Abstract: In current global economics the application of Business Continuity Management is the prerequisite for sustainable competitive advantage in an organization. Business Continuity Management is a managerial which identifies the potential impact of losses in an organization. The aim of this paper is to identify and critically evaluate the relative advantages and disadvantages of deploying Business Continuity Management in an organization on the basis of seven criteria. The strongest advantage of Business Continuity Management is in its capacity to identify a crisis situation and help the organization to flexibly and also to keep the critical knowledge within the organization. By contrast the main disadvantage is that establishing Business Continuity Management in an organization is time-consuming and its implementation as an integral part of the organizational culture present significant difficulties.
Abstract: Digital broadcasting has been an area of active
research, development, innovation and business models development
in recent years. This paper presents a survey on the characteristics of
the digital terrestrial television broadcasting (DTTB) standards, and
implementation status of DTTB worldwide showing the standards
adopted. It is clear that only the developed countries and some in the
developing ones shall be able to beat the ITU set analogue to digital
broadcasting migration deadline because of the challenges that these
countries faces in digitizing their terrestrial broadcasting. The
challenges to keep on track the DTTB migration plan are also
discussed in this paper. They include financial, technology gap,
policies alignment with DTTB technology, etc. The reported
performance comparisons for the different standards are also
presented. The interesting part is that the results for many
comparative studies depends to a large extent on the objective behind
such studies, hence counter claims are common.
Abstract: Attempts were made to identify anuran glial cells. They were found as nervous tissue resident. Having stage dependent morphotype changes, whereby, appeared as an ovoid to oval in resting state and amoeboid mrophotypes in activated state, stained fairly with methylene blue and take up Pelikane blue 10% aqueous solution, as well as having the ability to phagocytize heat killed Staphylococcus aureus. They were delineated from the migrating peripheral monocytes by morphotypic and morphometeric differences. Such criteria were consistence with glial cells. Thus, the anuran glial cells are being identified in the frog Rana ridibunda Pallas 1771 and this animal can be of use as a simple model for the immunobiology of glial cells.
Abstract: As the air traffic increases at a hub airport, some
flights cannot land or depart at their preferred target time. This event
happens because the airport runways become occupied to near their
capacity. It results in extra costs for both passengers and airlines
because of the loss of connecting flights or more waiting, more fuel
consumption, rescheduling crew members, etc. Hence, devising an
appropriate scheduling method that determines a suitable runway and
time for each flight in order to efficiently use the hub capacity and
minimize the related costs is of great importance. In this paper, we
present a mixed-integer zero-one model for scheduling a set of mixed
landing and departing flights (despite of most previous studies
considered only landings). According to the fact that the flight cost is
strongly affected by the level of airline, we consider different airline
categories in our model. This model presents a single objective
minimizing the total sum of three terms, namely 1) the weighted
deviation from targets, 2) the scheduled time of the last flight (i.e.,
makespan), and 3) the unbalancing the workload on runways. We
solve 10 simulated instances of different sizes up to 30 flights and 4
runways. Optimal solutions are obtained in a reasonable time, which
are satisfactory in comparison with the traditional rule, namely First-
Come-First-Serve (FCFS) that is far apart from optimality in most
cases.
Abstract: We consider the methods of construction simple
polygons for a set S of n points and applying them for searching the
minimal area polygon. In this paper we propose the approximate
algorithm, which generates the simple polygonalizations of a fixed
set of points and finds the minimal area polygon, in O (n3) time and
using O(n2) memory.
Abstract: Because of the low maintenance and robustness induction motors have many applications in the industries. The speed control of induction motor is more important to achieve maximum torque and efficiency. Various speed control techniques like, Direct Torque Control, Sensorless Vector Control and Field Oriented Control are discussed in this paper. Soft computing technique – Fuzzy logic is applied in this paper for the speed control of induction motor to achieve maximum torque with minimum loss. The fuzzy logic controller is implemented using the Field Oriented Control technique as it provides better control of motor torque with high dynamic performance. The motor model is designed and membership functions are chosen according to the parameters of the motor model. The simulated design is tested using various tool boxes in MATLAB. The result concludes that the efficiency and reliability of the proposed speed controller is good.
Abstract: Copolymerization of ethylene with 1-hexene was
carried out using two ansa-fluorenyl titanium derivative complexes.
The substituent effect on the catalytic activity, monomer reactivity
ratio and polymer property was investigated. It was found that the
presence of t-Bu groups on fluorenyl ring exhibited remarkable
catalytic activity and produced polymer with high molecular weight.
However, these catalysts produce polymer with narrow molecular
weight distribution, indicating the characteristic of single-site
metallocene catalyst. Based on 13C NMR, we can observe that
monomer reactivity ratio was affected by catalyst structure. The rH
values of complex 2 were lower than that of complex 1 which might
be result from the higher steric hindrance leading to a reduction of 1-
hexene insertion step.
Abstract: Within the new world order, the term “crisis" is nowadays familiar to companies. Organizations are experiencing conditions which are surprising, uncertain, often adverse and usually unstable. The companies, who grasp the importance of transformation within the information age, have felt the need to develop modern methods to achieve the ability to thrive despite severe shocks. Through strategically managing human resource and developing appropriate elements of human resource system, companies can be assured for resolving the crisis. In this paper the role of HR system on resolving crisis has been evaluated. To help accomplish this, an insight on previous strategic HRM literature and an introduction to the elements and relationship within HR systems has been presented. It also reviews different attitude around resilience in literature. It continues by reviewing three elements central to developing an organization-s capacity for crisis resolving and it will demonstrate how designing proper elements of HR system can lead the organizations to possess the ability for passing through crisis. Finally it will evaluate an Iranian Insurance organization in case of one of the three central elements (specific cognitive ability) and observe how successful they were on developing an effective HR system to be ready for facing crisis.
Abstract: Bleeding in the digestive duct is an important diagnostic parameter for patients. Blood in the endoscopic image can be determined by investigating the color tone of blood due to the degree of oxygenation, under- or over- illumination, food debris and secretions, etc. However, we found that how to pre-process raw images obtained from the capsule detectors was very important. We applied various image process methods suitable for the capsule endoscopic image in order to remove noises and unbalanced sensitivities for the image pixels. The results showed that much improvement was achieved by additional pre-processing techniques on the algorithm of determining bleeding areas.
Abstract: This paper deals with the combination of OSGi and
cloud computing. Both technologies are mainly placed in the field of
distributed computing. Therefore, it is discussed how different
approaches from different institutions work. In addition, the
approaches are compared to each other.
Abstract: In this longitudinal study, we examined the moderating role of personality in the relationship between communication behaviors and long-term dyadic adjustment. A sample of 82 couples completed the NEO Five-Factor Inventory and the Dyadic Adjustment Scale. These couples were also videotaped during a 15-minute problem-solving discussion. Approximately 2.5 years later, these couples completed again the Dyadic Adjustment Scale. Results show that personality of both men and women moderates the relationship between communication behaviors of the partner and long-term dyadic adjustment of the individual. Women-s openness and men-s extraversion moderate the relationship between some communication behaviors and long-term dyadic adjustment
Abstract: Time series forecasting is an important and widely
popular topic in the research of system modeling. This paper
describes how to use the hybrid PSO-RLSE neuro-fuzzy learning
approach to the problem of time series forecasting. The PSO
algorithm is used to update the premise parameters of the
proposed prediction system, and the RLSE is used to update the
consequence parameters. Thanks to the hybrid learning (HL)
approach for the neuro-fuzzy system, the prediction performance
is excellent and the speed of learning convergence is much faster
than other compared approaches. In the experiments, we use the
well-known Mackey-Glass chaos time series. According to the
experimental results, the prediction performance and accuracy in
time series forecasting by the proposed approach is much better
than other compared approaches, as shown in Table IV. Excellent
prediction performance by the proposed approach has been
observed.
Abstract: Internet is without any doubt the fastest and effective mean of communication making it possible to reach a great number of people in the world. It draws its base from exchange points. Indeed exchange points are used to inter-connect various Internet suppliers and operators in order to allow them to exchange traffic and it is with these interconnections that Internet made its great strides. They thus make it possible to limit the traffic delivered via the operators of transits. This limitation allows a significant improvement of the quality of service, a reduction in the latency time just as a reduction of the cost of connection for the final subscriber. Through this article we will show how the installation of an IXP allows an improvement and a diversification of the services just as a reduction of the Internet connection costs.
Abstract: This paper presents the methodology from machine
learning approaches for short-term rain forecasting system. Decision
Tree, Artificial Neural Network (ANN), and Support Vector Machine
(SVM) were applied to develop classification and prediction models
for rainfall forecasts. The goals of this presentation are to
demonstrate (1) how feature selection can be used to identify the
relationships between rainfall occurrences and other weather
conditions and (2) what models can be developed and deployed for
predicting the accurate rainfall estimates to support the decisions to
launch the cloud seeding operations in the northeastern part of
Thailand. Datasets collected during 2004-2006 from the
Chalermprakiat Royal Rain Making Research Center at Hua Hin,
Prachuap Khiri khan, the Chalermprakiat Royal Rain Making
Research Center at Pimai, Nakhon Ratchasima and Thai
Meteorological Department (TMD). A total of 179 records with 57
features was merged and matched by unique date. There are three
main parts in this work. Firstly, a decision tree induction algorithm
(C4.5) was used to classify the rain status into either rain or no-rain.
The overall accuracy of classification tree achieves 94.41% with the
five-fold cross validation. The C4.5 algorithm was also used to
classify the rain amount into three classes as no-rain (0-0.1 mm.),
few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall
accuracy of classification tree achieves 62.57%. Secondly, an ANN
was applied to predict the rainfall amount and the root mean square
error (RMSE) were used to measure the training and testing errors of
the ANN. It is found that the ANN yields a lower RMSE at 0.171 for
daily rainfall estimates, when compared to next-day and next-2-day
estimation. Thirdly, the ANN and SVM techniques were also used to
classify the rain amount into three classes as no-rain, few-rain, and
moderate-rain as above. The results achieved in 68.15% and 69.10%
of overall accuracy of same-day prediction for the ANN and SVM
models, respectively. The obtained results illustrated the comparison
of the predictive power of different methods for rainfall estimation.
Abstract: The paper represents a reflection on how to select proper indicators to assess the progress of regional contexts towards a knowledge-based society. Taking the first research methodologies elaborated at an international level (World Bank, OECD, etc.) as a reference point, this work intends to identify a set of indicators of the knowledge economy suitable to adequately understand in which manner and to which extent the territorial development dynamics are correlated with the knowledge-base of the considered local society. After a critical survey of the variables utilized within other approaches adopted by international or national organizations, this paper seeks to elaborate a framework of variables, named Regional Knowledge Economy Indicators (ReKEI), necessary to describe the knowledge-based relations of subnational socio-economic contexts. The realization of this framework has a double purpose: an analytical one consisting in highlighting the regional differences in the governance of knowledge based processes, and an operative one consisting in providing some reference parameters for contributing to increasing the effectiveness of those economic policies aiming at enlarging the knowledge bases of local societies.
Abstract: The main objective of this study was to remove and recover Ni, Cu and Fe from a mixed metal system using sodium hypophosphite as a reducing agent and nickel powder as seeding material. The metal systems studied consisted of Ni-Cu, Ni-Fe and Ni-Cu-Fe solutions. A 5 L batch reactor was used to conduct experiments where 100 mg/l of each respective metal was used. It was found that the metals were reduced to their elemental form with removal efficiencies of over 80%. The removal efficiency decreased in the order Fe>Ni>Cu. The metal powder obtained contained between 97-99% Ni and was almost spherical and porous. Size enlargement by aggregation was the dominant particulate process.
Abstract: Safer driver behavior promoting is the main goal of this paper. It is a fact that drivers behavior is relatively safer when being monitored. Thus, in this paper, we propose a monitoring system to report specific driving event as well as the potentially aggressive events for estimation of the driving performance. Our driving monitoring system is composed of two parts. The first part is the in-vehicle embedded system which is composed of a GPS receiver, a two-axis accelerometer, radar sensor, OBD interface, and GPRS modem. The design considerations that led to this architecture is described in this paper. The second part is a web server where an adaptive hierarchical fuzzy system is proposed to classify the driving performance based on the data that is sent by the in-vehicle embedded system and the data that is provided by the geographical information system (GIS). Our system is robust, inexpensive and small enough to fit inside a vehicle without distracting the driver.
Abstract: Static analysis of source code is used for auditing web
applications to detect the vulnerabilities. In this paper, we propose a
new algorithm to analyze the PHP source code for detecting LFI and
RFI potential vulnerabilities. In our approach, we first define some
patterns for finding some functions which have potential to be abused
because of unhandled user inputs. More precisely, we use regular
expression as a fast and simple method to define some patterns for
detection of vulnerabilities. As inclusion functions could be also used
in a safe way, there could occur many false positives (FP). The first
cause of these FP-s could be that the function does not use a usersupplied
variable as an argument. So, we extract a list of usersupplied
variables to be used for detecting vulnerable lines of code.
On the other side, as vulnerability could spread among the variables
like by multi-level assignment, we also try to extract the hidden usersupplied
variables. We use the resulted list to decrease the false
positives of our method. Finally, as there exist some ways to prevent
the vulnerability of inclusion functions, we define also some patterns
to detect them and decrease our false positives.
Abstract: Responses of the dynamical systems are highly affected by the natural frequencies and it has a huge impact on design and operation of high-rise and high-speed elevators. In the present paper, the variational iteration method (VIM) is employed to investigate better understanding the dynamics of elevator cable as a single-degree-of-freedom (SDOF) swing system. Comparisons made among the results of the proposed closed-form analytical solution, the traditional numerical iterative time integration solution, and the linearized governing equations confirm the accuracy and efficiency of the proposed approach. Furthermore, based on the results of the proposed closed-form solution, the linearization errors in calculating the natural frequencies in different cases are discussed.
Abstract: In this paper, we proposed the distribution of mesh
normal vector direction as a feature descriptor of a 3D model. A
normal vector shows the entire shape of a model well. The
distribution of normal vectors was sampled in proportion to each
polygon's area so that the information on the surface with less surface
area may be less reflected on composing a feature descriptor in order
to enhance retrieval performance. At the analysis result of ANMRR,
the enhancement of approx. 12.4%~34.7% compared to the existing
method has also been indicated.