Search results for: temporal pattern of gene expression data.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8497

Search results for: temporal pattern of gene expression data.

8047 Association between Single Nucleotide Polymorphism of Calpain1 Gene and Meat Tenderness Traits in Different Genotypes of Chicken: Malaysian Native and Commercial Broiler Line

Authors: Abtehal Y. Anaas, Mohd. Nazmi Bin Abd. Manap

Abstract:

Meat Tenderness is one of the most important factors affecting consumers' assessment of meat quality. Variation in meat tenderness is genetically controlled and varies among breeds, and it is also influenced by environmental factors that can affect its creation during rigor mortis and postmortem. The final postmortem meat tenderization relies on the extent of proteolysis of myofibrillar proteins caused by the endogenous activity of the proteolytic calpain system. This calpain system includes different calcium-dependent cysteine proteases, and an inhibitor, calpastatin. It is widely accepted that in farm animals including chickens, the μ-calpain gene (CAPN1) is a physiological candidate gene for meat tenderness. This study aimed to identify the association of single nucleotide polymorphism (SNP) markers in the CAPN1 gene with the tenderness of chicken breast meat from two Malaysian native and commercial broiler breed crosses. Ten, five months old native chickens and ten, 42 days commercial broilers were collected from the local market and breast muscles were removed two hours after slaughter, packed separately in plastic bags and kept at -20ºC for 24 h. The tenderness phenotype for all chickens’ breast meats was determined by Warner-Bratzler Shear Force (WBSF). Thawing and cooking losses were also measured in the same breast samples before using in WBSF determination. Polymerase chain reaction (PCR) was used to identify the previously reported C7198A and G9950A SNPs in the CAPN1 gene and assess their associations with meat tenderness in the two breeds. The broiler breast meat showed lower shear force values and lower thawing loss rates than the native chickens (p<0.05), whereas there were similar in the rates of cooking loss. The study confirms some previous results that the markers CAPN1 C7198A and G9950A were not significantly associated with the variation in meat tenderness in chickens. Therefore, further study is needed to confirm the functional molecular mechanism of these SNPs and evaluate their associations in different chicken populations.

Keywords: CAPNl, chicken, meat tenderness, meat quality, SNPs.

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8046 Evolution of Developing Flushing Cone during the Pressurized Flushing in Reservoir Storage

Authors: Meshkati M. E., Dehghani A. A., Naser G., E mamgholizadeh S., Mosaedi A.

Abstract:

Sedimentation in reservoirs and the corresponding loss of storage capacity is one of the most serious problems in dam engineering. Pressurized flushing, a way to remove sediments from the reservoir, is flushing under a pressurized flow condition and nearly constant water level. Pressurized flushing has only local effects around the outlet. Sediment in the vicinity of the outlet openings is scoured and a funnel shaped crater is created. In this study, the temporal development of flushing cone under various hydraulic conditions was studied experimentally. Time variations of parameters such as maximum length and width of flushing and also depth of scouring cone was measured. Results indicated that an increase in flow velocity (and consequently in Froude number) established new hydraulically conditions for flushing mechanism and so a sudden growth was observed in the amount of sediment released and also scouring dimenssions. In addition, a set of nondimensional relationships were identified for temporal variations of flushing scour dimenssions, which can eventuallt be used to estimate the development of flushing cone.

Keywords: Pressure Flushing, Dam, Sediment, Scouring.

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8045 A Novel Method for the Characterization of Synchronization and Coupling in Multichannel EEG and ECoG

Authors: Manfred Hartmann, Andreas Graef, Hannes Perko, Christoph Baumgartner, Tilmann Kluge

Abstract:

In this paper we introduce a novel method for the characterization of synchronziation and coupling effects in multivariate time series that can be used for the analysis of EEG or ECoG signals recorded during epileptic seizures. The method allows to visualize the spatio-temporal evolution of synchronization and coupling effects that are characteristic for epileptic seizures. Similar to other methods proposed for this purpose our method is based on a regression analysis. However, a more general definition of the regression together with an effective channel selection procedure allows to use the method even for time series that are highly correlated, which is commonly the case in EEG/ECoG recordings with large numbers of electrodes. The method was experimentally tested on ECoG recordings of epileptic seizures from patients with temporal lobe epilepsies. A comparision with the results from a independent visual inspection by clinical experts showed an excellent agreement with the patterns obtained with the proposed method.

Keywords: EEG, epilepsy, regression analysis, seizurepropagation.

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8044 Developing Structured Sizing Systems for Manufacturing Ready-Made Garments of Indian Females Using Decision Tree-Based Data Mining

Authors: Hina Kausher, Sangita Srivastava

Abstract:

In India, there is a lack of standard, systematic sizing approach for producing readymade garments. Garments manufacturing companies use their own created size tables by modifying international sizing charts of ready-made garments. The purpose of this study is to tabulate the anthropometric data which cover the variety of figure proportions in both height and girth. 3,000 data have been collected by an anthropometric survey undertaken over females between the ages of 16 to 80 years from the some states of India to produce the sizing system suitable for clothing manufacture and retailing. The data are used for the statistical analysis of body measurements, the formulation of sizing systems and body measurements tables. Factor analysis technique is used to filter the control body dimensions from the large number of variables. Decision tree-based data mining is used to cluster the data. The standard and structured sizing system can facilitate pattern grading and garment production. Moreover, it can exceed buying ratios and upgrade size allocations to retail segments.

Keywords: Anthropometric data, data mining, decision tree, garments manufacturing, ready-made garments, sizing systems.

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8043 The Inhibition of Relapse of Orthodontic Tooth Movement by NaF Administration in Expressions of TGF-β1, Runx2, Alkaline Phosphatase and Microscopic Appearance of Woven Bone

Authors: R. Sutjiati, Rubianto, I. B. Narmada, I. K. Sudiana, R. P. Rahayu

Abstract:

The prevalence of post-treatment relapse in orthodontics in the community is high enough; therefore, relapses in orthodontic treatment must be prevented well. The aim of this study is to experimentally test the inhibition of relapse of orthodontics tooth movement in NaF of expression TGF-β1, Runx2, alkaline phosphatase (ALP) and microscopic of woven bone. The research method used was experimental laboratory research involving 30 rats, which were divided into three groups. Group A: rats were not given orthodontic tooth movement and without NaF. Group B: rats were given orthodontic tooth movement and without 11.5 ppm by topical application. Group C: rats were given orthodontic tooth movement and 11.75 ppm by topical application. Orthodontic tooth movement was conducted by applying ligature wires of 0.02 mm in diameter on the molar-1 (M-1) of left permanent maxilla and left insisivus of maxilla. Immunohistochemical examination was conducted to calculate the number of osteoblast to determine TGF β1, Runx2, ALP and haematoxylin to determine woven bone on day 7 and day 14. Results: It was shown that administrations of Natrium Fluoride topical application proved effective to increase the expression of TGF-β1, Runx2, ALP and to increase woven bone in the tension area greater than administration without natrium fluoride topical application (p < 0.05), except the expression of ALP on day 7 and day 14 which was significant. The results of the study show that NaF significantly increases the expressions of TGF-β1, Runx2, ALP and woven bone. The expression of the variables enhanced on day 7 compared on that on day 14, except ALP. Thus, it can be said that the acceleration of woven bone occurs on day 7.

Keywords: TGF-β1, Runx2, ALP, woven bone, natrium fluoride.

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8042 Combining Bagging and Boosting

Authors: S. B. Kotsiantis, P. E. Pintelas

Abstract:

Bagging and boosting are among the most popular resampling ensemble methods that generate and combine a diversity of classifiers using the same learning algorithm for the base-classifiers. Boosting algorithms are considered stronger than bagging on noisefree data. However, there are strong empirical indications that bagging is much more robust than boosting in noisy settings. For this reason, in this work we built an ensemble using a voting methodology of bagging and boosting ensembles with 10 subclassifiers in each one. We performed a comparison with simple bagging and boosting ensembles with 25 sub-classifiers, as well as other well known combining methods, on standard benchmark datasets and the proposed technique was the most accurate.

Keywords: data mining, machine learning, pattern recognition.

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8041 Heuristic Search Algorithms for Tuning PUMA 560 Fuzzy PID Controller

Authors: Sufian Ashraf Mazhari, Surendra Kumar

Abstract:

This paper compares the heuristic Global Search Techniques; Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Generalized Pattern Search, genetic algorithm hybridized with Nelder–Mead and Generalized pattern search technique for tuning of fuzzy PID controller for Puma 560. Since the actual control is in joint space ,inverse kinematics is used to generate various joint angles correspoding to desired cartesian space trajectory. Efficient dynamics and kinematics are modeled on Matlab which takes very less simulation time. Performances of all the tuning methods with and without disturbance are compared in terms of ITSE in joint space and ISE in cartesian space for spiral trajectory tracking. Genetic Algorithm hybridized with Generalized Pattern Search is showing best performance.

Keywords: Controller tuning, Fuzzy Control, Genetic Algorithm, Heuristic search, Robot control.

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8040 DNA Polymorphism Studies of β-Lactoglobulin Gene in Saudi Goats

Authors: Amr A. El Hanafy, Muhammad Qureshi, Jamal Sabir, Mohamed Mutawakil, Mohamed M. Ahmed, Hassan El Ashmaoui, Hassan Ramadan, Mohamed Abou-Alsoud, Mahmoud Abdel Sadek

Abstract:

Domestic goats (Capra hircus) are extremely diverse species and principal animal genetic resource of the developing world. These facilitate a persistent supply of meat, milk, fibre, and skin and are considered as important revenue generators in small pastoral environments. This study aimed to fingerprint β-LG gene at PCR-RFLP level in native Saudi goat breeds (Ardi, Habsi and Harri) in an attempt to have a preliminary image of β-LG genotypic patterns in Saudi breeds as compared to other foreign breeds such as Indian and Egyptian. Also, the Phylogenetic analysis was done to investigate evolutionary trends and similarities among the caprine β-LG gene with that of the other domestic specie, viz. cow, buffalo and sheep. Blood samples were collected from 300 animals (100 for each breed) and genomic DNA was extracted. A fragment of the β-LG gene (427bp) was amplified using specific primers. Subsequent digestion with Sac II restriction endonuclease revealed two alleles (A and B) and three different banding patterns or genotypes i.e. AA, AB and BB. The statistical analysis showed a general trend that β-LG AA genotype had higher milk yield than β-LG AB and β-LG BB genotypes. Nucleotide sequencing of the selected β-LG fragments was done and submitted to GenBank NCBI (Accession No. KJ544248, KJ588275, KJ588276, KJ783455, KJ783456 and KJ874959). Phylogenetic analysis on the basis of nucleotide sequences of native Saudi goats indicated evolutional similarity with the GenBank reference sequences of goat, Bubalus bubalis and Bos taurus. However, the origin of sheep which is the most closely related from the evolutionary point of view, was located some distance away.

Keywords: β-Lactoglobulin, Saudi goats, PCR-RFLP, Phylogenetic analysis.

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8039 Residue and Temporal Trend of Polychlorinated Biphenyls (PCBs) in Surface Soils from Bacninh, Vietnam

Authors: Toan Vu Duc, Son Ha Viet

Abstract:

An evaluation of the PCBs residues in the surface soils from Bacninh, Vietnam was carried out. Sixty representative soil samples were collected from the centre of Bacninh and three surrounding districts. The analyzed results indicated the wide extent of contamination of total PCBs in Bacninh. In industrial and urban zones, total PCBs concentrations ranged from ranged from <0.02 to 32.68ng g-1 (mean 19.89 ±15.64ng g-1) dry weight, while those in agricultural zones ranged from <0.02 to 13.26ng g-1 (mean 8.14 ± 4.89ng g-1) dry weight. The mean percentages of PCB28, PCB52, PCB101, PCB138, PCB153 and PCB180 compared with Σ6PCBs in the analyzed soil samples are 3.1%, 13.9%, 21.7%, 30.7%, 25.8% and 4.8%, respectively. These values can be explained by the chemical properties as well as the compositions of PCBs mixture which probably escaped from dielectric oil. An increasing trend and the long-time release of PCBs are observed.

Keywords: Contamination, PCBs, soil, temporal trend.

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8038 Classroom Teacher Candidates' Definitions and Beliefs about Technology Integration

Authors: Ahmet Baytak, Cenk Akbıyık

Abstract:

The purpose of this paper is to present teacher candidates- beliefs about technology integration in their field of study, which is classroom teaching in this case. The study was conducted among the first year students in college of education in Turkey. This study is based on both quantitative and qualitative data. For the quantitative data- Likert scale was used and for the qualitative data pattern matching was employed. The primary findings showed that students defined educational technology as technologies that improve learning with their visual, easily accessible, and productive features. They also believe these technologies could affect their future students- learning positively.

Keywords: Educational technology, classroom teacher candidates, technology integration, teacher education.

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8037 Minimal Critical Sets of Inertias for Irreducible Zero-nonzero Patterns of Order 3

Authors: Ber-Lin Yu, Ting-Zhu Huang

Abstract:

If there exists a nonempty, proper subset S of the set of all (n + 1)(n + 2)/2 inertias such that S Ôèå i(A) is sufficient for any n × n zero-nonzero pattern A to be inertially arbitrary, then S is called a critical set of inertias for zero-nonzero patterns of order n. If no proper subset of S is a critical set, then S is called a minimal critical set of inertias. In [3], Kim, Olesky and Driessche identified all minimal critical sets of inertias for 2 × 2 zero-nonzero patterns. Identifying all minimal critical sets of inertias for n × n zero-nonzero patterns with n ≥ 3 is posed as an open question in [3]. In this paper, all minimal critical sets of inertias for 3 × 3 zero-nonzero patterns are identified. It is shown that the sets {(0, 0, 3), (3, 0, 0)}, {(0, 0, 3), (0, 3, 0)}, {(0, 0, 3), (0, 1, 2)}, {(0, 0, 3), (1, 0, 2)}, {(0, 0, 3), (2, 0, 1)} and {(0, 0, 3), (0, 2, 1)} are the only minimal critical sets of inertias for 3 × 3 irreducible zerononzero patterns.

Keywords: Permutation digraph, zero-nonzero pattern, irreducible pattern, critical set of inertias, inertially arbitrary.

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8036 A Modified Run Length Coding Technique for Test Data Compression Based on Multi-Level Selective Huffman Coding

Authors: C. Kalamani, K. Paramasivam

Abstract:

Test data compression is an efficient method for reducing the test application cost. The problem of reducing test data has been addressed by researchers in three different aspects: Test Data Compression, Built-in-Self-Test (BIST) and Test set compaction. The latter two methods are capable of enhancing fault coverage with cost of hardware overhead. The drawback of the conventional methods is that they are capable of reducing the test storage and test power but when test data have redundant length of runs, no additional compression method is followed. This paper presents a modified Run Length Coding (RLC) technique with Multilevel Selective Huffman Coding (MLSHC) technique to reduce test data volume, test pattern delivery time and power dissipation in scan test applications where redundant length of runs is encountered then the preceding run symbol is replaced with tiny codeword. Experimental results show that the presented method not only improves the test data compression but also reduces the overall test data volume compared to recent schemes. Experiments for the six largest ISCAS-98 benchmarks show that our method outperforms most known techniques.

Keywords: Modified run length coding, multilevel selective Huffman coding, built-in-self-test modified selective Huffman coding, automatic test equipment.

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8035 Characterization of Novel Atrazine-Degrading Klebsiella sp. isolated from Thai Agricultural Soil

Authors: Sawangjit Sopid

Abstract:

Atrazine, a herbicide widely used in sugarcane and corn production, is a frequently detected groundwater contaminant. An atrazine-degrading bacterium, strain KB02, was obtained from long-term atrazine-treated sugarcane field soils in Kanchanaburi province of Thailand. Strain KB02 had a rod-to-coccus morphological cycle during growth. Sequence analysis of the PCR product indicated that the 16S rRNA gene in strain KB02 was ranging from 97-98% identical to the same region in Klebsiella sp. Based on biochemical, physiological analysis and 16S rDNA sequence analysis of one representative isolate, strain KB02, the isolates belong to the genus Klebsiella in the family Enterobacteriaceae. Interestingly that the various primers for atzA, B and C failed to amplify genomic DNA of strain KB02. Whereas the expected PCR product of atzA, B and C were obtained from the reference strain, Arthrobacter sp. strain KU001.

Keywords: Atrazine, atz gene, Biodegradation, bioremediation, Klebsiella

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8034 Shot Boundary Detection Using Octagon Square Search Pattern

Authors: J. Kavitha, S. Sowmyayani, P. Arockia Jansi Rani

Abstract:

In this paper, a shot boundary detection method is presented using octagon square search pattern. The color, edge, motion and texture features of each frame are extracted and used in shot boundary detection. The motion feature is extracted using octagon square search pattern. Then, the transition detection method is capable of detecting the shot or non-shot boundaries in the video using the feature weight values. Experimental results are evaluated in TRECVID video test set containing various types of shot transition with lighting effects, object and camera movement within the shots. Further, this paper compares the experimental results of the proposed method with existing methods. It shows that the proposed method outperforms the state-of-art methods for shot boundary detection.

Keywords: Content-based indexing and retrieval, cut transition detection, discrete wavelet transform, shot boundary detection, video source.

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8033 The Incidence of Obesity among Adult Women in Pekanbaru City, Indonesia, Related to High Fat Consumption, Stress Level, and Physical Activity

Authors: Yudia Mailani Putri, Martalena Purba, B. J. Istiti Kandarina

Abstract:

Background: Obesity has been recognized as a global health problem. Individuals classified as overweight and obese are increasing at an alarming rate. This condition is associated with psychological and physiological problems. as a person reaches adulthood, somatic growth ceases. At this stage, the human body has developed fully, to a stable state. As the capital of Riau Province in Indonesia, Pekanbaru is dominated by Malay ethnic population habitually consuming cholesterol-rich fatty foods as a daily menu, a trigger to the onset of obesity resulting in high prevalence of degenerative diseases. Research objectives: The aim of this study is elaborating the relationship between high-fat consumption pattern, stress level, physical activity and the incidence of obesity in adult women in Pekanbaru city. Research Methods: Among the combined research methods applied in this study, the first stage is quantitative observational, analytical cross-sectional research design with adult women aged 20-40 living in Pekanbaru city. The sample consists of 200 women with BMI≥25. Sample data is processed with univariate, bivariate (correlation and simple linear regression) and multivariate (multiple linear regression) analysis. The second phase is qualitative descriptive study purposive sampling by in-depth interviews. six participants withdrew from the study. Results: According to the results of the bivariate analysis, there are relationships between the incidence of obesity and the pattern of high fat foods consumption (energy intake (p≤0.000; r = 0.536), protein intake (p≤0.000; r=0.307), fat intake (p≤0.000; r=0.416), carbohydrate intake (p≤0.000; r=0.430), frequency of fatty food consumption (p≤0.000; r=0.506) and frequency of viscera foods consumption (p≤0.000; r=0.535). There is a relationship between physical activity and incidence of obesity (p≤0.000; r=-0.631). However, there is no relationship between the level of stress (p=0.741; r=0.019-) and the incidence of obesity. Physical activity is a predominant factor in the incidence of obesity in adult women in Pekanbaru city. Conclusion: There are relationships between high-fat food consumption pattern, physical activity and the incidence of obesity in Pekanbaru city whereas physical activity is a predominant factor in the occurrence of obesity, supported by the unchangeable pattern of high-fat foods consumption.

Keywords: Obesity, adult, high in fat, stress, physical activity, consumption pattern.

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8032 Techniques Used in String Matching for Network Security

Authors: Jamuna Bhandari

Abstract:

String matching also known as pattern matching is one of primary concept for network security. In this area the effectiveness and efficiency of string matching algorithms is important for applications in network security such as network intrusion detection, virus detection, signature matching and web content filtering system. This paper presents brief review on some of string matching techniques used for network security.

Keywords: Filtering, honeypot, network telescope, pattern, string, signature.

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8031 Finding an Optimized Discriminate Function for Internet Application Recognition

Authors: E. Khorram, S.M. Mirzababaei

Abstract:

Everyday the usages of the Internet increase and simply a world of the data become accessible. Network providers do not want to let the provided services to be used in harmful or terrorist affairs, so they used a variety of methods to protect the special regions from the harmful data. One of the most important methods is supposed to be the firewall. Firewall stops the transfer of such packets through several ways, but in some cases they do not use firewall because of its blind packet stopping, high process power needed and expensive prices. Here we have proposed a method to find a discriminate function to distinguish between usual packets and harmful ones by the statistical processing on the network router logs. So an administrator can alarm to the user. This method is very fast and can be used simply in adjacent with the Internet routers.

Keywords: Data Mining, Firewall, Optimization, Packetclassification, Statistical Pattern Recognition.

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8030 Data Mining Determination of Sunlight Average Input for Solar Power Plant

Authors: Fl. Loury, P. Sablonière, C. Lamoureux, G. Magnier, Th. Gutierrez

Abstract:

A method is proposed to extract faithful representative patterns from data set of observations when they are suffering from non-negligible fluctuations. Supposing time interval between measurements to be extremely small compared to observation time, it consists in defining first a subset of intermediate time intervals characterizing coherent behavior. Data projection on these intervals gives a set of curves out of which an ideally “perfect” one is constructed by taking the sup limit of them. Then comparison with average real curve in corresponding interval gives an efficiency parameter expressing the degradation consecutive to fluctuation effect. The method is applied to sunlight data collected in a specific place, where ideal sunlight is the one resulting from direct exposure at location latitude over the year, and efficiency is resulting from action of meteorological parameters, mainly cloudiness, at different periods of the year. The extracted information already gives interesting element of decision, before being used for analysis of plant control.

Keywords: Base Input Reconstruction, Data Mining, Efficiency Factor, Information Pattern Operator.

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8029 Sounds Alike Name Matching for Myanmar Language

Authors: Yuzana, Khin Marlar Tun

Abstract:

Personal name matching system is the core of essential task in national citizen database, text and web mining, information retrieval, online library system, e-commerce and record linkage system. It has necessitated to the all embracing research in the vicinity of name matching. Traditional name matching methods are suitable for English and other Latin based language. Asian languages which have no word boundary such as Myanmar language still requires sounds alike matching system in Unicode based application. Hence we proposed matching algorithm to get analogous sounds alike (phonetic) pattern that is convenient for Myanmar character spelling. According to the nature of Myanmar character, we consider for word boundary fragmentation, collation of character. Thus we use pattern conversion algorithm which fabricates words in pattern with fragmented and collated. We create the Myanmar sounds alike phonetic group to help in the phonetic matching. The experimental results show that fragmentation accuracy in 99.32% and processing time in 1.72 ms.

Keywords: natural language processing, name matching, phonetic matching

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8028 The Effect of Electrical Stimulation Intensity on VEGF Expression and Biomechanical Properties during Wound

Authors: M R Asadi, G Torkaman, M Hedayati

Abstract:

We evaluated the effect of sensory (direct current (DC), 600μA) and motor (monophasic current, pulse duration 300μs, 100 Hz, 2.5-3mA) intensities of cathodal electrical stimulation (ES) current to release VEGF and biomechanical properties of wound. 54 male Sprague-dawley rats were randomly assigned into one control and two experimental groups. A full thickness skin incision was made on animals- dorsal region. The experimental groups received ES for 1h/day and every other day. VEGF expression was measured in skin on the 7th day after surgical incision and tensile strength was measured on 21st day. On the 7th day, the values of skin VEGF in the sensory group were significantly greater than those of the other groups (p < 0.05). Sensory and Motor intensity stimulation, can not improve the biomechanical properties of the repaired wounds. It seems the mechanical environment induced by sensory and motor intensity of electrical stimulation, could not simulate the role of normal daily stress and strain to maturation of collagen fibers and their cross links. Further work is needed to determine the relationship between VEGF expression after ES and its effect on tensile strength of healed wound.

Keywords: Biomechanical properties Direct current, Monophasic current, Skin, VEGF

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8027 Comparison of Different Hydrograph Routing Techniques in XPSTORM Modelling Software: A Case Study

Authors: Fatema Akram, Mohammad Golam Rasul, Mohammad Masud Kamal Khan, Md. Sharif Imam Ibne Amir

Abstract:

A variety of routing techniques are available to develop surface runoff hydrographs from rainfall. The selection of runoff routing method is very vital as it is directly related to the type of watershed and the required degree of accuracy. There are different modelling softwares available to explore the rainfall-runoff process in urban areas. XPSTORM, a link-node based, integrated stormwater modelling software, has been used in this study for developing surface runoff hydrograph for a Golf course area located in Rockhampton in Central Queensland in Australia. Four commonly used methods, namely SWMM runoff, Kinematic wave, Laurenson, and Time-Area are employed to generate runoff hydrograph for design storm of this study area. In runoff mode of XPSTORM, the rainfall, infiltration, evaporation and depression storage for subcatchments were simulated and the runoff from the subcatchment to collection node was calculated. The simulation results are presented, discussed and compared. The total surface runoff generated by SWMM runoff, Kinematic wave and Time-Area methods are found to be reasonably close, which indicates any of these methods can be used for developing runoff hydrograph of the study area. Laurenson method produces a comparatively less amount of surface runoff, however, it creates highest peak of surface runoff among all which may be suitable for hilly region. Although the Laurenson hydrograph technique is widely acceptable surface runoff routing technique in Queensland (Australia), extensive investigation is recommended with detailed topographic and hydrologic data in order to assess its suitability for use in the case study area.

Keywords: ARI, design storm, IFD, rainfall temporal pattern, routing techniques, surface runoff, XPSTORM.

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8026 Input Data Balancing in a Neural Network PM-10 Forecasting System

Authors: Suk-Hyun Yu, Heeyong Kwon

Abstract:

Recently PM-10 has become a social and global issue. It is one of major air pollutants which affect human health. Therefore, it needs to be forecasted rapidly and precisely. However, PM-10 comes from various emission sources, and its level of concentration is largely dependent on meteorological and geographical factors of local and global region, so the forecasting of PM-10 concentration is very difficult. Neural network model can be used in the case. But, there are few cases of high concentration PM-10. It makes the learning of the neural network model difficult. In this paper, we suggest a simple input balancing method when the data distribution is uneven. It is based on the probability of appearance of the data. Experimental results show that the input balancing makes the neural networks’ learning easy and improves the forecasting rates.

Keywords: AI, air quality prediction, neural networks, pattern recognition, PM-10.

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8025 Analysis of Feature Space for a 2d/3d Vision based Emotion Recognition Method

Authors: Robert Niese, Ayoub Al-Hamadi, Bernd Michaelis

Abstract:

In modern human computer interaction systems (HCI), emotion recognition is becoming an imperative characteristic. The quest for effective and reliable emotion recognition in HCI has resulted in a need for better face detection, feature extraction and classification. In this paper we present results of feature space analysis after briefly explaining our fully automatic vision based emotion recognition method. We demonstrate the compactness of the feature space and show how the 2d/3d based method achieves superior features for the purpose of emotion classification. Also it is exposed that through feature normalization a widely person independent feature space is created. As a consequence, the classifier architecture has only a minor influence on the classification result. This is particularly elucidated with the help of confusion matrices. For this purpose advanced classification algorithms, such as Support Vector Machines and Artificial Neural Networks are employed, as well as the simple k- Nearest Neighbor classifier.

Keywords: Facial expression analysis, Feature extraction, Image processing, Pattern Recognition, Application.

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8024 A Constrained Clustering Algorithm for the Classification of Industrial Ores

Authors: Luciano Nieddu, Giuseppe Manfredi

Abstract:

In this paper a Pattern Recognition algorithm based on a constrained version of the k-means clustering algorithm will be presented. The proposed algorithm is a non parametric supervised statistical pattern recognition algorithm, i.e. it works under very mild assumptions on the dataset. The performance of the algorithm will be tested, togheter with a feature extraction technique that captures the information on the closed two-dimensional contour of an image, on images of industrial mineral ores.

Keywords: K-means, Industrial ores classification, Invariant Features, Supervised Classification.

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8023 Learning Spatio-Temporal Topology of a Multi-Camera Network by Tracking Multiple People

Authors: Yunyoung Nam, Junghun Ryu, Yoo-Joo Choi, We-Duke Cho

Abstract:

This paper presents a novel approach for representing the spatio-temporal topology of the camera network with overlapping and non-overlapping fields of view (FOVs). The topology is determined by tracking moving objects and establishing object correspondence across multiple cameras. To track people successfully in multiple camera views, we used the Merge-Split (MS) approach for object occlusion in a single camera and the grid-based approach for extracting the accurate object feature. In addition, we considered the appearance of people and the transition time between entry and exit zones for tracking objects across blind regions of multiple cameras with non-overlapping FOVs. The main contribution of this paper is to estimate transition times between various entry and exit zones, and to graphically represent the camera topology as an undirected weighted graph using the transition probabilities.

Keywords: Surveillance, multiple camera, people tracking, topology.

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8022 A Robust Method for Finding Nearest-Neighbor using Hexagon Cells

Authors: Ahmad Attiq Al-Ogaibi, Ahmad Sharieh, Moh’d Belal Al-Zoubi, R. Bremananth

Abstract:

In pattern clustering, nearest neighborhood point computation is a challenging issue for many applications in the area of research such as Remote Sensing, Computer Vision, Pattern Recognition and Statistical Imaging. Nearest neighborhood computation is an essential computation for providing sufficient classification among the volume of pixels (voxels) in order to localize the active-region-of-interests (AROI). Furthermore, it is needed to compute spatial metric relationships of diverse area of imaging based on the applications of pattern recognition. In this paper, we propose a new methodology for finding the nearest neighbor point, depending on making a virtually grid of a hexagon cells, then locate every point beneath them. An algorithm is suggested for minimizing the computation and increasing the turnaround time of the process. The nearest neighbor query points Φ are fetched by seeking fashion of hexagon holistic. Seeking will be repeated until an AROI Φ is to be expected. If any point Υ is located then searching starts in the nearest hexagons in a circular way. The First hexagon is considered be level 0 (L0) and the surrounded hexagons is level 1 (L1). If Υ is located in L1, then search starts in the next level (L2) to ensure that Υ is the nearest neighbor for Φ. Based on the result and experimental results, we found that the proposed method has an advantage over the traditional methods in terms of minimizing the time complexity required for searching the neighbors, in turn, efficiency of classification will be improved sufficiently.

Keywords: Hexagon cells, k-nearest neighbors, Nearest Neighbor, Pattern recognition, Query pattern, Virtually grid

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8021 Evaluation of Natural Drainage Flow Pattern, Necessary for Flood Control, Using Digitized Topographic Information: A Case Study of Bayelsa State Nigeria

Authors: Collins C. Chiemeke

Abstract:

The need to evaluate and understand the natural drainage pattern in a flood prone, and fast developing environment is of paramount importance. This information will go a long way to help the town planners to determine the drainage pattern, road networks and areas where prominent structures are to be located. This research work was carried out with the aim of studying the Bayelsa landscape topography using digitized topographic information, and to model the natural drainage flow pattern that will aid the understanding and constructions of workable drainages. To achieve this, digitize information of elevation and coordinate points were extracted from a global imagery map. The extracted information was modeled into 3D surfaces. The result revealed that the average elevation for Bayelsa State is 12 m above sea level. The highest elevation is 28 m, and the lowest elevation 0 m, along the coastline. In Yenagoa the capital city of Bayelsa were a detail survey was carried out showed that average elevation is 15 m, the highest elevation is 25 m and lowest is 3 m above the mean sea level. The regional elevation in Bayelsa, showed a gradation decrease from the North Eastern zone to the South Western Zone. Yenagoa showed an observed elevation lineament, were low depression is flanked by high elevation that runs from the North East to the South west. Hence, future drainages in Yenagoa should be directed from the high elevation, from South East toward the North West and from the North West toward South East, to the point of convergence which is at the center that flows from South East toward the North West. Bayelsa when considered on a regional Scale, the flow pattern is from the North East to the South West, and also North South. It is recommended that in the event of any large drainage construction at municipal scale, it should be directed from North East to the South West or from North to South. Secondly, detail survey should be carried out to ascertain the local topography and the drainage pattern before the design and construction of any drainage system in any part of Bayelsa.

Keywords: Bayelsa, Digitized Topographic Information, Drainage, Flood.

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8020 Analyzing the Impact of Spatio-Temporal Climate Variations on the Rice Crop Calendar in Pakistan

Authors: Muhammad Imran, Iqra Basit, Mobushir Riaz Khan, Sajid Rasheed Ahmad

Abstract:

The present study investigates the space-time impact of climate change on the rice crop calendar in tropical Gujranwala, Pakistan. The climate change impact was quantified through the climatic variables, whereas the existing calendar of the rice crop was compared with the phonological stages of the crop, depicted through the time series of the Normalized Difference Vegetation Index (NDVI) derived from Landsat data for the decade 2005-2015. Local maxima were applied on the time series of NDVI to compute the rice phonological stages. Panel models with fixed and cross-section fixed effects were used to establish the relation between the climatic parameters and the time-series of NDVI across villages and across rice growing periods. Results show that the climatic parameters have significant impact on the rice crop calendar. Moreover, the fixed effect model is a significant improvement over cross-sectional fixed effect models (R-squared equal to 0.673 vs. 0.0338). We conclude that high inter-annual variability of climatic variables cause high variability of NDVI, and thus, a shift in the rice crop calendar. Moreover, inter-annual (temporal) variability of the rice crop calendar is high compared to the inter-village (spatial) variability. We suggest the local rice farmers to adapt this change in the rice crop calendar.

Keywords: Landsat NDVI, panel models, temperature, rainfall.

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8019 A Computational Cost-Effective Clustering Algorithm in Multidimensional Space Using the Manhattan Metric: Application to the Global Terrorism Database

Authors: Semeh Ben Salem, Sami Naouali, Moetez Sallami

Abstract:

The increasing amount of collected data has limited the performance of the current analyzing algorithms. Thus, developing new cost-effective algorithms in terms of complexity, scalability, and accuracy raised significant interests. In this paper, a modified effective k-means based algorithm is developed and experimented. The new algorithm aims to reduce the computational load without significantly affecting the quality of the clusterings. The algorithm uses the City Block distance and a new stop criterion to guarantee the convergence. Conducted experiments on a real data set show its high performance when compared with the original k-means version.

Keywords: Pattern recognition, partitional clustering, K-means clustering, Manhattan distance, terrorism data analysis.

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8018 Feature Subset Selection approach based on Maximizing Margin of Support Vector Classifier

Authors: Khin May Win, Nan Sai Moon Kham

Abstract:

Identification of cancer genes that might anticipate the clinical behaviors from different types of cancer disease is challenging due to the huge number of genes and small number of patients samples. The new method is being proposed based on supervised learning of classification like support vector machines (SVMs).A new solution is described by the introduction of the Maximized Margin (MM) in the subset criterion, which permits to get near the least generalization error rate. In class prediction problem, gene selection is essential to improve the accuracy and to identify genes for cancer disease. The performance of the new method was evaluated with real-world data experiment. It can give the better accuracy for classification.

Keywords: Microarray data, feature selection, recursive featureelimination, support vector machines.

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