Abstract: The present experimental study insights the decontamination of instantaneous velocity fluctuations captured by Acoustic Doppler Velocimeter (ADV) in gravel-bed streams to ascertain near-bed turbulence for low Reynolds number. The interference between incidental and reflected pulses produce spikes in the ADV data especially in the near-bed flow zone and therefore filtering the data are very essential. Nortek’s Vectrino four-receiver ADV probe was used to capture the instantaneous three-dimensional velocity fluctuations over a non-cohesive bed. A spike removal algorithm based on the acceleration threshold method was applied to note the bed roughness and its influence on velocity fluctuations and velocity power spectra in the carrier fluid. The velocity power spectra of despiked signals with a best combination of velocity threshold (VT) and acceleration threshold (AT) are proposed which ascertained velocity power spectra a satisfactory fit with the Kolmogorov “–5/3 scaling-law” in the inertial sub-range. Also, velocity distributions below the roughness crest level fairly follows a third-degree polynomial series.
Abstract: This paper explores efficient ways to implement various
media-updating features like news aggregation, video conversion,
and bulk email handling. All of these jobs share the property
that they are periodic in nature, and they all benefit from being
handled in a distributed fashion. The data for these jobs also often
comes from a social or collaborative source. We isolate the class of
periodic, one round map reduce jobs as a useful setting to describe
and handle media updating tasks. As such tasks are simpler than
general map reduce jobs, programming them in a general map
reduce platform could easily become tedious. This paper presents
a MediaUpdater module of the Yioop Open Source Search Engine
Web Portal designed to handle such jobs via an extension of a
PHP class. We describe how to implement various media-updating
tasks in our system as well as experiments carried out using these
implementations on an Amazon Web Services cluster.
Abstract: With digitalization increasingly changing the rules of competition, firms face the need to adapt and assimilate digital technologies in order to remain competitive. Firms can choose from various possibilities to integrate digital technologies including the option to embed digital technologies aiming to innovate products or to develop digital products. However, the question of which specific factors influence a firm’s decision to pursue digital product innovation remains unanswered in research. By adopting the Technology-Organization-Environment (TOE)-framework we have designed a qualitative exploratory study including eleven German practitioners to investigate relevant contingency factors. Our results indicate that the most critical factors for a company’s decision to pursue digital product innovation can be found in the technological and environmental dimensions, namely customers, competitive pressure, technological change, as well as digitalization fit.
Abstract: One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed with homogeneous ensemble classifier using bagging and heterogeneous ensemble classifier using arcing and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of standard datasets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase, and combining phase. A wide range of comparative experiments is conducted for standard datasets of intrusion detection. The performance of the proposed homogeneous and heterogeneous ensemble classifiers are compared to the performance of other standard homogeneous and heterogeneous ensemble methods. The standard homogeneous ensemble methods include Error correcting output codes, Dagging and heterogeneous ensemble methods include majority voting, stacking. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and the proposed bagged RBF and SVM performs significantly better than ECOC and Dagging and the proposed hybrid RBF-SVM performs significantly better than voting and stacking. Also heterogeneous models exhibit better results than homogeneous models for standard datasets of intrusion detection.
Abstract: Patient satisfaction represents a crucial aspect in the evaluation of health care services. Preoperative teaching provides the patient with pertinent information concerning the surgical process and the intended surgical procedure as well as anticipated patient behavior (anxiety, fear), expected sensation, and the probable outcomes. Although patient education is part of Accreditation protocols, it is not uniform at most places. The aim of this study was to try to assess the benefit of preoperative patient education on selected post-operative outcome parameters; mainly, post-operative pain scores, requirement of additional analgesia, return to activity of daily living and overall patient satisfaction, and try to standardize few education protocols. Dependent variables were measured before and after the treatment on a study population of 302 volunteers. Educational intervention was provided by the Investigator in the preoperative period to the study group through personal counseling. An information booklet contained detailed information was also provided. Statistical Analysis was done using Chi square test, Mann Whitney u test and Fischer Exact Test on a total of 302 subjects. P value
Abstract: Social entrepreneurship is a new and exciting topic
that holds a great promise in helping alleviate the social problems of
the world. As a new subject, the meaning of the term is too broad and
this is counterproductive in trying to build understanding around the
concept. The purpose of this study is to identify and compare the
elements of social entrepreneurship as defined by seven international
organizations leading social entrepreneurship projects: Ashoka
Foundation, Skoll Foundation, Schwab Foundation and Yunus
Center; as well as from three other institutions fostering social
entrepreneurship: Global Social Benefit Institute, BRAC University,
and Socialab. The study used document analysis from Skoll
Foundation, Schwab Foundation, Yunus Center and Ashoka
Foundation; and open ended interview to experts from the Global
Social Benefit Institute at Santa Clara University in United States,
BRAC University from Bangladesh, and Socialab from Argentina.
The study identified three clearly differentiated schools of thought,
based on their views on revenue, scalability, replicability and
geographic location. While this study is by no means exhaustive, it
provides an indication of the patterns of ideas fostered by important
players in the field. By clearly identifying the similarities and
differences in the concept of social entrepreneurship, research and
practitioners are better equipped to build on the subject, and to
promote more adequate and accurate social policies to foster the
development of social entrepreneurship.
Abstract: Today, insurers may use the yield curve as an indicator
evaluation of the profit or the performance of their portfolios;
therefore, they modeled it by one class of model that has the ability
to fit and forecast the future term structure of interest rates. This class
of model is the Nelson-Siegel-Svensson model. Unfortunately, many
authors have reported a lot of difficulties when they want to calibrate
the model because the optimization problem is not convex and has
multiple local optima. In this context, we implement a hybrid Particle
Swarm optimization and Nelder Mead algorithm in order to minimize
by least squares method, the difference between the zero-coupon
curve and the NSS curve.
Abstract: The technological paradigm of the disaster
management field, especially in the case of governmental
intervention strategies, is generally based on rapid and flexible
accommodation solutions. From various technical solution patterns
used to address the immediate housing needs of disaster victims, the
adaptive re-use of existing buildings can be considered to be both
low-cost and practical. However, there is a scarcity of analytical
methods to screen, select and adapt buildings to help decision makers
in cases of emergency. Following an extensive literature review, this
paper aims to highlight key points and problem areas associated with
the adaptive re-use of buildings within the disaster management
context. In other disciplines such as real estate management, the
adaptive re-use potential (ARP) of existing buildings is typically
based on the prioritization of a set of technical and non-technical
criteria which are then weighted to arrive at an economically viable
investment decision. After a disaster, however, the assessment of the
ARP of buildings requires consideration of different/additional layers
of analysis which stem from general disaster management principles
and the peculiarities of different types of disasters, as well as of their
victims. In this paper, a discussion of the development of an adaptive
re-use potential (ARP) assessment model is presented. It is thought
that governmental and non-governmental decision makers who are
required to take quick decisions to accommodate displaced masses
following disasters are likely to benefit from the implementation of
such a model.
Abstract: The idea of cropping-system is a method used by
farmers. It is an environmentally-friendly method, protecting the
natural resources (soil, water, air, nutritive substances) and increase
the production at the same time, taking into account some crop
particularities. The combination of this powerful method with the
concepts of genetic algorithms results into a possibility of generating
sequences of crops in order to form a rotation. The usage of this type
of algorithms has been efficient in solving problems related to
optimization and their polynomial complexity allows them to be used
at solving more difficult and various problems. In our case, the
optimization consists in finding the most profitable rotation of
cultures. One of the expected results is to optimize the usage of the
resources, in order to minimize the costs and maximize the profit. In
order to achieve these goals, a genetic algorithm was designed. This
algorithm ensures the finding of several optimized solutions of
cropping-systems possibilities which have the highest profit and,
thus, which minimize the costs. The algorithm uses genetic-based
methods (mutation, crossover) and structures (genes, chromosomes).
A cropping-system possibility will be considered a chromosome and
a crop within the rotation is a gene within a chromosome. Results
about the efficiency of this method will be presented in a special
section. The implementation of this method would bring benefits into
the activity of the farmers by giving them hints and helping them to
use the resources efficiently.
Abstract: The aim of the paper is to investigate the effect of
corporate social responsibility (CSR) CSR on the National
Commercial Bank (NCB) in Saudi Arabia. In order to achieve this, a
case study was made of the CSR activities of this bank from the
perspective of its branch managers. The NCB was chosen as it was
one of the first Saudi banks to engage in CSR and currently has a
wide range of CSR initiatives. A qualitative research method was
used. Open-ended questionnaires were administered to eighty branch
managers of the NCB, with fifty-five usable questionnaires returned
and twenty managers were interviewed as part of the primary
research. Data from both questionnaires and interviews were
analysed using qualitative content analysis. Six themes emerged from
the questionnaire findings were used to develop the interview
questions. These themes are the following: Awareness of employees
about CSR in the NCB; CSR activities as a type of investment;
Government and media support; Increased employee loyalty in the
NCB; Prestige and profit to the NCB; and View of CSR in Islam.
This paper makes a theoretical contribution in that it investigates and
increases understanding of the effect of CSR on the NCB in Saudi
Arabia. In addition, it makes a practical contribution by making
recommendations which can support the development of CSR in the
NCB. A limitation of the paper is that it is a case study of only one
bank. It is therefore recommended that future research could be
conducted with other banks in Saudi Arabia, or indeed, with a range
of other types of firm within the financial services area in Saudi
Arabia. In this way, the same issues could be explored but with a
greater potential generalisability of findings of CSR within the Saudi
Arabian financial services industry. In addition, this paper takes a
qualitative approach and it is suggested that future research be carried
out using mixed methods, which could provide a greater depth of
analysis.
Abstract: The purpose of this study is to explore the different facets of growth among micro, small and medium-sized firms in Croatia and to analyze the differences between models designed for all micro, small and medium-sized firms and those in creative industries. Three growth prediction models were designed and tested using the growth of sales, employment and assets of the company as dependent variables. The key drivers of sales growth are: prudent use of cash, industry affiliation and higher share of intangible assets. Growth of assets depends on retained profits, internal and external sources of financing, as well as industry affiliation. Growth in employment is closely related to sources of financing, in particular, debt and it occurs less frequently than growth in sales and assets. The findings confirm the assumption that growth strategies of small and medium-sized enterprises (SMEs) in creative industries have specific differences in comparison to SMEs in general. Interestingly, only 2.2% of growing enterprises achieve growth in employment, assets and sales simultaneously.
Abstract: 3D model-based vehicle matching provides a new way
for vehicle recognition, localization and tracking. Its key is to
construct an evaluation function, also called fitness function, to
measure the degree of vehicle matching. The existing fitness functions
often poorly perform when the clutter and occlusion exist in traffic
scenarios. In this paper, we present a practical and efficient fitness
function. Unlike the existing evaluation functions, the proposed
fitness function is to study the vehicle matching problem from
both local and global perspectives, which exploits the pixel gradient
information as well as the silhouette information. In view of the
discrepancy between 3D vehicle model and real vehicle, a weighting
strategy is introduced to differently treat the fitting of the model’s
wireframes. Additionally, a normalization operation for the model’s
projection is performed to improve the accuracy of the matching.
Experimental results on real traffic videos reveal that the proposed
fitness function is efficient and robust to the cluttered background
and partial occlusion.
Abstract: This paper explores the relationships between the basic learning processes of leading trade union workers and their methods for coping with the changes in the life-courses of societies today. It will discuss the fragile discourse on lifelong learning in trade unions and the “production of self-techniques” to get in touch with the new economic forms. On the basis of an empirical project, different processes of the socialization of leading trade union workers will be analysed to discover the consequences of the lifelong learning discourse. The results show what competences they need to develop for the “wider benefits of negotiations”. The main challenge remains to make visible how deeply intertwined trade union learning and education are with development in an ongoing dynamic economic process, rather than a quick-fix injection of skills and information. There is a complex relationship existing between the three ‘partners’, work, learning and society forming. The author suggests that contemporary trade unions could be trendsetters who make their own learning agendas by drawing less on formal education and more on informal and non-formal learning contexts. This is in parallel with growing political and scientific consciousness of the need to arrive at new educational/vocational policies and practices.
Abstract: This paper presents a comprehensive survey of recent research studies to segment and classify brain MR (magnetic resonance) images in order to detect significant changes to brain ventricles. The paper also presents a general framework for detecting regions that atrophy, which can help neurologists in detecting and staging Alzheimer. Furthermore, a prototype was implemented to segment brain MR images in order to extract the region of interest (ROI) and then, a classifier was employed to differentiate between normal and abnormal brain tissues. Experimental results show that the proposed scheme can provide a reliable second opinion that neurologists can benefit from.
Abstract: This paper investigates the barriers behind the underutilisation of six sigma in Libyan manufacturing companies (LMCs). A mixed-method methodology is proposed, starting by conducting interviews to collect qualitative data followed by the development of a questionnaire to obtain quantitative data. The focus of this paper is on discussing the findings of the interview stage and how these can be used to further develop the questionnaire stage. The interview results showed that only four key barriers were highlighted as being encountered by LMCs. With a difference in terms of their significance, these factors were identified, and placed in descending order according to their importance, namely: “Lack of top management commitment”, “Lack of training”, “Lack of knowledge about six sigma”, and “Culture effect”. The findings also showed that some barriers which, were found in previous studies of six sigma implementation were not considered as barriers to LMCs but can, in fact, be considered as success factors or enablers for six sigma adoption. These factors were identified as: “sufficiency of time and financial resources”; “customers unsatisfied”; “good communication between all departments in the company”; “we are certain about its results and benefits to our company and unhappy with the current quality system”. These results suggest that LMCs face fewer barriers to adopting six sigma than many well-established global companies operating in other countries and could take advantage of these successful factors by developing and implementing a six sigma framework to improve their product quality and competitiveness.
Abstract: The basic objective of the research is to study the effect of hybrid wind energy on the cost of generated electricity considering the cost of reduction CO2 emissions. The system consists of small wind turbine(s), storage battery bank and a diesel generator (W/D/B). Using an optimization software package, different system configurations are investigated to reach optimum configuration based on the net present cost (NPC) and cost of energy (COE) as economic optimization criteria. The cost of avoided CO2 is taken into consideration. The system is intended to supply the electrical load of a small community (gathering six families) in a remote Egyptian area. The investigated system is not connected to the electricity grid and may replace an existing conventional diesel powered electric supply system to reduce fuel consumption and CO2 emissions. The simulation results showed that W/D energy system is more economic than diesel alone. The estimated COE is 0.308$/kWh and extracting the cost of avoided CO2, the COE reached 0.226 $/kWh which is an external benefit of wind turbine, as there are no pollutant emissions through operational phase.
Abstract: In this paper, we discuss a Bayesian approach to
quantile autoregressive (QAR) time series model estimation and
forecasting. Together with a combining forecasts technique, we then
predict USD to GBP currency exchange rates. Combined forecasts
contain all the information captured by the fitted QAR models
at different quantile levels and are therefore better than those
obtained from individual models. Our results show that an unequally
weighted combining method performs better than other forecasting
methodology. We found that a median AR model can perform well in
point forecasting when the predictive density functions are symmetric.
However, in practice, using the median AR model alone may involve
the loss of information about the data captured by other QAR models.
We recommend that combined forecasts should be used whenever
possible.
Abstract: The aim of this study is to explore the need of small and medium-sized businesses in tourism and hospitality industry to adopt technology and enhance their degree of digitalization, along with the main benefits enjoyed by technology and the main challenges that hinder its adoption. Within a hermeneutic phenomenological perspective, semi-structured interviews were conducted with three hotel owners and the focus was to identify the main reasons of adoption of technology, enablers and barriers. The findings were grouped with the goal of identifying typology of business practices in using and adopting technology.
Abstract: The shared goal of social entrepreneurship, corporate social responsibility and social innovation is the advancement of society. The business model of social enterprises is characterized by unique strategies based on the competencies of the entrepreneurs, and is not aimed primarily at the maximization of profits, but rather at carrying out goals for the benefit of society. Corporate social responsibility refers to the active behavior of a company, by which it can create new solutions to meet the needs of society, either on its own or in cooperation with other social stakeholders. The objectives of this article are to define concepts, describe and integrate relevant theoretical models, develop a model and introduce some examples of international practice that can inspire initiatives for social development.
Abstract: Reinforced concrete bridges designed by code are intended to achieve target reliability levels adequate for the geographical environment where the code is applicable. Several methods can be used to estimate such reliability levels. Many of them require the establishment of an explicit limit state function (LSF). When such LSF is not available as a close-form expression, the simulation techniques are often employed. The simulation methods are computing intensive and time consuming. Note that if the reliability of real bridges designed by code is of interest, numerical schemes, the finite element method (FEM) or computational mechanics could be required. In these cases, it can be quite difficult (or impossible) to establish a close-form of the LSF, and the simulation techniques may be necessary to compute reliability levels. To overcome the need for a large number of simulations when no explicit LSF is available, the point estimate method (PEM) could be considered as an alternative. It has the advantage that only the probabilistic moments of the random variables are required. However, in the PEM, fitting of the resulting moments of the LSF to a probability density function (PDF) is needed. In the present study, a very simple alternative which allows the assessment of the reliability levels when no explicit LSF is available and without the need of extensive simulations is employed. The alternative includes the use of the PEM, and its applicability is shown by assessing reliability levels of reinforced concrete bridges in Mexico when a numerical scheme is required. Comparisons with results by using the Monte Carlo simulation (MCS) technique are included. To overcome the problem of approximating the probabilistic moments from the PEM to a PDF, a well-known distribution is employed. The approach mixes the PEM and other classic reliability method (first order reliability method, FORM). The results in the present study are in good agreement whit those computed with the MCS. Therefore, the alternative of mixing the reliability methods is a very valuable option to determine reliability levels when no close form of the LSF is available, or if numerical schemes, the FEM or computational mechanics are employed.