Abstract: This paper proposes a stroke extraction method for use in off-line signature verification. After giving a brief overview of the current ongoing researches an algorithm is introduced for detecting and following strokes in static images of signatures. Problems like the handling of junctions and variations in line width and line intensity are discussed in detail. Results are validated by both using an existing on-line signature database and by employing image registration methods.
Abstract: This paper describes the design of new method of
propagation delay measurement in micro and nanostructures during
characterization of ASIC standard library cell. Providing more
accuracy timing information about library cell to the design team we
can improve a quality of timing analysis inside of ASIC design flow
process. Also, this information could be very useful for semiconductor
foundry team to make correction in technology process. By
comparison of the propagation delay in the CMOS element and result
of analog SPICE simulation. It was implemented as digital IP core for
semiconductor manufacturing process. Specialized method helps to
observe the propagation time delay in one element of the standard-cell
library with up-to picoseconds accuracy and less. Thus, the special
useful solutions for VLSI schematic to parameters extraction, basic
cell layout verification, design simulation and verification are
announced.
Abstract: Artificial neural networks (ANN) have the ability to model input-output relationships from processing raw data. This characteristic makes them invaluable in industry domains where such knowledge is scarce at best. In the recent decades, in order to overcome the black-box characteristic of ANNs, researchers have attempted to extract the knowledge embedded within ANNs in the form of rules that can be used in inference systems. This paper presents a new technique that is able to extract a small set of rules from a two-layer ANN. The extracted rules yield high classification accuracy when implemented within a fuzzy inference system. The technique targets industry domains that possess less complex problems for which no expert knowledge exists and for which a simpler solution is preferred to a complex one. The proposed technique is more efficient, simple, and applicable than most of the previously proposed techniques.
Abstract: The optimal extraction condition of dried
Echinocactus grusonii powder was studied. The three independent
variables are raw material drying temperature, extraction
temperature, and extraction time. The dependent variables are both
yield percentage of crude extract and total phenolic quantification as
gallic acid equivalent in crude extract. The experimental design was
based on central composite design. Highest yield percentage of crude
extract could get from extraction condition at raw material drying
temperature at 60°C, extraction temperature at 15°C, and extraction
time for 25 min °C. Moreover, the crude extract with highest phenolic
occurred by extraction condition of raw material drying temperature
at 60°C, extraction temperature at 35 °C, and extraction lasting 25
min.
Abstract: This study aims to assess the potential of solar energy technology for improving access to water and hence the livelihood strategies of rural communities in Baja California Sur, Mexico. It focuses on livestock ranches and photovoltaic water-pumptechnology as well as other water extraction methods. The methodology used are the Sustainable Livelihoods and the Appropriate Technology approaches. A household survey was applied in June of 2006 to 32 ranches in the municipality, of which 22 used PV pumps; and semi-structured interviews were conducted. Findings indicate that solar pumps have in fact helped people improve their quality of life by allowing them to pursue a different livelihood strategy and that improved access to water -not necessarily as more water but as less effort to extract and collect it- does not automatically imply overexploitation of the resource; consumption is based on basic needs as well as on storage and pumping capacity. Justification for such systems lies in the avoidance of logistical problems associated to fossil fuels, PV pumps proved to be the most beneficial when substituting gasoline or diesel equipment but of dubious advantage if intended to replace wind or gravity systems. Solar water pumping technology-s main obstacle to dissemination are high investment and repairs costs and it is therefore not suitable for all cases even when insolation rates and water availability are adequate. In cases where affordability is not an obstacle it has become an important asset that contributes –by means of reduced expenses, less effort and saved time- to the improvement of livestock, the main livelihood provider for these ranches.
Abstract: Optimization of a microwave-assisted extraction of cherry laurel (Prunus laurocerasus) fruit using methanol was studied. The influence of process parameters (microwave power, plant material-to-solvent ratio and the extraction time) on the extraction efficiency were optimized by using response surface methodology. The predicted maximum yield of extractive substances (41.85 g/100 g fresh plant material) was obtained at microwave power of 600 W and plant material to solvent ratio of 0.2 g/cm3 after 26 minutes of extraction, while a mean value of 40.80±0.41 g/100 g fresh plant material was obtained from laboratory experiments. This proves applicability of the model in predicting optimal extraction conditions with minimal laborious and time consuming. The results indicated that all process parameters were effective on the extraction efficiency, while the most important factor was extraction time. In order to rationalize production the optimal economical condition which gave a large total extract yield with minimal energy and solvent consumption was found.
Abstract: A new and cost effective RP-HPLC method was
developed and validated for simultaneous analysis of non steroidal
anti inflammatory dugs Diclofenac sodium (DFS), Flurbiprofen
(FLP) and an opioid analgesic Tramadol (TMD) in advanced drug
delivery systems (Liposome and Microcapsules), marketed brands
and human plasma. Isocratic system was employed for the flow of
mobile phase consisting of 10 mM sodium dihydrogen phosphate
buffer and acetonitrile in molar ratio of 67: 33 with adjusted pH of
3.2. The stationary phase was hypersil ODS column (C18, 250×4.6
mm i.d., 5 μm) with controlled temperature of 30 C°. DFS in
liposomes, microcapsules and marketed drug products was
determined in range of 99.76-99.84%. FLP and TMD in
microcapsules and brands formulation were 99.78 - 99.94 % and
99.80 - 99.82 %, respectively. Single step liquid-liquid extraction
procedure using combination of acetonitrile and trichloroacetic acid
(TCA) as protein precipitating agent was employed. The detection
limits (at S/N ratio 3) of quality control solutions and plasma samples
were 10, 20, and 20 ng/ml for DFS, FLP and TMD, respectively.
The Assay was acceptable in linear dynamic range. All other
validation parameters were found in limits of FDA and ICH method
validation guidelines. The proposed method is sensitive, accurate and
precise and could be applicable for routine analysis in
pharmaceutical industry as well as in human plasma samples for
bioequivalence and pharmacokinetics studies.
Abstract: Studies in economics domain tried to reveal the correlation between stock markets. Since the globalization era, interdependence between stock markets becomes more obvious. The Dynamic Interaction Network (DIN) algorithm, which was inspired by a Gene Regulatory Network (GRN) extraction method in the bioinformatics field, is applied to reveal important and complex dynamic relationship between stock markets. We use the data of the stock market indices from eight countries around the world in this study. Our results conclude that DIN is able to reveal and model patterns of dynamic interaction from the observed variables (i.e. stock market indices). Furthermore, it is also found that the extracted network models can be utilized to predict movement of the stock market indices with a considerably good accuracy.
Abstract: An effective approach for extracting document images from a noisy background is introduced. The entire scheme is divided into three sub- stechniques – the initial preprocessing operations for noise cluster tightening, introduction of a new thresholding method by maximizing the ratio of stan- dard deviations of the combined effect on the image to the sum of weighted classes and finally the image restoration phase by image binarization utiliz- ing the proposed optimum threshold level. The proposed method is found to be efficient compared to the existing schemes in terms of computational complexity as well as speed with better noise rejection.
Abstract: This paper presents an algorithm based on the
wavelet decomposition, for feature extraction from the ECG signal
and recognition of three types of Ventricular Arrhythmias using
neural networks. A set of Discrete Wavelet Transform (DWT)
coefficients, which contain the maximum information about the
arrhythmias, is selected from the wavelet decomposition. After that a
novel clustering algorithm based on nature inspired algorithm (Ant
Colony Optimization) is developed for classifying arrhythmia types.
The algorithm is applied on the ECG registrations from the MIT-BIH
arrhythmia and malignant ventricular arrhythmia databases. We
applied Daubechies 4 wavelet in our algorithm. The wavelet
decomposition enabled us to perform the task efficiently and
produced reliable results.
Abstract: Fishing has always been an essential component of
the Polynesians- life. Fishhooks, mostly in pearl shell, found during
archaeological excavations are the artifacts related to this activity the
most numerous. Thanks to them, we try to reconstruct the ancient
techniques of resources exploitation, inside the lagoons and offshore.
They can also be used as chronological and cultural indicators. The
shapes and dimensions of these artifacts allow comparisons and
classifications used in both functional approach and chrono-cultural
perspective. Hence it is very important for the ethno-archaeologists
to dispose of reliable methods and standardized measurement of
these artifacts. Such a reliable objective and standardized method
have been previously proposed. But this method cannot be envisaged
manually because of the very important time required to measure
each fishhook manually and the quantity of fishhooks to measure
(many hundreds). We propose in this paper a detailed acquisition
protocol of fishhooks and an automation of every step of this method.
We also provide some experimental results obtained on the fishhooks
coming from three archaeological excavations sites.
Abstract: This paper used a fuzzy kohonen neural network for medical image segmentation. Image segmentation plays a important role in the many of medical imaging applications by automating or facilitating the diagnostic. The paper analyses the tumor by extraction of the features of (area, entropy, means and standard deviation).These measurements gives a description for a tumor.
Abstract: Slag sample from copper smelting operation in a
water jacket furnace from DRC plant was used. The study intends to
determine the effect of cooling in the extraction of base metals. The
cooling methods investigated were water quenching, air cooling and
furnace cooling. The latter cooling ways were compared to the
original as received slag. It was observed that, the cooling rate of the
slag affected the leaching of base metals as it changed the phase
distribution in the slag and the base metals distribution within the
phases. It was also found that fast cooling of slag prevented
crystallization and produced an amorphous phase that encloses the
base metals. The amorphous slags from the slag dumps were more
leachable in acidic medium (HNO3) which leached 46%Cu, 95% Co,
85% Zn, 92% Pb and 79% Fe with no selectivity at pH0, than in
basic medium (NH4OH). The leachability was vice versa for the
modified slags by quenching in water which leached 89%Cu with a
high selectivity as metal extractions are less than 1% for Co, Zn, Pb
and Fe at ambient temperature and pH12. For the crystallized slags,
leaching of base metals increased with the increase of temperature
from ambient temperature to 60°C and decreased at the higher
temperature of 80°C due to the evaporation of the ammonia solution
used for basic leaching, the total amounts of base metals that were
leached in slow cooled slags were very low compared to the
quenched slag samples.
Abstract: Hypericum perforatum L. is a member of the Hypericaceae (Guttiferae) family and commonly known as St. John’s wort. There is a growing interest in this medicinal plant because of the constituents of this genus. A number of species have been shown to possess various biological activities such as antiviral, wound healing, analgesic, hepatoprotective, antimicrobial and antioxidant activities and also have therapeutic effects on burns, bruises, swelling, anxiety and mild to moderate depression.
In this study, the aerial parts of Hypericum perforatum L. are extracted and the main and effective constituents are determined. The analysis of the extracts was performed by GC-MS and LC-MS. As a next step, it is aimed to investigate the usage of the main constituents of the medicinal plant.
Abstract: The novelty proposed in this study is twofold and consists in the developing of a new color similarity metric based on the human visual system and a new color indexing based on a textual approach. The new color similarity metric proposed is based on the color perception of the human visual system. Consequently the results returned by the indexing system can fulfill as much as possibile the user expectations. We developed a web application to collect the users judgments about the similarities between colors, whose results are used to estimate the metric proposed in this study. In order to index the image's colors, we used a text indexing engine to facilitate the integration of visual features in a database of text documents. The textual signature is build by weighting the image's colors in according to their occurrence in the image. The use of a textual indexing engine, provide us a simple, fast and robust solution to index images. A typical usage of the system proposed in this study, is the development of applications whose data type is both visual and textual. In order to evaluate the proposed method we chose a price comparison engine as a case of study, collecting a series of commercial offers containing the textual description and the image representing a specific commercial offer.
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: 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: 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: This paper proposes a system to extract images from web pages and then detect the skin color regions of these images. As part of the proposed system, using BandObject control, we built a Tool bar named 'Filter Tool Bar (FTB)' by modifying the Pavel Zolnikov implementation. The Yahoo! Team provides us with the Yahoo! SDK API, which also supports image search and is really useful. In the proposed system, we introduced three new methods for extracting images from the web pages (after loading the web page by using the proposed FTB, before loading the web page physically from the localhost, and before loading the web page from any server). These methods overcome the drawback of the regular expressions method for extracting images suggested by Ilan Assayag. The second part of the proposed system is concerned with the detection of the skin color regions of the extracted images. So, we studied two famous skin color detection techniques. The first technique is based on the RGB color space and the second technique is based on YUV and YIQ color spaces. We modified the second technique to overcome the failure of detecting complex image's background by using the saturation parameter to obtain an accurate skin detection results. The performance evaluation of the efficiency of the proposed system in extracting images before and after loading the web page from localhost or any server in terms of the number of extracted images is presented. Finally, the results of comparing the two skin detection techniques in terms of the number of pixels detected are presented.
Abstract: Recognition of Indian languages scripts is challenging problems. In Optical Character Recognition [OCR], a character or symbol to be recognized can be machine printed or handwritten characters/numerals. There are several approaches that deal with problem of recognition of numerals/character depending on the type of feature extracted and different way of extracting them. This paper proposes a recognition scheme for handwritten Hindi (devnagiri) numerals; most admired one in Indian subcontinent. Our work focused on a technique in feature extraction i.e. global based approach using end-points information, which is extracted from images of isolated numerals. These feature vectors are fed to neuro-memetic model [18] that has been trained to recognize a Hindi numeral. The archetype of system has been tested on varieties of image of numerals. . In proposed scheme data sets are fed to neuro-memetic algorithm, which identifies the rule with highest fitness value of nearly 100 % & template associates with this rule is nothing but identified numerals. Experimentation result shows that recognition rate is 92-97 % compared to other models.