European Journal of Scientific Research
Volume 110 No 1
A Biological Overview on the Genus Cyclamen
Wissam Mazouz and Samah Djeddi
Cyclamen (Primulaceae) is a genus contains 22 species of perennials growing from tubers. The present bibiographical review summarizes all reports on the botanical data, biological properties, phytochemical composition as well as the pharmacological activities of the Cyclamen species.
Keywords: Cyclamen, botanical data, biological properties, previous research.
Cotton Seed Extract (Gossypium) Promotes Blood Cells Development than Ranferon and Haemoglobin B12
Jimmy E. O, Obillor C. L, A. J. Ekpo, Bala D, Abia. W and Ekwere, E O
Haematinics potentials of cotton seed extract (Gossypium) was investigated in albino rats in comparison with known blood syrup; ranferon and haemoglobin B12 for 28 days. The cotton seed extract increased the haemoglobin levels at low, medium and high dosages than ranferon and haemoglobin B12, P < 0.05. The extract also significantly elevated red blood cells, pack cell volume and mean corpuscular haemoglobin at high dosage, P < 0.05. Also platelet counts were increased at low and high dosage of the extract but lymphocytes were increased at medium dosage, P < 0.05. Monocytes count was increased significantly, P <0.05 at high dosage as compared with control, ranferon and haemoglobin B12. Ranferon syrup elevated platelet counts, neutrophil lymphocytes, monocytes, mean corpuscular volume red blood cells, pack cell volume and haemoglobin significantly, P < 0.01 as compared with control. However, the effect on these blood indices were not effective as compared with the cotton seed extract. Also haemoglobin B12 syrup had similar effects on haematological indices as that of ranferon but not as effective as cotton seed extract. The study has shown that cotton seed extract is more potent than ranferon and haemoglobin B12 syrup and could serve as alternative drug for blood cells development particularly in anaemic situation.
Keywords: Cotton seed extract, ranferon, haemoglobin B12 and blood indices.
The Role of Trust and IT as Supply Chain Antecedents on Supply Chain Agility: Conceptual Framework
Mahdi Mohammad Bagheri, Abu Bakar Abdul Hamid, Nik Naziman AR, Abbas Mardani and Ehsan Kish Hazrate Soltan
Firms must be agile for the reason that being responsive is a crucial competency for them in present global economy. Organizations that are agile happen to be more successful. The agility of an organization is dependent on the agility of its supply chain. The main aim of this paper is to give a new variable in explaining how Trust, Information Technology (IT) and agility can create sustained competitive advantage for firms. Achievement of supply chain agility (SCA) is linked to the organization’s other resources, namely trust and IT. IT is considered as a competitive tool by researchers and practitioners. Therefore, the current paper gives a conceptual framework to ascertain factors which affect SCA. Hence, it is crucial for managers to apply their firms' IT and trust as lower-order organizational capabilities to improve agility as a higher-order organizational capability. The findings of this study will present interesting information and insight about how to improve agility in small and medium-size enterprises. Moreover, the information presented in this study will be the foundation of future supply chain capability studies. To aid the study, Resourced-Based View (RBV) theory has been developed as the framework for the present research. The paper also proposes the framework for future research in empirical investigation in manufacturing.
Keywords: Information Technology (IT), Supply Chain agility (SCA), Competitive Advantage, Resource Based View (RBV).
Regional Flood Modelling for Maximum Annual Flood using Artificial Neural Networks
M. Hedayatizadeh, M.R. Kavianpour and M. Golestani
Flood is one of the well-known facts which endanger the lives and human resources all over the world. Reliable estimations of flood discharge in every region lead to determine the exact size of hydraulic structures and to reduce the risk of their failures. However, the locations of synoptic stations seldom coincide with the site of interest and also the available record may be too short to make meaningful statistical inferences. Therefore, in such situations with the lack of data, regional flood analysis is regarded as a suitable solution for flood estimations. In this paper, artificial neural networks (ANN) are used for flood estimations in such catchments. Different learning algorithms consisting of back propagation and least-squares estimations are used for training systems. The proposed approach has been applied to 19 catchments in the province of Urmia north-east of Iran, and the results have been compared to nonlinear and linear regression approaches. The performance of these approaches was evaluated by using root mean square error and the correlation coefficients. Results indicate that ANN provides much better generalization capability than the regression approaches. Finally, through sensitivity analysis, the effect of each input parameter on outputs was determined to highlight the most effective catchment descriptors in the ANN model.
Keywords: Artificial Neural Networks; Linear Regression Method; Nonlinear Regression Method; Regional Flood Frequency Analysis; Sensitivity Analysis.
Synthesis & Characterization of Fused Rings by The Condensation
Nagham .Mahmood .Al–Jamali
In the present work, The starting materials (diamine compounds such as hydrazine and hydrazine derivatives) react with electrophilic compounds via condensation reaction to give fused rings (five ,six, seven–membered) , which contain dinitrogen atoms (diaze –cycles ) from compounds [1-17]. All proposed structures were supported by spectral methods (FT.IR , H.NMR and (C.H.N)–analysis ) & physical properties like melting points.
Keyword: Fused ring , condensation reaction ,di amines compounds.
An Improved KD-Tree Algorithm Based Community Mining in Social Networks
Renuga Devi. R and M. Hemalatha
The network community mining problem is a challenging problem that was handled by a novel model for characterizing network communities are proposed by introducing a stochastic process on networks and analyzed its dynamics based on the large deviation theory that method called as local mixing (LM) algorithm where it performs Network community mining based on Local Mixing properties but it does not optimize communication performance and there is large complexity of performing the partitioning with a predefined stopping criterion which surmounted using an improved KD-tree with LM algorithm where the KD-Tree with the joint encoding scheme is utilized to reduce the memory limitations with automatic calculation of stopping criterion using the value of Eigen-gap. However, in order to reduce the running time by making algorithm to run faster, we propose an improved KD-tree that simplifies the implementation process with improved performance in two-dimensional spaces. Improved KD-tree apply recursive splitting which result in a minimal hierarchical structure creating n equal child node always from a root making it to converge to the solution faster than the existing KD-tree with Local Mixing Algorithm. The experimental results show that the improved KD-tree method is more effective and scalable reducing memory and time usage than the classically existing KD-tree method.
Keywords: Network Community Mining Problem, Local Mixing, Community Mining, Social Network, Recursive Bisection Strategy, Stopping Criterion, KD-Tree, Community Bipartition Scheme, Eigen-Gap, Eigen Values, Community Structure, Improved KD-tree, and Joint encoding scheme.
Estimation of True Stock Value: A Hybrid McNiven Approach with Predictive Data Mining Concepts
S. Prasanna and D. Ezhilmaran
In financial marketing, picking the right stock to buy or to sell depends on the true value of the stock. Knowing the true stock value is a tough task and it must be effectively calculated for the undervalued stocks. The previous works for calculating the true value of the stocks are based on McNiven’s equation. Though the McNiven’s approach is one of the renowned approach for estimating the true value of the stock, it suffers from the lack of the historic data for the estimation of the true stock value. This proposed methodology makes use of hybrid McNiven’s formula for estimating the true value of the stock by including new rules based on the historical financial ratios of the stock. After calculating the true value of the stock, the stocks that are undervalued, ie the stocks whose values will increase in the near future are selected with a predictive data mining concept. This predictive data mining makes use of the neural network technique to mine the stocks with the help of the hybrid McNiven’s stock value for each stock in the past. The results of this stock selections shows that the stocks selected by the hybrid McNiven’s formula are more effective and reliable than the stocks selected by 3D subspace clustering technique. This helps the investors to select better stocks for their investment and get a better yield than using other stock selection methods.
Keywords: McNiven’s formula, true stock value, data mining, and neural networks.
The Role of 'Circumstances Influencing Fermentation’ in Producing Maximum Pectinase Enzyme
Seifollah Farmohammadi, Javad Kazemzadeh Khoei and Ghanbarov Khodaverdi
Pectinase is the most important synthetic enzyme using in different industries like food and drink Industries, paper and leather and etc industries. This type of enzyme is produced by bacteria, ferment, and fungus, but it is mostly produced by funguses particularly Aspergillus niger. Using carbon resources with low economic value like materials for agriculture industries is the reason for reduction of Pectinase value. In present paper, the optimal circumstances influencing Fermentation to produce maximum pectinase enzymes, Pectinesterase, pectin lyase and endopectin with the purpose of time reduction is using date pomace as substrate. In this paper, a study about production of pectinase enzyme from date pomace using Aspergillus niger in submerging culture has been provided. The impact of fermentation and combination parameters in culture medium for producing pectin lyase using Factorial Survey and Scenario Approach was studied in this paper. The results show that the increase of fermentation time up to 75 hours made the increase of enzyme activity and after this, with increase of fermentation time; the enzyme activity reduces as well. After optimization, maximum enzyme (1.38 U/ml) at 73.93 hours, density of Aluminum Sulphate (0.35%) and PH=4.82. According to the high production of date in the country and high date pomaces, the fermentation methods could be developed for date pomace like organic acids, enzymes, unicellular proteins which this is economic beneficial.
Keywords: Pectinase enzymes, Pectinesterase, pectin lyase, endopectin, Fermentation.
Constrains of Solar Energy Applying in Rural Area Constraints in Application of Solar Energy in Rural Areas of Iran
Serveh Ahmadi, S. Jamal F. Hosseini, S. Mehdi Mirdamadi, Morteza Almasi and Farhad Lashgar Ara
The purpose of this study is to examine the constraints in application of solar energy in rural areas of Iran. The population includes 90 experts in charge of providing services in application of solar system are in rural areas. The main instrument was questionnaire and its validity was confirmed by the expert panel and the reliability was determined by using Cronbach alpha (a=86%). The results of factorial analysis show that six factors named human, administrative, educational, economic, environmental and extensional constraints influence in application of solar energy, respectively.
Keywords: Solar Energy ? Application, Factor Analysis of Constrains, Service Provider Experts in Solar System
Crosstalk Reduction using Bus Encoding in RLC Modeled Interconnects
S. K. Verma and B. K. Kaushik
In current nanoscale technology, crosstalk (voltage glitch, undesirable noise, etc) is a major deterrent for high performance RLC modelled VLSI interconnects. This research paper primarily proposes two novel encoding methods (I and II) for RLC modelled interconnects to reduce the effect of crosstalk and simultaneous switching noise. The proposed encoding methods are able to evade the worst case crosstalks. The encoding method I identifies the severe crosstalks, i.e., Type-0 and Type-1 in the inverted and non-inverted forms of incoming data with respect to the previous data. The data having minimum crosstalk among the inverted and non-inverted forms are only sent through transmission line. The encoding method I removes the worst case crosstalk and simultaneously reduces other mild crosstalks. The removal of worst case crosstalk improves the overall performance of interconnect. The encoding method II identifies Type-2 crosstalk along with Type-0 and Type-1 similar to encoding method I. Furthermore, the encoding method II, exhibits the improvement over method I in terms of reduction in crosstalk.
Keywords: VLSI; RLC Interconnects; Encoding Method; Bus Invert; Crosstalk.
A Model for ERP Pre-implementation Stage A Case Study of Bandar Abbas Oil Refining Company
Rohallah Shokri, Javad Pirmoradian, Hassan Soltani and Nasrin Pirmoradian
In this study a model for the study of pre-implementation of ERP system is presented. Pre-implementation of ERP system entails time and high cost with deep effects on organization. Therefore, technical, economic, and operational feasibility of the project are first performed on the basis of a hierarchical model by the proposed model and then, if the results are satisfactory, readiness assessment of the organization is carried out. In order to assess the readiness of the organization, different factors effective on the implementation of the system are specified and then, by the use of ANP (analytic network process) method they are weighed. The results of the readiness assessment show in what areas the organization needs to enhance its readiness level. The proposed model was executed at Bandar Abbas Oil Refining Company and the studies showed it was technically, economically, and operationally relatively positive, but the readiness of the organization for the implementation of ERP system was below average.
Keywords: Feasibility study, Organization resource planning, Readiness assessment, Analytic network process.
Etude de la Prévalence et des Facteurs de Risque Liés Aux Mammites Subcliniques en Élevages Ovins Dans L’est Algérien
La mammite subclinique continue d'être la maladie la plus onéreuse économiquement des ovins laitiers en Algérie, ce d’autant plus que les données actuelles sont insuffisantes. Pour enquêter sur la prévalence de cette pathologie infectieuse chez les ovins dans l’Est algérien, des échantillons de lait de quartier, de 214 brebis en lactation de race: Ouled Djellel, dans 34 élevages, ont été testés par le CMT; qui a été appliqué à la ferme, après nettoyage de la mamelle et expulsion des premiers jets de lait.
L’expression du taux de positivité du test de CMT est illustrée par un pourcentage de 23.36%, ce qui signifie que 50 brebis ont un problème de mammite subclinique.
On peut conclut que les mammites subcliniques posent des problèmes sérieux de santé aussi bien pour les brebis que l’être humaine, et que les conditions d’hygiène et la mauvaise conduite du troupeau ont constitué les probables facteurs de risque.
Motsclés: La Prévalence, Mammite Subclinique, Facteurs A Risque, Ovins.
Behaviour of Reinforced Concrete Beams with Duct Openings Strengthened by Steel Plates
J. Suresh and R. Angeline Prabhavathy
In reinforced concrete beams, openings are often provided in practice to accommodate service pipes and ducts. This eliminates a significant amount of dead space. Due to provision of openings in web, the load carrying capacity and shear capacity reduces and local cracking appears around the openings and reduces the stiffness of the beam. This paper discusses the behaviour of reinforced concrete beams containing openings strengthened by steel plates. Out of the nine specimens tested, one specimen was cast without openings, four specimens were cast with square and rectangular openings of different sizes in the shear zone and four specimens with openings strengthened using steel plates. Solid beam without opening was considered as the control beam. The behaviour of reinforced concrete beams with and without openings at ultimate load, the deflection and cracking patterns were investigated. The presence of duct openings in the shear zone reduces the load carrying capacity by 55 to 70 % for the beams with openings. Experimental results shows that strengthening the duct openings with steel plates of 4mm thickness increases the load carrying capacity, shear strength and the ductility characteristics of the beam. Crack formation was delayed in the case of beam strengthened using steel plates.
Keywords: Beams with openings, Steel Plates, Ultimate Strength, Duct openings.
Measuring Trust Semantically for Smartphone-Applications' Providers
Smartphone-Applications nowadays are a critical factor to their success. Making sure that a specific information, service or product from an online provider is reliable and trustworthy may sometimes be a difficult task. The World Wide Web (WWW) is an open environment in which every person is allowed to populate some information. The accuracy or reliability of such information, to some extent, is unknown, and therefore cannot be trusted. In this paper, we argued that using ontologies may form a useful tool to find the best Smartphone-applications provider. The contribution of this paper is to develop ontology concepts for measuring such "goodness". Common and frequent concepts from five popular and trusted online Smartphone-applications providers were extracted, refined, and then checked against nine other online providers. These providers are also judged by experts who are Smartphone-applications specialists. The results discussed in this paper have shown that the proposed approach has achieved high matching score to the experts' judgments.
Keywords: Semantic Web; Ontology; Credibility; Smartphone-applications; Trust.
Ontology Evaluation for Software Components
The emerging of semantic web creates a large number of ontologies which creates the need for new techniques to evaluate the quality of ontology. Ontology evaluation is essential part for building semantic-web based systems. The evaluation process involves many parameters; this paper discusses some of these issues mainly: the effect of threshold, number of concepts and relationships on the quality of ontology. This paper uses the fitting (coverage) methodology; Java and .Net components; F-Measure; some statistical tests; WordNet relationships; and KAON tools. The worst (minimum) and the average thresholds have been defined using F-measure and four statistical tests. The results are very interesting and sometime controversial. The results show that, unexpectedly, using relationships might not improve the coverage results for ontology. The paper demonstrates our experience in building and evaluating ontologies in the domain of Java and .Net ontologies. This paper summarizers these parameters and contributes in answering some questions to evaluate ontologies in software components. It answers questions such as: Which measure to use, how to apply the recall and precision measures in ontology evaluation, what is the best statistical test to compare two ontologies, what is the acceptable/unacceptable threshold for each test, what is the optimal number of concepts in an ontology, how much does each concept contribute in enhancing the ontology, the benefit of using WordNet relationships, what is the needed frequencies to build good ontology, and the needed samples size to conduct such experiments.
Indexterms: Semantic Web, Ontology evaluation, Statistical methods, and Software Components.