N-Sun Decomposition of Complete Graphs and Complete Bipartite Graphs

Graph decompositions are vital in the study of combinatorial design theory. Given two graphs G and H, an H-decomposition of G is a partition of the edge set of G into disjoint isomorphic copies of H. An n-sun is a cycle Cn with an edge terminating in a vertex of degree one attached to each vertex. In this paper we have proved that the complete graph of order 2n, K2n can be decomposed into n-2 n-suns, a Hamilton cycle and a perfect matching, when n is even and for odd case, the decomposition is n-1 n-suns and a perfect matching. For an odd order complete graph K2n+1, delete the star subgraph K1, 2n and the resultant graph K2n is decomposed as in the case of even order. The method of building n-suns uses Walecki's construction for the Hamilton decomposition of complete graphs. A spanning tree decomposition of even order complete graphs is also discussed using the labeling scheme of n-sun decomposition. A complete bipartite graph Kn, n can be decomposed into n/2 n-suns when n/2 is even. When n/2 is odd, Kn, n can be decomposed into (n-2)/2 n-suns and a Hamilton cycle.

Determining the Online Purchasing Loyalty for Thai Herbal Products

The objective of this study is to identify the factors that influence the online purchasing loyalty for Thai herbal products. Survey research is used to gather data from Thai herb online merchants to assess factors that have impacts on enhancing loyalty. Data were collected from 300 online customers who had experience in online purchasing of Thai Herbal products. Prior experience consists of data from previous usage of online herbs, herb purchase and internet usage. E-Quality data consists of information quality, system quality, service quality and the product quality of Thai herbal products sold online. The results suggest that prior experience, Equality, attitude toward purchase and trust in online merchant have major impacts on loyalty. The good attitude and E-Quality of purchasing Thai herbal product online are the most significant determinants affecting loyalty.

Textile Technology: Application in Sport and Medicine

Sport is one of the sectors in which the largest technical projections regarding the functions of textiles can be found. He is a large consumer of high performance composite materials and new fibers. It is one of the sectors where the innovation is the most important when the greatest numbers of spectacular developments are aimed at increasing performance. In medicine, textile innovation is used and contributes in the amelioration of different materials such as dressing, orthosis, bandages, etc. The hygienic textiles in non-woven materials record a strong growth. The objective of this study is to show the different advances of development we obtained in the both ways (sport and medicine). Polyamide fibers where developed tacking into account the specification of the high level athlete’s performance like swimming and triathlon (Olympic Games, Brazil 2016). The first textile utilization was for skiing (Olympic Games, Sotchi 2014). The different textiles technologies where adapted for medicine.

Photon Localization inside a Waveguide Modeled by Uncertainty Principle

In the present work, an attempt is made to understand electromagnetic field confinement in a subwavelength waveguide structure using concepts of quantum mechanics. Evanescent field in the waveguide is looked as inability of the photon to get confined in the waveguide core and uncertainty of position is assigned to it. The momentum uncertainty is calculated from position uncertainty. Schrödinger wave equation for the photon is written by incorporating position-momentum uncertainty. The equation is solved and field distribution in the waveguide is obtained. The field distribution and power confinement is compared with conventional waveguide theory. They were found in good agreement with each other.

Hydrolysis of Hull-Less Pumpkin Oil Cake Protein Isolate by Pepsin

The present work represents an investigation of the hydrolysis of hull-less pumpkin (Cucurbita Pepo L.) oil cake protein isolate (PuOC PI) by pepsin. To examine the effectiveness and suitability of pepsin towards PuOC PI the kinetic parameters for pepsin on PuOC PI were determined and then, the hydrolysis process was studied using Response Surface Methodology (RSM). The hydrolysis was carried out at temperature of 30°C and pH 3.00. Time and initial enzyme/substrate ratio (E/S) at three levels were selected as the independent parameters. The degree of hydrolysis, DH, was mesuared after 20, 30 and 40 minutes, at initial E/S of 0.7, 1 and 1.3 mA/mg proteins. Since the proposed second-order polynomial model showed good fit with the experimental data (R2 = 0.9822), the obtained mathematical model could be used for monitoring the hydrolysis of PuOC PI by pepsin, under studied experimental conditions, varying the time and initial E/S. To achieve the highest value of DH (39.13 %), the obtained optimum conditions for time and initial E/S were 30 min and 1.024 mA/mg proteins.

ADABeV: Automatic Detection of Abnormal Behavior in Video-surveillance

Intelligent Video-Surveillance (IVS) systems are being more and more popular in security applications. The analysis and recognition of abnormal behaviours in a video sequence has gradually drawn the attention in the field of IVS, since it allows filtering out a large number of useless information, which guarantees the high efficiency in the security protection, and save a lot of human and material resources. We present in this paper ADABeV, an intelligent video-surveillance framework for event recognition in crowded scene to detect the abnormal human behaviour. This framework is attended to be able to achieve real-time alarming, reducing the lags in traditional monitoring systems. This architecture proposal addresses four main challenges: behaviour understanding in crowded scenes, hard lighting conditions, multiple input kinds of sensors and contextual-based adaptability to recognize the active context of the scene.

Performance Monitoring of the Refrigeration System with Minimum Set of Sensors

This paper describes a methodology for remote performance monitoring of retail refrigeration systems. The proposed framework starts with monitoring of the whole refrigeration circuit which allows detecting deviations from expected behavior caused by various faults and degradations. The subsequent diagnostics methods drill down deeper in the equipment hierarchy to more specifically determine root causes. An important feature of the proposed concept is that it does not require any additional sensors, and thus, the performance monitoring solution can be deployed at a low installation cost. Moreover only a minimum of contextual information is required, which also substantially reduces time and cost of the deployment process.

Accurate Time Domain Method for Simulation of Microstructured Electromagnetic and Photonic Structures

A time-domain numerical model within the framework of transmission line modeling (TLM) is developed to simulate electromagnetic pulse propagation inside multiple microcavities forming photonic crystal (PhC) structures. The model developed is quite general and is capable of simulating complex electromagnetic problems accurately. The field quantities can be mapped onto a passive electrical circuit equivalent what ensures that TLM is provably stable and conservative at a local level. Furthermore, the circuit representation allows a high level of hybridization of TLM with other techniques and lumped circuit models of components and devices. A photonic crystal structure formed by rods (or blocks) of high-permittivity dieletric material embedded in a low-dielectric background medium is simulated as an example. The model developed gives vital spatio-temporal information about the signal, and also gives spectral information over a wide frequency range in a single run. The model has wide applications in microwave communication systems, optical waveguides and electromagnetic materials simulations.

Eco-Innovation as a New Sustainable Development Strategy: Case Studies

Sustainable development is one of the most debated issues, recently. In terms of providing more livable Earth continuity, while Production activities are going on, on the other hand protecting the environment has importance. As a strategy for sustainable development, eco-innovation is the application of innovations to reduce environmental burdens. Endeavors to understand ecoinnovation processes have been affected from environmental economics and innovation economics from neoclassical economics, and evolutionary economics other than neoclassical economics. In the light of case study analyses, this study aims to display activities in this field through case studies after explaining the theoretical framework of eco-innovations. This study consists of five sections including introduction and conclusion. In the second part of the study identifications of the concepts related with eco-innovation are described and eco-innovations are classified. Third section considers neoclassical and evolutionary approaches from neoclassical economics and evolutionary economics, respectively. Fourth section gives the case studies of successful eco-innovations. Last section is the conclusion part and offers suggestions for future eco-innovation research according to the theoretical framework and the case studies.

Semi-Blind Two-Dimensional Code Acquisition in CDMA Communications

In this paper, we propose a new algorithm for joint time-delay and direction-of-arrival (DOA) estimation, here called two-dimensional code acquisition, in an asynchronous directsequence code-division multiple-access (DS-CDMA) array system. This algorithm depends on eigenvector-eigenvalue decomposition of sample correlation matrix, and requires to know desired user-s training sequence. The performance of the algorithm is analyzed both analytically and numerically in uncorrelated and coherent multipath environment. Numerical examples show that the algorithm is robust with unknown number of coherent signals.

Knowledge Management Applied to Forensic Sciences

This paper presents initiatives of Knowledge Management (KM) applied to Forensic Sciences field, especially developed at the Forensic Science Institute of the Brazilian Federal Police. Successful projects, related to knowledge sharing, drugs analysis and environmental crimes, are reported in the KM perspective. The described results are related to: a) the importance of having an information repository, like a digital library, in such a multidisciplinary organization; b) the fight against drug dealing and environmental crimes, enabling the possibility to map the evolution of crimes, drug trafficking flows, and the advance of deforestation in Amazon rain forest. Perspectives of new KM projects under development and studies are also presented, tracing an evolution line of the KM view at the Forensic Science Institute.

Developing New Processes and Optimizing Performance Using Response Surface Methodology

Response surface methodology (RSM) is a very efficient tool to provide a good practical insight into developing new process and optimizing them. This methodology could help engineers to raise a mathematical model to represent the behavior of system as a convincing function of process parameters. Through this paper the sequential nature of the RSM surveyed for process engineers and its relationship to design of experiments (DOE), regression analysis and robust design reviewed. The proposed four-step procedure in two different phases could help system analyst to resolve the parameter design problem involving responses. In order to check accuracy of the designed model, residual analysis and prediction error sum of squares (PRESS) described. It is believed that the proposed procedure in this study can resolve a complex parameter design problem with one or more responses. It can be applied to those areas where there are large data sets and a number of responses are to be optimized simultaneously. In addition, the proposed procedure is relatively simple and can be implemented easily by using ready-made standard statistical packages.

A Text Clustering System based on k-means Type Subspace Clustering and Ontology

This paper presents a text clustering system developed based on a k-means type subspace clustering algorithm to cluster large, high dimensional and sparse text data. In this algorithm, a new step is added in the k-means clustering process to automatically calculate the weights of keywords in each cluster so that the important words of a cluster can be identified by the weight values. For understanding and interpretation of clustering results, a few keywords that can best represent the semantic topic are extracted from each cluster. Two methods are used to extract the representative words. The candidate words are first selected according to their weights calculated by our new algorithm. Then, the candidates are fed to the WordNet to identify the set of noun words and consolidate the synonymy and hyponymy words. Experimental results have shown that the clustering algorithm is superior to the other subspace clustering algorithms, such as PROCLUS and HARP and kmeans type algorithm, e.g., Bisecting-KMeans. Furthermore, the word extraction method is effective in selection of the words to represent the topics of the clusters.

A 3D Approach for Extraction of the Coronaryartery and Quantification of the Stenosis

Segmentation and quantification of stenosis is an important task in assessing coronary artery disease. One of the main challenges is measuring the real diameter of curved vessels. Moreover, uncertainty in segmentation of different tissues in the narrow vessel is an important issue that affects accuracy. This paper proposes an algorithm to extract coronary arteries and measure the degree of stenosis. Markovian fuzzy clustering method is applied to model uncertainty arises from partial volume effect problem. The algorithm employs: segmentation, centreline extraction, estimation of orthogonal plane to centreline, measurement of the degree of stenosis. To evaluate the accuracy and reproducibility, the approach has been applied to a vascular phantom and the results are compared with real diameter. The results of 10 patient datasets have been visually judged by a qualified radiologist. The results reveal the superiority of the proposed method compared to the Conventional thresholding Method (CTM) on both datasets.

Mathematical Models for Overall Gas Transfer Coefficient Using Different Theories and Evaluating Their Measurement Accuracy

Oxygen transfer, the process by which oxygen is transferred from the gaseous to liquid phase, is a vital part of the waste water treatment process. Because of low solubility of oxygen and consequent low rate of oxygen transfer, sufficient oxygen to meet the requirement of aerobic waste does not enter through normal surface air water interface. Many theories have come up in explaining the mechanism of gas transfer and absorption of non-reacting gases in a liquid, of out of which, Two film theory is important. An exiting mathematical model determines approximate value of Overall Gas Transfer coefficient. The Overall Gas Transfer coefficient, in case of Penetration theory, is 1.13 time more than that obtained in case of Two film theory. The difference is due to the difference in assumptions in the two theories. The paper aims at development of mathematical model which determines the value of Overall Gas Transfer coefficient with greater accuracy than the existing model.

Groundwater Quality Improvement by Using Aeration and Filtration Methods

An experiment was conducted using two aeration methods (water-into-air and air-into-water) and followed by filtration processes using manganese greensand material. The properties of groundwater such as pH, dissolved oxygen, turbidity and heavy metal concentration (iron and manganese) will be assessed. The objectives of this study are i) to determine the effective aeration method and ii) to assess the effectiveness of manganese greensand as filter media in removing iron and manganese concentration in groundwater. Results showed that final pH for all samples after treatment are in range from 7.40 and 8.40. Both aeration methods increased the dissolved oxygen content. Final turbidity for groundwater samples are between 3 NTU to 29 NTU. Only three out of eight samples achieved iron concentration of 0.3mg/L and less and all samples reach manganese concentration of 0.1mg/L and less. Air-into-water aeration method gives higher percentage of iron and manganese removal compare to water-into-air method.

Impact of Foreign Aid and Levels of Education on Democracy in Pakistan

This study examines the relationships between foreign aid, levels of schooling and democracy for Pakistan using the ARDL cointegration approach. The results of study provide strong evidence for fairly robust long run as well as short run relationships among these variables for the period 1973-2008. The results state that foreign aid and primary school enrollments have negative impact on democracy index and high school enrollments have positive impact on democracy index in Pakistan. The study suggests for promotion of education levels and relies on local resources instead of foreign aid for a good quality of political institutions in Pakistan.

Phytoremediation of Wastewater Using Some of Aquatic Macrophytes as Biological Purifiers for Irrigation Purposes

An attempt was made for availability of wastewater reuse/reclamation for irrigation purposes using phytoremediation “the low cost and less technology", using six local aquatic macrophytes “e.g. T. angustifolia, B. maritimus, Ph. australis, A. donax, A. plantago-aquatica and M. longifolia (Linn)" as biological waste purifiers. Outdoor experiments/designs were conducted from May 03, 2007 till October 15, 2008, close to one of the main sewage channels of Sulaimani City/Iraq*. All processes were mainly based on conventional wastewater treatment processes, besides two further modifications were tested, the first was sand filtration pots, implanted by individual species of experimental macrophytes and the second was constructed wetlands implanted by experimental macrophytes all together. Untreated and treated wastewater samples were analyzed for their key physico-chemical properties (only heavy metals Fe, Mn, Zn and Cu with particular reference to removal efficiency by experimental macrophytes are highlighted in this paper). On the other hand, vertical contents of heavy metals were also evaluated from both pots and the cells of constructed wetland. After 135 days, macrophytes were harvested and heavy metals were analyzed in their biomass (roots/shoots) for removal efficiency assessment (i.e. uptake/ bioaccumulation rate). Results showed that; removal efficiency of all studied heavy metals was much higher in T. angustifolia followed by Ph. Australis, B. maritimus and A. donax in triple experiment sand pots. Constructed wetland experiments have revealed that; the more replicated constructed wetland cells the highest heavy metal removal efficiency was indicated.

Blur and Ringing Artifact Measurement in Image Compression using Wavelet Transform

Quality evaluation of an image is an important task in image processing applications. In case of image compression, quality of decompressed image is also the criterion for evaluation of given coding scheme. In the process of compression -decompression various artifacts such as blocking artifacts, blur artifact, ringing or edge artifact are observed. However quantification of these artifacts is a difficult task. We propose here novel method to quantify blur and ringing artifact in an image.

Dichotomous Logistic Regression with Leave-One-Out Validation

In this paper, the concepts of dichotomous logistic regression (DLR) with leave-one-out (L-O-O) were discussed. To illustrate this, the L-O-O was run to determine the importance of the simulation conditions for robust test of spread procedures with good Type I error rates. The resultant model was then evaluated. The discussions included 1) assessment of the accuracy of the model, and 2) parameter estimates. These were presented and illustrated by modeling the relationship between the dichotomous dependent variable (Type I error rates) with a set of independent variables (the simulation conditions). The base SAS software containing PROC LOGISTIC and DATA step functions can be making used to do the DLR analysis.