Abstract: This paper deals with the problem of management of
information resources in libraries of the public institution Sultan
Moulay Slimane University (SMSU) in order to analyze the
satisfaction of the readers, and allow university leaders to make better
strategic and instant decisions. For this, the integration of an
integrated management decision library system is a priority program
of higher education, as part of the Digital Morocco, which has a
proactive policy to develop the use of new technologies information
and communication in higher institutions. This operational
information system can provide better services to the students and for
the leaders. Our approach is to integrate the tools of business
intelligence (BI) in the library management by using power BI.
Abstract: Land reallocation is one of the most important steps in
land consolidation projects. Many different models were proposed for
land reallocation in the literature such as Fuzzy Logic, block priority
based land reallocation and Spatial Decision Support Systems. A
model including four parts is considered for automatic block
reallocation with genetic algorithm method in land consolidation
projects. These stages are preparing data tables for a project land,
determining conditions and constraints of land reallocation, designing
command steps and logical flow chart of reallocation algorithm and
finally writing program codes of Genetic Algorithm respectively. In
this study, we designed the first three steps of the considered model
comprising four steps.
Abstract: Consumers are demanding novel beverages that are
healthier, convenient and have appealing consumer acceptance. The
objectives of this study were to investigate the effects of adding grape
polyphenols and the influence of presenting health claims on the
sensory acceptability of wines. Fresh red sorrel calyces were
fermented into wines. The total soluble solids of the pectinase-treated
sorrel puree were from 4°Brix to 23.8°Brix. Polyphenol in the form
of grape pomace extract was added to sorrel wines (w/v) in specified
levels to give 0. 25. 50 and 75 ppm. A focus group comprising of 12
panelists was use to select the level of polyphenol to be added to
sorrel wines for sensory preference The sensory attributed of the
wines which were evaluated were colour, clarity, aroma, flavor,
mouth-feel, sweetness, astringency and overall preference. The sorrel
wine which was most preferred from focus group evaluation was
presented for hedonic rating. In the first stage of hedonic testing, the
sorrel wine was served chilled at 7°C for 24 h prior to sensory
evaluation. Each panelist was provided with a questionnaire and was
asked to rate the wines on colour, aroma, flavor, mouth-feel,
sweetness, astringency and overall acceptability using a 9-point
hedonic scale. In the second stage of hedonic testing, the panelist
were instructed to read a health abstract on the health benefits of
polyphenolic compounds and again to rate sorrel wine with added 25
ppm polyphenol. Paired t-test was used for the analysis of the
influence of presenting health information on polyphenols on hedonic
scoring of sorrel wines. Focus groups found that the addition of
polyphenol addition had no significant effect on sensory color and
aroma but affected clarity and flavor. A 25 ppm wine was liked
moderately in overall acceptability. The presentation of information
on the health benefit of polyphenols in sorrel wines to panelists had
no significant influence on the sensory acceptance of wine. More
than half of panelists would drink this wine now and then. This wine
had color L 19.86±0.68, chroma 2.10±0.12, hue° 16.90 ±3.10 and
alcohol content of 13.0%. The sorrel wine was liked moderately in
overall acceptability with the added polyphenols.
Abstract: Workflow scheduling is an important part of cloud
computing and based on different criteria it decides cost, execution
time, and performances. A cloud workflow system is a platform
service facilitating automation of distributed applications based on
new cloud infrastructure. An aspect which differentiates cloud
workflow system from others is market-oriented business model, an
innovation which challenges conventional workflow scheduling
strategies. Time and Cost optimization algorithm for scheduling
Hybrid Clouds (TCHC) algorithm decides which resource should be
chartered from public providers is combined with a new De-De
algorithm considering that every instance of single and multiple
workflows work without deadlocks. To offset this, two new concepts
- De-De Dodging Algorithm and Priority Based Decisive Algorithm -
combine with conventional deadlock avoidance issues by proposing
one algorithm that maximizes active (not just allocated) resource use
and reduces Makespan.
Abstract: ANDASA is a knowledge management platform for
the capitalization of knowledge and cultural assets for the artistic and
cultural sectors. It was built based on the priorities expressed by the
participating artists. Through mapping artistic activities and
specificities, it enables to highlight various aspects of the artistic
research and production. Such instrument will contribute to create
networks and partnerships, as it enables to evidentiate who does
what, in what field, using which methodology. The platform is
accessible to network participants and to the general public.
Abstract: This paper examines the relationship between
corporate governance rating and stock prices of 26 Turkish firms
listed in Turkish stock exchange (Borsa Istanbul) by using panel data
analysis over five-year period. The paper also investigates the stock
performance of firms with governance rating with regards to the
market portfolio (i.e. BIST 100 Index) both prior and after
governance scoring began. The empirical results show that there is no
relation between corporate governance rating and stock prices when
using panel data for annual variation in both rating score and stock
prices. Further analysis indicates surprising results that while the
selected firms outperform the market significantly prior to rating, the
same performance does not continue afterwards.
Abstract: This paper investigates the connotation, and some of
the realistic implications, of the economic reform of health sector in
under developed countries. The paper investigates the issues that
economic reforms have to address, and the policy targets they are
considered to accomplish. The work argues that the development of
economic reform is not connected only with understanding the
priorities and refining them, furthermore with reformation and
restructuring the organizations through which health policies are
employed. Considering various organizational values, that are likely
to be regular to all economic reform programs, a regulatory approach
to institutional reform is unsuitable. The paper further investigates the
selection of economic reform that may as well influence via technical
suggestions and analysis, but the verdict to continue, and the
consequent success of execution, eventually depends on the
progressive political sustainability. The paper concludes by giving
examples of institutional reforms from various underdeveloped
countries and includes recommendation of the responsibility and
control of donor organizations.
Abstract: Floorplanning plays a vital role in the physical design
process of Very Large Scale Integrated (VLSI) chips. It is an
essential design step to estimate the chip area prior to the optimized
placement of digital blocks and their interconnections. Since VLSI
floorplanning is an NP-hard problem, many optimization techniques
were adopted in the literature. In this work, a music-inspired
Harmony Search (HS) algorithm is used for the fixed die outline
constrained floorplanning, with the aim of reducing the total chip
area. HS draws inspiration from the musical improvisation process of
searching for a perfect state of harmony. Initially, B*-tree is used to
generate the primary floorplan for the given rectangular hard
modules and then HS algorithm is applied to obtain an optimal
solution for the efficient floorplan. The experimental results of the
HS algorithm are obtained for the MCNC benchmark circuits.
Abstract: This paper reviews the model-based qualitative and
quantitative Operations Management research in the context of
Construction Supply Chain Management (CSCM). Construction
industry has been traditionally blamed for low productivity, cost and
time overruns, waste, high fragmentation and adversarial
relationships. The construction industry has been slower than other
industries to employ the Supply Chain Management (SCM) concept
and develop models that support the decision-making and planning.
However the last decade there is a distinct shift from a project-based
to a supply-based approach of construction management. CSCM
comes up as a new promising management tool of construction
operations and improves the performance of construction projects in
terms of cost, time and quality. Modeling the Construction Supply
Chain (CSC) offers the means to reap the benefits of SCM, make
informed decisions and gain competitive advantage. Different
modeling approaches and methodologies have been applied in the
multi-disciplinary and heterogeneous research field of CSCM. The
literature review reveals that a considerable percentage of the CSC
modeling research accommodates conceptual or process models
which present general management frameworks and do not relate to
acknowledged soft Operations Research methods. We particularly
focus on the model-based quantitative research and categorize the
CSCM models depending on their scope, objectives, modeling
approach, solution methods and software used. Although over the last
few years there has been clearly an increase of research papers on
quantitative CSC models, we identify that the relevant literature is
very fragmented with limited applications of simulation,
mathematical programming and simulation-based optimization. Most
applications are project-specific or study only parts of the supply
system. Thus, some complex interdependencies within construction
are neglected and the implementation of the integrated supply chain
management is hindered. We conclude this paper by giving future
research directions and emphasizing the need to develop optimization
models for integrated CSCM. We stress that CSC modeling needs a
multi-dimensional, system-wide and long-term perspective. Finally,
prior applications of SCM to other industries have to be taken into
account in order to model CSCs, but not without translating the
generic concepts to the context of construction industry.
Abstract: The purpose of the study was to find out the effects of
Aquatic and Land plyometric training on selected physical variables
in intercollegiate male handball players. To achieve this purpose of
the study, forty five handball players of Sardar Vallabhbhai National
Institute of Technology, Surat, Gujarat were selected as players at
random and their age ranged between 18 to 21 years. The selected
players were divided into three equal groups of fifteen players each.
Group I underwent Aquatic plyometric training, Group II underwent
Land plyometric training and Group III Control group for three days
per week for twelve weeks. Control Group did not participate in any
special training programme apart from their regular activities as per
their curriculum. The following physical fitness variables namely
speed; leg explosive power and agility were selected as dependent
variables. All the players of three groups were tested on selected
dependent variables prior to and immediately after the training
programme. The analysis of covariance was used to analyze the
significant difference, if any among the groups. Since, three groups
were compared, whenever the obtained ‘F’ ratio for adjusted posttest
was found to be significant, the Scheffe’s test to find out the paired
mean differences, if any. The 0.05 level of confidence was fixed as
the level of significance to test the ‘F’ ratio obtained by the analysis
of covariance, which was considered as an appropriate. The result of
the study indicates due to Aquatic and Land plyometric training on
speed, explosive power, and agility has been improved significantly.
Abstract: Exploration and exploitation capabilities are both
important within Operations as means for improvement when
managed separately, and for establishing dynamic improvement
capabilities when combined in balance. However, it is unclear what
exploration and exploitation capabilities imply in improvement and
development work within an Operations context. So, in order to
better understand how to develop exploration and exploitation
capabilities within Operations, the main characteristics of these
constructs needs to be identified and further understood. Thus, the
objective of this research is to increase the understanding about
exploitation and exploration characteristics, to concretize what they
translates to within the context of improvement and development
work in an Operations unit, and to identify practical challenges. A
literature review and a case study are presented. In the literature
review, different interpretations of exploration and exploitation are
portrayed, key characteristics have been identified, and a deepened
understanding of exploration and exploitation characteristics is
described. The case in the study is an Operations unit, and the aim is
to explore to what extent and in what ways exploration and
exploitation activities are part of the improvement structures and
processes. The contribution includes an identification of key
characteristics of exploitation and exploration, as well as an
interpretation of the constructs. Further, some practical challenges are
identified. For instance, exploration activities tend to be given low
priority, both in daily work as in the manufacturing strategy. Also,
the overall understanding about the concepts of exploitation and
exploration (or any similar aspect of dynamic improvement
capabilities) is very low.
Abstract: Total Quality Management (TQM) is a managerial
approach that improves the competitiveness of the industry,
meanwhile Information technology (IT) was introduced with TQM
for handling the technical issues which is supported by quality
experts for fulfilling the customers’ requirement. Present paper aims
to utilise AHP (Analytic Hierarchy Process) methodology to
priorities and rank the hierarchy levels of TQM enablers and IT
resource together for its successful implementation in the Information
and Communication Technology (ICT) industry. A total of 17 TQM
enablers (nine) and IT resources (eight) were identified and
partitioned into 3 categories and were prioritised by AHP approach.
The finding indicates that the 17 sub-criteria can be grouped into
three main categories namely organizing, tools and techniques, and
culture and people. Further, out of 17 sub-criteria, three sub-criteria:
top management commitment and support, total employee
involvement, and continuous improvement got highest priority
whereas three sub-criteria such as structural equation modelling,
culture change, and customer satisfaction got lowest priority. The
result suggests a hierarchy model for ICT industry to prioritise the
enablers and resources as well as to improve the TQM and IT
performance in the ICT industry. This paper has some managerial
implication which suggests the managers of ICT industry to
implement TQM and IT together in their organizations to get
maximum benefits and how to utilize available resources. At the end,
conclusions, limitation, future scope of the study are presented.
Abstract: To mitigate the urban heat island effect has become a
global issue when we are faced with the challenge of climate change.
Through literature review, plant photosynthesis can reduce the carbon
dioxide and mitigate the urban heat island effect to a degree. Because
there are not enough open space and parks, green roof has become an
important policy in Taiwan.
We selected elementary school buildings in northern New Taipei
City as research subjects since elementary schools are asked with
priority to build green roof and important educational place to promote
green roof concept. Testo175-H1 recording device was used to record
the temperature and humidity differences between roof surface and
interior space below roof with and without green roof in the long-term.
We also use questionnaires to investigate the awareness of comfort
level of green roof and sensation of teachers and students of the
elementary schools.
The results indicated that the temperature of roof without greening
was higher than that with greening by about 2°C. But sometimes
during noontime, the temperature of green roof was higher than that of
non-green roof probably because of the character of the accumulation
and dissipation of heat of greening. The temperature of the interior
space below green roof was normally lower than that without green
roof by about 1°C, showing that green roof could lower the
temperature. The humidity of the green roof was higher than the one
without greening also indicated that green roof retained water better.
Teachers liked to combine green roof concept in the curriculum,
and students wished all classes can take turns to maintain the green
roof. Teachers and students whose school had integrated green roof
concept in the curriculum were more willing to participate in the
maintenance work of green roof. Teachers and students who may have
access to and touch the green roof can be more aware of the green roof
benefit. We suggest architects to increase the accessibility and
visibility of green roof, such as use it as a part of the activity space.
This idea can be a reference to the green roof curriculum design.
Abstract: The problems arising from unbalanced data sets
generally appear in real world applications. Due to unequal class
distribution, many researchers have found that the performance of
existing classifiers tends to be biased towards the majority class. The
k-nearest neighbors’ nonparametric discriminant analysis is a method
that was proposed for classifying unbalanced classes with good
performance. In this study, the methods of discriminant analysis are
of interest in investigating misclassification error rates for classimbalanced
data of three diabetes risk groups. The purpose of this
study was to compare the classification performance between
parametric discriminant analysis and nonparametric discriminant
analysis in a three-class classification of class-imbalanced data of
diabetes risk groups. Data from a project maintaining healthy
conditions for 599 employees of a government hospital in Bangkok
were obtained for the classification problem. The employees were
divided into three diabetes risk groups: non-risk (90%), risk (5%),
and diabetic (5%). The original data including the variables of
diabetes risk group, age, gender, blood glucose, and BMI were
analyzed and bootstrapped for 50 and 100 samples, 599 observations
per sample, for additional estimation of the misclassification error
rate. Each data set was explored for the departure of multivariate
normality and the equality of covariance matrices of the three risk
groups. Both the original data and the bootstrap samples showed nonnormality
and unequal covariance matrices. The parametric linear
discriminant function, quadratic discriminant function, and the
nonparametric k-nearest neighbors’ discriminant function were
performed over 50 and 100 bootstrap samples and applied to the
original data. Searching the optimal classification rule, the choices of
prior probabilities were set up for both equal proportions (0.33: 0.33:
0.33) and unequal proportions of (0.90:0.05:0.05), (0.80: 0.10: 0.10)
and (0.70, 0.15, 0.15). The results from 50 and 100 bootstrap samples
indicated that the k-nearest neighbors approach when k=3 or k=4 and
the defined prior probabilities of non-risk: risk: diabetic as 0.90:
0.05:0.05 or 0.80:0.10:0.10 gave the smallest error rate of
misclassification. The k-nearest neighbors approach would be
suggested for classifying a three-class-imbalanced data of diabetes
risk groups.
Abstract: Microscopic simulation tool kits allow for
consideration of the two processes of railway operations and the
previous timetable production. Block occupation conflicts on both
process levels are often solved by using defined train priorities. These
conflict resolutions (dispatching decisions) generate reactionary
delays to the involved trains. The sum of reactionary delays is
commonly used to evaluate the quality of railway operations, which
describes the timetable robustness. It is either compared to an
acceptable train performance or the delays are appraised
economically by linear monetary functions. It is impossible to
adequately evaluate dispatching decisions without a well-founded
objective function. This paper presents a new approach for the
evaluation of dispatching decisions. The approach uses mode choice
models and considers the behaviour of the end-customers. These
models evaluate the reactionary delays in more detail and consider
other competing modes of transport. The new approach pursues the
coupling of a microscopic model of railway operations with the
macroscopic choice mode model. At first, it will be implemented for
railway operations process but it can also be used for timetable
production. The evaluation considers the possibility for the customer
to interchange to other transport modes. The new approach starts to
look at rail and road, but it can also be extended to air travel. The
result of mode choice models is the modal split. The reactions by the
end-customers have an impact on the revenue of the train operating
companies. Different purposes of travel have different payment
reserves and tolerances towards late running. Aside from changes to
revenues, longer journey times can also generate additional costs.
The costs are either time- or track-specific and arise from required
changes to rolling stock or train crew cycles. Only the variable values
are summarised in the contribution margin, which is the base for the
monetary evaluation of delays. The contribution margin is calculated
for different possible solutions to the same conflict. The conflict
resolution is optimised until the monetary loss becomes minimal. The
iterative process therefore determines an optimum conflict resolution
by monitoring the change to the contribution margin. Furthermore, a
monetary value of each dispatching decision can also be derived.
Abstract: Association rule mining is one of the most important fields of data mining and knowledge discovery. In this paper, we propose an efficient multiple support frequent pattern growth algorithm which we called “MSFP-growth” that enhancing the FPgrowth algorithm by making infrequent child node pruning step with multiple minimum support using maximum constrains. The algorithm is implemented, and it is compared with other common algorithms: Apriori-multiple minimum supports using maximum constraints and FP-growth. The experimental results show that the rule mining from the proposed algorithm are interesting and our algorithm achieved better performance than other algorithms without scarifying the accuracy.
Abstract: In this paper static scheme of under-frequency based load shedding is considered for chemical and petrochemical industries with islanded distribution networks relying heavily on the primary commodity to ensure minimum production loss, plant downtime or critical equipment shutdown. A simplistic methodology is proposed for in-house implementation of this scheme using underfrequency relays and a step by step guide is provided including the techniques to calculate maximum percentage overloads, frequency decay rates, time based frequency response and frequency based time response of the system. Case study of FFL electrical system is utilized, presenting the actual system parameters and employed load shedding settings following the similar series of steps. The arbitrary settings are then verified for worst overload conditions (loss of a generation source in this case) and comprehensive system response is then investigated.
Abstract: The paper shows the necessity of farm diversification
in accordance with the current trends in agricultural sector of
Georgia. The possibilities for the diversification and the
corresponding economic policy are suggested.
The causes that hinder diversification of farms are revealed,
possibilities of diversification are identified and the ability of
increasing employment through diversification is proved. Index of
harvest diversification is calculated based on the areas used for
cereals and legumes, potatoes and vegetables and other food crops.
Crop and livestock production indexes are analyzed; correlation
between crop capacity index and value added per worker and per
hectare is studied.
Based on the research farm diversification strategies and priorities
of corresponding economic policy are presented. Based on the
conclusions relevant recommendations are suggested.
Abstract: The purposes of this study are 1) to study the effects
of participatory error correction process and 2) to find out the
students’ satisfaction of such error correction process. This study is a
Quasi Experimental Research with single group, in which data is
collected 5 times preceding and following 4 experimental studies of
participatory error correction process including providing coded
indirect corrective feedback in the students’ texts with error treatment
activities. Samples include 52 2nd year English Major students,
Faculty of Humanities and Social Sciences, Suan Sunandha Rajabhat
University. Tool for experimental study includes the lesson plan of
the course; Reading and Writing English for Academic Purposes II,
and tools for data collection include 5 writing tests of short texts and
a questionnaire. Based on formative evaluation of the students’
writing ability prior to and after each of the 4 experiments, the
research findings disclose the students’ higher scores with statistical
difference at 0.00. Moreover, in terms of the effect size of such
process, it is found that for mean of the students’ scores prior to and
after the 4 experiments; d equals 0.6801, 0.5093, 0.5071, and 0.5296
respectively. It can be concluded that participatory error correction
process enables all of the students to learn equally well and there is
improvement in their ability to write short texts. Finally the students’
overall satisfaction of the participatory error correction process is in
high level (Mean = 4.39, S.D. = 0.76).
Abstract: The biodegradable family of polymers
polyhydroxyalkanoates is an interesting substitute for convectional
fossil-based plastics. However, the manufacturing and environmental
impacts associated with their production via intracellular bacterial
fermentation are strongly dependent on the raw material used and on
energy consumption during the extraction process, limiting their
potential for commercialization. Industrial wastewater is studied in
this paper as a promising alternative feedstock for waste valorization.
Based on results from laboratory and pilot-scale experiments, a
conceptual process design, techno-economic analysis and life cycle
assessment are developed for the large-scale production of the most
common type of polyhydroxyalkanoate, polyhydroxbutyrate.
Intracellular polyhydroxybutyrate is obtained via fermentation of
microbial community present in industrial wastewater and the
downstream processing is based on chemical digestion with
surfactant and hypochlorite. The economic potential and
environmental performance results help identifying bottlenecks and
best opportunities to scale-up the process prior to industrial
implementation. The outcome of this research indicates that the
fermentation of wastewater towards PHB presents advantages
compared to traditional PHAs production from sugars because the
null environmental burdens and financial costs of the raw material in
the bioplastic production process. Nevertheless, process optimization
is still required to compete with the petrochemicals counterparts.