Abstract: Hybrid photovoltaic thermal (PV/T) solar system comprises a solar collector which is disposed on photovoltaic solar cells. The disadvantage of a conventional photovoltaic cell is that its performance decreases as the temperature increases. Indeed, part of the solar radiation is converted into electricity and is dissipated as heat, increasing the temperature of the photovoltaic cell with respect to the ambient temperature. The objective of this work is to study experimentally and implement a hybrid prototype to evaluate electrical and thermal performance. In this paper, an experimental study of two new configurations of hybrid collectors is exposed. The results are given and interpreted. The two configurations of absorber studied are a new combination with tubes and galvanized tank, the other is a tubes and sheet.
Abstract: Objective: The objective of this paper is to assess the
hospitals preparedness for emergency using WHO standards.
Method: This is a cross-sectional study, consisted of site visit,
questionnaire survey, 16 health facilities were included. The WHO
standard for emergency preparedness of health facilities was used to
evaluate and assess the hospitals preparedness of health facilities.
Result: 13 hospitals were responded. They scored below average
in all measure >75%), while above average score was in 7 out 9 nine
measure with a range of 8%-25%. Un acceptable below average was
noted in two measures only.
Discussion: The biggest challenge facing the hospitals in their
emergency intervention is the lack of pre-emergency and emergency
preparedness plans as well as the coordination of the hospitals
response mechanisms.
Conclusion: The studied hospitals presently are far from
international disasters preparedness protocols. That necessitates
improvements in emergency preparedness, as well as in physician
skills for injury management.
Abstract: At present, dictionary attack has been the basic tool for
recovering key passwords. In order to avoid dictionary attack, users
purposely choose another character strings as passwords. According to
statistics, about 14% of users choose keys on a keyboard (Kkey, for
short) as passwords. This paper develops a framework system to attack
the password chosen from Kkeys and analyzes its efficiency. Within
this system, we build up keyboard rules using the adjacent and parallel
relationship among Kkeys and then use these Kkey rules to generate
password databases by depth-first search method. According to the
experiment results, we find the key space of databases derived from
these Kkey rules that could be far smaller than the password databases
generated within brute-force attack, thus effectively narrowing down
the scope of attack research. Taking one general Kkey rule, the
combinations in all printable characters (94 types) with Kkey adjacent
and parallel relationship, as an example, the derived key space is about
240 smaller than those in brute-force attack. In addition, we
demonstrate the method's practicality and value by successfully
cracking the access password to UNIX and PC using the password
databases created
Abstract: In this paper, the shape design process is briefly discussed emphasizing the use of topology optimization in the conceptual design stage. The basic idea is to view feasible domains for sensitivity region concepts. In this method, the main process consists of two steps: as the design moves further inside the feasible domain using Taguchi method, and thus becoming more successful topology optimization, the sensitivity region becomes larger. In designing a double-eccentric butterfly valve, related to hydrodynamic performance and disc structure, are discussed where the use of topology optimization has proven to dramatically improve an existing design and significantly decrease the development time of a shape design. Computational Fluid Dynamics (CFD) analysis results demonstrate the validity of this approach.
Abstract: Chinese Idioms are a type of traditional Chinese idiomatic
expressions with specific meanings and stereotypes structure
which are widely used in classical Chinese and are still common in
vernacular written and spoken Chinese today. Currently, Chinese
Idioms are retrieved in glossary with key character or key word in
morphology or pronunciation index that can not meet the need of
searching semantically. OCIRS is proposed to search the desired
idiom in the case of users only knowing its meaning without any key
character or key word. The user-s request in a sentence or phrase will
be grammatically analyzed in advance by word segmentation, key
word extraction and semantic similarity computation, thus can be
mapped to the idiom domain ontology which is constructed to provide
ample semantic relations and to facilitate description logics-based
reasoning for idiom retrieval. The experimental evaluation shows that
OCIRS realizes the function of searching idioms via semantics, obtaining
preliminary achievement as requested by the users.
Abstract: Severe acute respiratory syndrome (SARS) is a respiratory disease in humans which is caused by the SARS coronavirus. The treatment of coronavirus-associated SARS has been evolving and so far there is no consensus on an optimal regimen. The mainstream therapeutic interventions for SARS involve broad-spectrum antibiotics and supportive care, as well as antiviral agents and immunomodulatory therapy. The Protein- Ligand interaction plays a significant role in structural based drug designing. In the present work we have taken the receptor Angiotensin converting enzyme 2 and identified the drugs that are commonly used against SARS. They are Lopinavir, Ritonavir, Ribavirin, and Oseltamivir. The receptor Angiotensin converting enzyme 2 (ACE-2) was docked with above said drugs and the energy value obtained are as follows, Lopinavir (-292.3), Ritonavir (-325.6), Oseltamivir (- 229.1), Ribavirin (-208.8). Depending on the least energy value we have chosen the best two drugs out of the four conventional drugs. We tried to improve the binding efficiency and steric compatibility of the two drugs namely Ritonavir and Lopinavir. Several modifications were made to the probable functional groups (phenylic, ketonic groups in case of Ritonavir and carboxylic groups in case of Lopinavir respectively) which were interacting with the receptor molecule. Analogs were prepared by Marvin Sketch software and were docked using HEX docking software. Lopinavir analog 8 and Ritonavir analog 11 were detected with significant energy values and are probable lead molecule. It infers that some of the modified drugs are better than the original drugs. Further work can be carried out to improve the steric compatibility of the drug based upon the work done above for a more energy efficient binding of the drugs to the receptor.
Abstract: A new reverse phase-high performance liquid chromatography (RP-HPLC) method with fluorescent detector (FLD) was developed and optimized for Norfloxacin determination in human plasma. Mobile phase specifications, extraction method and excitation and emission wavelengths were varied for optimization. HPLC system contained a reverse phase C18 (5 μm, 4.6 mm×150 mm) column with FLD operated at excitation 330 nm and emission 440 nm. The optimized mobile phase consisted of 14% acetonitrile in buffer solution. The aqueous phase was prepared by mixing 2g of citric acid, 2g sodium acetate and 1 ml of triethylamine in 1 L of Milli-Q water was run at a flow rate of 1.2 mL/min. The standard curve was linear for the range tested (0.156–20 μg/mL) and the coefficient of determination was 0.9978. Aceclofenac sodium was used as internal standard. A detection limit of 0.078 μg/mL was achieved. Run time was set at 10 minutes because retention time of norfloxacin was 0.99 min. which shows the rapidness of this method of analysis. The present assay showed good accuracy, precision and sensitivity for Norfloxacin determination in human plasma with a new internal standard and can be applied pharmacokinetic evaluation of Norfloxacin tablets after oral administration in human.
Abstract: this paper presents an auto-regressive network called the Auto-Regressive Multi-Context Recurrent Neural Network (ARMCRN), which forecasts the daily peak load for two large power plant systems. The auto-regressive network is a combination of both recurrent and non-recurrent networks. Weather component variables are the key elements in forecasting because any change in these variables affects the demand of energy load. So the AR-MCRN is used to learn the relationship between past, previous, and future exogenous and endogenous variables. Experimental results show that using the change in weather components and the change that occurred in past load as inputs to the AR-MCRN, rather than the basic weather parameters and past load itself as inputs to the same network, produce higher accuracy of predicted load. Experimental results also show that using exogenous and endogenous variables as inputs is better than using only the exogenous variables as inputs to the network.
Abstract: The Time-Domain Boundary Element Method (TDBEM)
is a well known numerical technique that handles quite
properly dynamic analyses considering infinite dimension media.
However, when these analyses are also related to nonlinear behavior,
very complex numerical procedures arise considering the TD-BEM,
which may turn its application prohibitive. In order to avoid this
drawback and model nonlinear infinite media, the present work
couples two BEM formulations, aiming to achieve the best of two
worlds. In this context, the regions expected to behave nonlinearly
are discretized by the Domain Boundary Element Method (D-BEM),
which has a simpler mathematical formulation but is unable to deal
with infinite domain analyses; the TD-BEM is employed as in the
sense of an effective non-reflexive boundary. An iterative procedure
is considered for the coupling of the TD-BEM and D-BEM, which is
based on a relaxed renew of the variables at the common interfaces.
Elastoplastic models are focused and different time-steps are allowed
to be considered by each BEM formulation in the coupled analysis.
Abstract: The development of wireless communication technologies has changed our living style in global level. After the international success of mobile telephony standards, the location and time independent voice connection has become a default method in daily telecommunications. As for today, highly advanced multimedia messaging plays a key role in value added service handling. Along with evolving data services, the need for more complex applications can be seen, including the mobile usage of broadcast technologies. Here performance of a system design for terrestrial multimedia content is examined with emphasis on mobile reception. This review paper has accommodated the understanding of physical layer role and the flavour of terrestrial channel effects on the terrestrial multimedia transmission using OFDM keeping DVB-H as benchmark standard.
Abstract: In this paper, we introduce an mobile agent framework
with proactive load balancing for ambient intelligence (AmI) environments.
One of the main obstacles of AmI is the scalability in
which the openness of AmI environment introduces dynamic resource
requirements on agencies. To mediate this scalability problem, our
framework proposes a load balancing module to proactively analyze
the resource consumption of network bandwidth and preferred agencies
to suggest the optimal communication method to its user. The
framework generally formulates an AmI environment that consists
of three main components: (1) mobile devices, (2) hosts or agencies,
and (3) directory service center (DSC). A preliminary implementation
was conducted with NetLogo and the experimental results show that
the proposed approach provides enhanced system performance by
minimizing the network utilization to provide users with responsive
services.
Abstract: Reducing energy consumption of embedded systems requires careful memory management. It has been shown that Scratch- Pad Memories (SPMs) are low size, low cost, efficient (i.e. energy saving) data structures directly managed at the software level. In this paper, the focus is on heuristic methods for SPMs management. A method is efficient if the number of accesses to SPM is as large as possible and if all available space (i.e. bits) is used. A Tabu Search (TS) approach for memory management is proposed which is, to the best of our knowledge, a new original alternative to the best known existing heuristic (BEH). In fact, experimentations performed on benchmarks show that the Tabu Search method is as efficient as BEH (in terms of energy consumption) but BEH requires a sorting which can be computationally expensive for a large amount of data. TS is easy to implement and since no sorting is necessary, unlike BEH, the corresponding sorting time is saved. In addition to that, in a dynamic perspective where the maximum capacity of the SPM is not known in advance, the TS heuristic will perform better than BEH.
Abstract: A bond graph model of an electrical transformer
including the nonlinear saturation is presented. A nonlinear observer for the transformer based on multivariable circle
criterion in the physical domain is proposed. In order to show the saturation and hysteresis effects on the electrical transformer,
simulation results are obtained. Finally, the paper describes that convergence of the estimates to the true states is achieved.
Abstract: The various types of frequent pattern discovery
problem, namely, the frequent itemset, sequence and graph mining
problems are solved in different ways which are, however, in certain
aspects similar. The main approach of discovering such patterns can
be classified into two main classes, namely, in the class of the levelwise
methods and in that of the database projection-based methods.
The level-wise algorithms use in general clever indexing structures
for discovering the patterns. In this paper a new approach is proposed
for discovering frequent sequences and tree-like patterns efficiently
that is based on the level-wise issue. Because the level-wise
algorithms spend a lot of time for the subpattern testing problem, the
new approach introduces the idea of using automaton theory to solve
this problem.
Abstract: Textile structures are engineered and fabricated to
meet worldwide structural applications. Nevertheless, research
varying textile structure on natural fibre as composite reinforcement
was found to be very limited. Most of the research is focusing on
short fibre and random discontinuous orientation of the reinforcement
structure. Realizing that natural fibre (NF) composite had been
widely developed to be used as synthetic fibre composite
replacement, this research attempted to examine the influence of
woven and cross-ply laminated structure towards its mechanical
performances. Laminated natural fibre composites were developed
using hand lay-up and vacuum bagging technique. Impact and
flexural strength were investigated as a function of fibre type (coir
and kenaf) and reinforcement structure (imbalanced plain woven,
0°/90° cross-ply and +45°/-45° cross-ply). Multi-level full factorial
design of experiment (DOE) and analysis of variance (ANOVA) was
employed to impart data as to how fibre type and reinforcement
structure parameters affect the mechanical properties of the
composites. This systematic experimentation has led to determination
of significant factors that predominant influences the impact and
flexural properties of the textile composites. It was proven that both
fibre type and reinforcement structure demonstrated significant
difference results. Overall results indicated that coir composite and
woven structure exhibited better impact and flexural strength. Yet,
cross-ply composite structure demonstrated better fracture resistance.
Abstract: This paper presents an algorithm of particle swarm
optimization with reduction for global optimization problems. Particle
swarm optimization is an algorithm which refers to the collective
motion such as birds or fishes, and a multi-point search algorithm
which finds a best solution using multiple particles. Particle
swarm optimization is so flexible that it can adapt to a number
of optimization problems. When an objective function has a lot of
local minimums complicatedly, the particle may fall into a local
minimum. For avoiding the local minimum, a number of particles are
initially prepared and their positions are updated by particle swarm
optimization. Particles sequentially reduce to reach a predetermined
number of them grounded in evaluation value and particle swarm
optimization continues until the termination condition is met. In order
to show the effectiveness of the proposed algorithm, we examine the
minimum by using test functions compared to existing algorithms.
Furthermore the influence of best value on the initial number of
particles for our algorithm is discussed.
Abstract: The image segmentation method described in this
paper has been developed as a pre-processing stage to be used in
methodologies and tools for video/image indexing and retrieval by
content. This method solves the problem of whole objects extraction
from background and it produces images of single complete objects
from videos or photos. The extracted images are used for calculating
the object visual features necessary for both indexing and retrieval
processes.
The segmentation algorithm is based on the cooperation among an
optical flow evaluation method, edge detection and region growing
procedures. The optical flow estimator belongs to the class of
differential methods. It permits to detect motions ranging from a
fraction of a pixel to a few pixels per frame, achieving good results in
presence of noise without the need of a filtering pre-processing stage
and includes a specialised model for moving object detection.
The first task of the presented method exploits the cues from
motion analysis for moving areas detection. Objects and background
are then refined using respectively edge detection and seeded region
growing procedures. All the tasks are iteratively performed until
objects and background are completely resolved.
The method has been applied to a variety of indoor and outdoor
scenes where objects of different type and shape are represented on
variously textured background.
Abstract: The occurrence and removal of trace organic
contaminants in the aquatic environment has become a focus of
environmental concern. For the selective removal of carbamazepine
from loaded waters molecularly imprinted polymers (MIPs) were
synthesized with carbamazepine as template. Parameters varied were
the type of monomer, crosslinker, and porogen, the ratio of starting
materials, and the synthesis temperature. Best results were obtained
with a template to crosslinker ratio of 1:20, toluene as porogen, and
methacrylic acid (MAA) as monomer. MIPs were then capable to
recover carbamazepine by 93% from a 10-5 M landfill leachate
solution containing also caffeine and salicylic acid. By comparison,
carbamazepine recoveries of 75% were achieved using a nonimprinted
polymer (NIP) synthesized under the same conditions, but
without template. In landfill leachate containing solutions
carbamazepine was adsorbed by 93-96% compared with an uptake of
73% by activated carbon. The best solvent for desorption was
acetonitrile, with which the amount of solvent necessary and dilution
with water was tested. Selected MIPs were tested for their reusability
and showed good results for at least five cycles. Adsorption
isotherms were prepared with carbamazepine solutions in the
concentration range of 0.01 M to 5*10-6 M. The heterogeneity index
showed a more homogenous binding site distribution.
Abstract: The paper explores the development of an optimization of method and apparatus for retrieving extended high dynamic range from digital negative image. Architectural photo imaging can benefit from high dynamic range imaging (HDRI) technique for preserving and presenting sufficient luminance in the shadow and highlight clipping image areas. The HDRI technique that requires multiple exposure images as the source of HDRI rendering may not be effective in terms of time efficiency during the acquisition process and post-processing stage, considering it has numerous potential imaging variables and technical limitations during the multiple exposure process. This paper explores an experimental method and apparatus that aims to expand the dynamic range from digital negative image in HDRI environment. The method and apparatus explored is based on a single source of RAW image acquisition for the use of HDRI post-processing. It will cater the optimization in order to avoid and minimize the conventional HDRI photographic errors caused by different physical conditions during the photographing process and the misalignment of multiple exposed image sequences. The study observes the characteristics and capabilities of RAW image format as digital negative used for the retrieval of extended high dynamic range process in HDRI environment.
Abstract: Ever since industrial revolution began, our ecosystem
has changed. And indeed, the negatives outweigh the positives.
Industrial waste usually released into all kinds of body of water, such
as river or sea. Tempeh waste is one example of waste that carries
many hazardous and unwanted substances that will affect the
surrounding environment. Tempeh is a popular fermented food in
Asia which is rich in nutrients and active substances. Tempeh liquid
waste- in particular- can cause an air pollution, and if penetrates
through the soil, it will contaminates ground-water, making it
unavailable for the water to be consumed. Moreover, bacteria will
thrive within the polluted water, which often responsible for causing
many kinds of diseases. The treatment used for this chemical waste is
biological treatment such as constructed wetland and activated
sludge. These kinds of treatment are able to reduce both physical and
chemical parameters altogether such as temperature, TSS, pH, BOD,
COD, NH3-N, NO3-N, and PO4-P. These treatments are implemented
before the waste is released into the water. The result is a
comparation between constructed wetland and activated sludge,
along with determining which method is better suited to reduce the
physical and chemical subtances of the waste.