the decision-making abilities of teenage basketball players in Singapore. There are five sections in this test – Competitive state anxiety inventory-2 (CSAI-2) questionnaire (measures player’s cognitive anxiety, somatic anxiety and self-confidence), Corsi block-tapping task (measures player’s short-term spatial memory), situation awareness global assessment technique (SAGAT) (measures players’ situation awareness in a basketball game), multiple choice questions on basketball knowledge (measures players’ knowledge of basketball rules and concepts), and lastly, a learning test that requires participants to recall and recognize basketball set plays (measures player’s ability to learn and recognize set plays). A total of 25 basketball players, aged 14 to 16 years old, from three secondary school teams participated in this experiment. The results that these basketball players obtained from this cognitive test were then used to compare with their physical fitness and basketball performance.
Abstract: Soil tillage systems can be able to influence soil compaction, water dynamics, soil temperature and crop yield. These processes can be expressed as changes of soil microbiological activity, soil respiration and sustainability of agriculture. Objectives of this study were: 1 - to assess the effects of tillage systems (Conventional System (CS), Minimum Tillage (MT), No-Tillage (NT)) on soil compaction, soil temperature, soil moisture and soil respiration and 2- to establish the effect of the changes on the production of wheat, maize and soybean. Five treatments were installed: CS-plough; MT-paraplow, chisel, rotary grape; NT-direct sowing. The study was conducted on an Argic-Stagnic Faeoziom. The MT and NT applications reduce or completely eliminate the soil mobilization, due to this; soil is compacted in the first year of application. The degree of compaction is directly related to soil type and its state of degradation. The state of soil compaction diminished over time, tending toward a specific type of soil density. Soil moisture was higher in NT and MT at the time of sowing and in the early stages of vegetation and differences diminished over time. Moisture determinations showed statistically significant differences. The MT and NT applications reduced the thermal amplitude in the first 15cm of soil depth and increased the soil temperature by 0.5-2.20C. Water dynamics and soil temperature showed no differences on the effect of crop yields. The determinations confirm the effect of soil tillage system on soil respiration; the daily average was lower at NT (315-1914 mmoli m-2s-1) and followed by MT (318-2395 mmoli m-2s-1) and is higher in the CS (321-2480 mmol m-2s-1). Comparing with CS, all the four conservation tillage measures decreased soil respiration, with the best effects of no-tillage. Although wheat production at MT and NT applications, had no significant differences soybean production was significantly affected from MT and NT applications. The differences in crop yields are recorded at maize and can be a direct consequence of loosening, mineralization and intensive mobilization of soil fertility.
Abstract: This paper proposes a video-based framework for face recognition to identify which faces appear in a video sequence. Our basic idea is like a tracking task - to track a selection of person candidates over time according to the observing visual features of face images in video frames. Hence, we employ the state-space model to formulate video-based face recognition by dividing this problem into two parts: the likelihood and the transition measures. The likelihood measure is to recognize whose face is currently being observed in video frames, for which two-dimensional linear discriminant analysis is employed. The transition measure estimates the probability of changing from an incorrect recognition at the previous stage to the correct person at the current stage. Moreover, extra nodes associated with head nodes are incorporated into our proposed state-space model. The experimental results are also provided to demonstrate the robustness and efficiency of our proposed approach.
Abstract: In today's world, success of most systems depend on the use of new technologies and information technology (IT) which aimed to increase efficiency and satisfaction of users. One of the most important systems that use information technology to deliver services is the education system. But for educational services in the form of E-learning systems, hardware and software equipment should be containing high quality, which requires substantial investment. Because the vast majority of educational establishments can not invest in this area so the best way for them is reducing the costs and providing the E-learning services by using cloud computing. But according to the novelty of the cloud technology, it can create challenges and concerns that the most noted among them are security issues. Security concerns about cloud-based E-learning products are critical and security measures essential to protect valuable data of users from security vulnerabilities in products. Thus, the success of these products happened if customers meet security requirements then can overcome security threats. In this paper tried to explore cloud computing and its positive impact on E- learning and put main focus to identify security issues that related to cloud-based E-learning efforts which have been improve security and provide solutions in management challenges.
Abstract: Project management process starts from the planning stage up to the stage of completion (handover of buildings, preparation of the final accounts and the closing balance). Seeing as this process is not easy to be implemented efficiently and effectively, the issue of unsuccessful delivery as per contract in construction has become a major problem for construction projects. These issues have been blamed mainly on inefficient traditional construction practices that continue to dominate the current industry. This is due to several factors, such as environments of construction technology, sophisticated design and customer demand, that are constantly changing and influencing, either directly or indirectly, to the practice of management. Among the identified influences are physical environment, social environment, information environment, political and moral atmosphere. Therefore, this paper is emerged to determine the fundamental variables in the final account closing success in construction project. This aim can be achieved via its objectives of identifying the key constraints to the closing of final accounts in construction projects in Malaysia, investigating solutions to the identified constraints and analysing the relative levels of impact of the identified constraints. It is expected that this paper provides effective measures to avoid or at least reduce the problems in final account closing to the optimum level. It is also anticipated that the finding or outcome reported in this paper could address the unsuccessful contributors in final account closing and define tools for their mitigation for the better development of construction project.
Abstract: The Choquet integral is a tool for the information fusion that is very effective in the case where fuzzy measures associated with it are well chosen. In this paper, we propose a new approach for calculating fuzzy measures associated with the Choquet integral in a context of data fusion in multimodal biometrics. The proposed approach is based on genetic algorithms. It has been validated in two databases: the first base is relative to synthetic scores and the second one is biometrically relating to the face, fingerprint and palmprint. The results achieved attest the robustness of the proposed approach.
Abstract: This paper presents the early-warning lights
classification management system for industrial parks promoted by the
Taiwan Environmental Protection Administration (EPA) since 2011,
including the definition of each early-warning light, objectives, action
program and accomplishments. All of the 151 industrial parks in
Taiwan were classified into four early-warning lights, including red,
orange, yellow and green, for carrying out respective pollution
management according to the monitoring data of soil and groundwater
quality, regulatory compliance, and regulatory listing of control site or
remediation site. The Taiwan EPA set up a priority list for high
potential polluted industrial parks and investigated their soil and
groundwater qualities based on the results of the light classification
and pollution potential assessment. In 2011-2013, there were 44
industrial parks selected and carried out different investigation, such as
the early warning groundwater well networks establishment and
pollution investigation/verification for the red and orange-light
industrial parks and the environmental background survey for the
yellow-light industrial parks. Among them, 22 industrial parks were
newly or continuously confirmed that the concentrations of pollutants
exceeded those in soil or groundwater pollution control standards.
Thus, the further investigation, groundwater use restriction, listing of
pollution control site or remediation site, and pollutant isolation
measures were implemented by the local environmental protection and
industry competent authorities; the early warning lights of those
industrial parks were proposed to adjust up to orange or red-light. Up
to the present, the preliminary positive effect of the soil and
groundwater quality management system for industrial parks has been
noticed in several aspects, such as environmental background
information collection, early warning of pollution risk, pollution
investigation and control, information integration and application, and
inter-agency collaboration. Finally, the work and goal of self-initiated
quality management of industrial parks will be carried out on the basis
of the inter-agency collaboration by the classified lights system of
early warning and management as well as the regular announcement of
the status of each industrial park.
Abstract: Missing values in data are common in real world applications. Since the performance of many data mining algorithms depend critically on it being given a good metric over the input space, we decided in this paper to define a distance function for unlabeled
datasets with missing values. We use the Bhattacharyya distance, which measures the similarity of two probability distributions, to define our new distance function. According to this distance, the distance between two points without missing attributes values is simply the Mahalanobis distance. When on the other hand there is a missing value of one of the coordinates, the distance is computed according to the distribution of the missing coordinate. Our distance is general and can be used as part of any algorithm that computes the distance between data points. Because its performance depends strongly on the chosen distance measure, we opted for the k nearest neighbor classifier to evaluate its ability to accurately reflect object similarity. We experimented on standard numerical datasets from the UCI repository from different fields. On these datasets we simulated missing values and compared the performance of the kNN classifier using our distance to other three basic methods. Our experiments show that kNN using our distance function outperforms the kNN using other methods. Moreover, the runtime performance of our method is only slightly higher than the other methods.
Abstract: This paper presents a finite buffer renewal input single working vacation and vacation interruption queue with state dependent services and state dependent vacations, which has a wide range of applications in several areas including manufacturing, wireless communication systems. Service times during busy period, vacation period and vacation times are exponentially distributed and are state dependent. As a result of the finite waiting space, state dependent services and state dependent vacation policies, the analysis of these queueing models needs special attention. We provide a recursive method using the supplementary variable technique to compute the stationary queue length distributions at pre-arrival and arbitrary epochs. An efficient computational algorithm of the model is presented which is fast and accurate and easy to implement. Various performance measures have been discussed. Finally, some special cases and numerical results have been depicted in the form of tables and graphs.
Abstract: This paper presents quantitative component criticality importance indices applicable for identifying and ranking critical components in the phase of thermal power plants design. Identifying critical components for power plant reliability provides one important input to decision-making and guidance throughout the development project. The study of components criticality importance indices to several characteristic structural schemes of conventional thermal power plant is presented and discussed.
Abstract: An efficient freeway system will be essential to the
development of Africa, and interchanges are a key to that efficiency.
Around the world, many interchanges between freeways and surface
streets, called service interchanges, are of the diamond configuration,
and interchanges using roundabouts or loop ramps are also popular.
However, many diamond interchanges have serious operational
problems, interchanges with roundabouts fail at high demand levels,
and loops use lots of expensive land. Newer service interchange
designs provide other options. The most popular new interchange
design in the US at the moment is the double crossover diamond
(DCD), also known as the diverging diamond. The DCD has
enormous potential, but also has several significant limitations.
The objectives of this paper are to review new service interchange
options and to highlight some of the main features of those
alternatives. The paper tests four conventional and seven
unconventional designs using seven measures related to efficiency,
cost, and safety.
The results show that there is no superior design in all measures
investigated. The DCD is better than most designs tested on most
measures examined. However, the DCD was only superior to all
other designs for bridge width. The DCD performed relatively poorly
for capacity and for serving pedestrians. Based on the results, African
freeway designers are encouraged to investigate the full range of
alternatives that could work at the spot of interest. Diamonds and
DCDs have their niches, but some of the other designs investigated
could be optimum at some spots.
Abstract: In times of global warming and the increasing
shortage of resources, sustainable production is becoming more and
more inevitable. Companies cannot only heighten their
competitiveness but also contribute positively to environmental
protection through efficient energy and resource consumption.
Regarding this, technical solutions are often preferred during
production, although organizational and process-related approaches
also offer great potential. This project focuses on reducing resource
usage, with a special emphasis on the human factor. It is the
aspiration to develop a methodology that systematically implements
and embeds suitable and individual measures and methods regarding
resource efficiency throughout the entire production. The measures
and methods established help employees handle resources and energy
more sensitively. With this in mind, this paper also deals with the
difficulties that can occur during the sensitization of employees and
the implementation of these measures and methods. In addition,
recommendations are given on how to avoid such difficulties.
Abstract: Electrification is a complex process and governed by various parameters. Modeling of power plant’s target efficiency or target heat rate is often formulated and compared with the actual values. This comparison not only implies the performance of the power plant but also reflects the energy losses possibly inherited in some of related equipment and processes. The current modeling of Coal-fired Mae Moh power plant was formulated at the first commissioning. Some of equipments were replaced due to its life time. Relatively outdated for 20 years, the utilization of the model is not accomplished. This work has focused on the development of the performance analysis model of aforementioned power plant according to the most updated and current working conditions. The model is more appropriate and shows accuracy in its analysis. Losses are detected and measures are introduced such that reduction in energy consumption, related cost, and also environment impacts can be anticipated.
Abstract: The gap between the selection of risk-reduction options in the railway industry and the task of their effective implementation results in compromised safety and substantial losses. An effective risk management must necessarily integrate the evaluation phases with the implementation phase. This paper proposes an essential categorisation of risk reduction measures that best addresses a standard railway industry portfolio. By categorising the risk reduction options into design, operational, procedural and technical options, it is guaranteed that the efforts of the implementation facilitators (people, processes and supporting systems) are systematically harmonised. The classification is based on an integration of fundamental principles of risk reduction in the railway industry with the systems engineering approach.
This paper argues that the use of a similar classification approach is an attribute of organisations possessing a superior level of risk-reduction readiness. The integration of the proposed rational classification structure provides a solid ground for effective risk reduction.
Abstract: Knowledge is increasingly recognised in this, the
knowledge era, as a strategic resource, by public sector organisations,
in view of the public sector reform initiatives. People and knowledge
play a vital role in attaining improved organisational performance
and high service quality. Many government departments in the public
sector have started to realise the importance of knowledge
management in streamlining their operations and processes. This
study focused on knowledge management in the public healthcare
service organisations, where the concept of service provider
competitiveness pales to insignificance, considering the huge
challenges emanating from the healthcare and public sector reforms.
Many government departments are faced with challenges of
improving organisational performance and service delivery,
improving accountability, making informed decisions, capturing the
knowledge of the aging workforce, and enhancing partnerships with
stakeholders.
The purpose of this paper is to examine the knowledge
management practices of the Gauteng Department of Health in South
Africa, in order to understand how knowledge management practices
influence improvement in organisational performance and healthcare
service delivery. This issue is explored through a review of literature
on dominant views on knowledge management and healthcare service
delivery, as well as results of interviews with, and questionnaire
responses from, the general staff of the Gauteng Department of
Health. Web-based questionnaires, face-to-face interviews and
organisational documents were used to collect data. The data were
analysed using both the quantitative and qualitative methods. The
central question investigated was: To what extent can the conditions
required for successful knowledge management be observed, in order
to improve organisational performance and healthcare service
delivery in the Gauteng Department of Health.
The findings showed that the elements of knowledge management
capabilities investigated in this study, namely knowledge creation,
knowledge sharing and knowledge application, have a positive,
significant relationship with all measures of organisational
performance and healthcare service delivery. These findings thus
indicate that by employing knowledge management principles, the
Gauteng Department of Health could improve its ability to achieve its
operational goals and objectives, and solve organisational and
healthcare challenges, thereby improving organisational performance
and enhancing healthcare service delivery in Gauteng.
Abstract: The exponential increase in the volume of medical image database has imposed new challenges to clinical routine in maintaining patient history, diagnosis, treatment and monitoring. With the advent of data mining and machine learning techniques it is possible to automate and/or assist physicians in clinical diagnosis. In this research a medical image classification framework using data mining techniques is proposed. It involves feature extraction, feature selection, feature discretization and classification. In the classification phase, the performance of the traditional kNN k nearest neighbor classifier is improved using a feature weighting scheme and a distance weighted voting instead of simple majority voting. Feature weights are calculated using the interestingness measures used in association rule mining. Experiments on the retinal fundus images show that the proposed framework improves the classification accuracy of traditional kNN from 78.57 % to 92.85 %.
Abstract: Provision of optical devices without proper instruction
and training may cause frustration resulting in rejection or incorrect
use of the magnifiers. However training in the use of magnifiers
increases the cost of providing these devices. This study compared
the efficacy of providing instruction alone and instruction plus
training in the use of magnifiers. 24 participants randomly assigned
to two groups. 15 received instruction and training and 9 received
instruction only. Repeated measures of print size and reading speed
were performed at pre, post training and follow up. Print size
decreased in both groups between pre and post training maintained at
follow up. Reading speed increased in both groups over time with the
training group demonstrating more rapid improvement. Whilst
overall outcomes were similar, training decreased the time required
to increase reading speed supporting the use of training for increased
efficiency. A cost effective form of training is suggested.
Abstract: A challenged control problem is when the
performance is pushed to the limit. The state-derivative feedback
control strategy directly uses acceleration information for feedback
and state estimation. The derivative part is concerned with the rateof-
change of the error with time. If the measured variable approaches
the set point rapidly, then the actuator is backed off early to allow it
to coast to the required level. Derivative action makes a control
system behave much more intelligently. A sensor measures the
variable to be controlled and the measured in formation is fed back to
the controller to influence the controlled variable. A high gain
problem can be also formulated for proportional plus derivative
feedback transformation. Using MATLAB Simulink dynamic
simulation tool this paper examines a system with a proportional plus
derivative feedback and presents an automatic implementation of
finding an acceptable controlled system. Using feedback
transformations the system is transformed into another system.
Abstract: Most known methods for measuring the structural similarity of document structures are based on, e.g., tag measures, path metrics and tree measures in terms of their DOM-Trees. Other methods measures the similarity in the framework of the well known vector space model. In contrast to these we present a new approach to measuring the structural similarity of web-based documents represented by so called generalized trees which are more general than DOM-Trees which represent only directed rooted trees.We will design a new similarity measure for graphs representing web-based hypertext structures. Our similarity measure is mainly based on a novel representation of a graph as strings of linear integers, whose components represent structural properties of the graph. The similarity of two graphs is then defined as the optimal alignment of the underlying property strings. In this paper we apply the well known technique of sequence alignments to solve a novel and challenging problem: Measuring the structural similarity of generalized trees. More precisely, we first transform our graphs considered as high dimensional objects in linear structures. Then we derive similarity values from the alignments of the property strings in order to measure the structural similarity of generalized trees. Hence, we transform a graph similarity problem to a string similarity problem. We demonstrate that our similarity measure captures important structural information by applying it to two different test sets consisting of graphs representing web-based documents.
Abstract: Any use of energy in industrial productive activities is combined with various environment impacts. Withintransportation,
this fact was not only found among land transport, railways and maritime transport, but also in the air transport industry. An effective climate protection requires strategies and measures for reducing all
greenhouses gas emissions, in particular carbon dioxide, and must
take into account the economic, ecologic and social aspects. It seem simperative now to develop and manufacture environmentally
friendly products and systems, to reduce consumption and use less
resource, and to save energy and power. Today-sproducts could
better serve these requirements taking into account the integration of
a power management system into the electrical power system.This
paper gives an overview of an approach ofpower management with
load prioritization in modernaircraft. Load dimensioning and load
management strategies on current civil aircraft will be presented and
used as a basis for the proposed approach.