European Journal of Scientific Research

Volume 141 No 4
September, 2016

Synthesis and Evaluation Antimicrobial Activity of some new Tetrazoline, Triazole and Triazoline Derivatives From Isatin
Suaad, M. H. Al-Majidi, Sameran, A. Khalaf
This research of some new different heterocyclic derivative of isatin compound. New 1,2,3,4-tetrazoline, 1,2,3-triazol and 1,2,3-triazoline derivatives of isatin which were prepared by condensation isatin with 2-amino pyridine in presence of glacial acetic acid and absolute ethanol as solvent to obtained Schiff bases of isatin 3-(imino pyridine)-1H-indole-2-one(1). The product was treated with sodium hydride in DMF at 0°C to give suspension of the sodium salt of isatin derivative and subsequent reaction with chloro acetyl chloride to obtain, 1-(α-chloroacetyl-)-3-(pyridine -2-yl imino) – indole -2-one (2). When reaction compound (2) with sodium azide to yield 2-(azido acetyl )-3-(pyridine-2-ylimino)-indole-2-one (3).The condensation reaction of substituted primary aromatic amine with different aromatic aldehyde in absolute ethanol give Schiff bases (4-10). Compound (3) react by two ways. The first with Schiff bases compound to obtain 1,2,3,4-tetrazoline derivatives (11-17) while the second way entered in 1,3-dipolar cyclo addition reaction with some of α-β-unsaturated carbonyl compounds to obtain derivatives of 1,2,3-triazoline (18-24) and triazole (25-27) respectively. Newly synthesized compounds were identified by spectral methods. (FTIR, 1H-NMR, 13C-NMR) and measurement of some of its physical properties and also some specific reaction. Furthermore the effects of the synthesized compounds were studied on some strains of bacteria and yeast.
Keywords: Isatin, Schiff base, 1,2,3,4-Tetrazoline, 1,2,3-Triazoline, 1,2,3-Triazole, antimicrobial.

A Framework for Distributed Data Mining of Big Data through Machine Learning
Saif Khalid Musluh
Machine learning applications have been around for many years. However, machine learning approaches on big data is relatively new phenomena. Big data processing needs to be done in a distributed environment where thousands of nodes work together along with data centres, cloud computing resources and distributed file systems. Hadoop is one such example for distributed programming framework. The programming approach used in such environment is known as MapReduce which is best used to let multiple nodes participate in processing given job. It exploits the power of GPU and supports parallel processing of data. The existing machine learning algorithms focused processing huge amount of data. However, there needs to be a framework that can improve the support for big data processing using machine learning algorithms. In this paper we proposed and implemented a framework that can support information retrieval and natural language processing. The framework takes big data as input and provides simulated environment demonstrating the functionalities of mapper and reducer. We built a prototype application that demonstrates the proof of concept. The empirical results revealed that the framework supports distributed data mining of big data through machine learning. However it is in its primitive stage and needs enhancement to be more useful in future.
Keywords: Big data, distributed programming framework, MapReduce, machine learning

Effect of Initial Temperature on (Methanol-O2-N2) Flame Using Combustion Bomb Method
Fouad A. Saleh
The double effect of oxygen enrichment and initial temperature of mixture on the laminar burning velocity of methanol premixed flame was studied in this paper. The measurement system is designed to measure the laminar flame speed using a combustion bomb method and thermocouple. The laminar flame speed results were obtained at atmospheric pressure, initial temperature (298,320,350 and 373)K, oxygen concentration (0.21, 0.23 , 0.25and 0.27) and the range of equivalence ratio ( 0.8 – 1.2 ). All the measurements were carried out at pre-pressure period to use “density ratio method” for the calculation of laminar burning velocity.
Validation of experimental work is approved by comparison measured values of laminar burning velocity for (methanol – air) mixtures with the available published data. Good agreements are obtained in its comparison with the literature results employed in the present work are successful and precise.
Keywords: Oxygen enrichment, initial temperature, laminar burning velocity, combustion bomb method

Lossless Image Compression using Non Decimated or Stationary Wavelet Transforms and Delta Encoding
Hend A. Elsayed, Hasanain F. Hashim, and Shawkat K. Guirguis
In this paper, we proposed an effective system for lossless image compression using different wavelet transform such as the stationary wavelet transform, the non decimated wavelet transform, and discrete wavelet transform with delta encoding and compare the results without delta encoding. With the development in the field of networking in the process of sending and receiving files needed to effective techniques for image compression as the raw images required large amounts of disk space to defect during transportation and storage operations. We used lossless compression to maintain the original features of the image in this process; there is a major problem which often is low compression ratios. We also use three types of wavelet transform which are discrete wavelet transform, non decimated wavelet transform, and stationary wavelet transform to demonstrate the effectiveness of the proposed system for comparison and to show the differences between each type to overcome previous challenges. This paper proposed a system for lossless image compression based on the use of the three types of wavelet transforms using Arithmetic coding and Huffman coding with delta coding, which helps in the high compression ratio to clarify the extent of the difference and distinction between each type. The results show that the stationary wavelet transform outperforms the non decimated wavelet transform and the discrete wavelet transform and with delta encoding outperforms without delta encoding. The arithmetic coding outperforms the huffman coding.
Keywords: Lossless Image Compression; Stationary Wavelet Transform; Non Decimated Wavelet Transform; Discrete Wavelet Transform; Delta Encoding

Neurofinance: A Systematic Review about A New Way to Looking the Financial Decision-Making
David Ascher, Wesley Vieira Da Silva, Claudimar Pereira Da Veiga, Alceu Souza
This research aims to investigate a new approach of financial decision-making so-called “Neurofinance” which comes recently to the center of the many discussions as a new way to scholars in management and accounting analyze more consistently some factors that affect the financial decision-making. One of the main objectives of this paper is the development of a systematic review adopted from Mousnad et al. (2014) by a search of neurofinance papers in order to organize the ideas, methodologies, processes, and main issues addressed to this subject. The results showed a relevant number of articles, which made direct contributions to the topic. The authors’ network shows a scattering of the writers and only three of them has more than two public works regarding this topic. After a review of all articles, it is concluded that the debate on neurofinance is still in the embryonal stage, but their findings are getting attention from research centers around the world. Finally, the present paper is important not only for the value of this systematic review, but also to become a guide to assist scholars interested in deep diving in neurofinance, by promoting a broader overview about what has been studied within this emerging field of finance, serving as a theoretical summary, including advantages and disadvantages to start studies of neurofinance.
Keywords: Bounded rationality; Neuroeconomics; Behavioral Finance; Cognitive Neuroscience; Systematic Review

Assessment of Groundwater Quality Using GIS and Various Water Quality Indices: A Case Study of the Shekhawati Region of Rajasthan, Northwest India
R. Gupta, A. Singhal and A. N. Singh
Assessment of Groundwater quality using Water Quality Index (WQI) and Geographic Information System (GIS) was carried out in the Shekhawati region of Rajasthan. The results of 15 physico-chemical parameters were used for the calculation of WQI. The results indicated that WQI values range from 0 to 1304 and 0-11,701 for two different approaches used and thus indicates very poor groundwater quality status in the region. The Fuzzy method as a third approach was also used to generate a WQI and resulted in only 2 values. The geographical information system using the Inverse Distance Weighted method (IDW) delineated groundwater quality zones into good to very poor potential areas. The hierarchal cluster analysis identified anthropogenic contamination, natural mineralization, reverse cation exchange as the major processes controlling groundwater chemistry. From the correlation matrix, it could be said that Turbidity, Total Hardness as CaCO3, Ca hardness as CaCO3, Mg hardness as CaCO3, Chlorides as Cl-, Fluorides as F- and TDS are responsible for high WQI values in the region.
Keywords: WQI, GIS, Dendrogram, Anthropogenic Contamination, Natural Mineralization

Hemisphericity (Right, Left and Integrated) As A Predictor of Reaction Time
Suliman Saleh A. Aljomaa and Ahmad M.A. Alghraibeh
The study aimed to explore the predictable correlation between hemisphericity (right, left and integrated) and reaction time. Two instruments were utilized—the reaction time machine and the hemisphericity scale. Instruments’ validity and reliability were insured. Fifty-four students were randomly assigned to participate in the study; their age mean was 21.4 years. Results proved that was significant differences were found between left hemisphere and both the right hemisphere and the integrated brain in favor of the left hemisphere; a correlation was found between hearing reaction time and both the left hemisphere and the integrated brain. A statistical effect was found on the left hemisphere, the integrated brain on hearing reaction time.
Keywords: left hemisphere, right hemisphere, the integrated brain, reaction time.

Placental Abruption: Epidemiological, Clinical and Therapeutic Aspects at the University Hospital of Brazzaville
Mbongo JA, Mahoungou JD, Aloumba G, Iloki LH
Objective: To describe the epidemiological and clinical aspects and the prognosis of the placental abruption and to permit its management and improved outcomes.
Methods: a retrospective and descriptive study conducted over a period of 12 months in the department of Obstetrics and Gynecology of the University Hospital of Brazzaville.
Results: hospital frequency of placental abruption was 0.45% (35 in 7705 deliveries). The age of the parturient ranged between 17 to 40 years with a mean of 30 years. Most of them were multigravida in 71.4% (25 in 35 of cases) and pauciparous in 62.8% (22 in 35 of cases). On admission, 23 patients (65.7%) were classified as Grade III, 10 (28.6%) as Grade II and 2 (5.7%) as Grade I using SHER classification. The macromolecules infusion was administered in all cases. The caesarean section was the most used mode of delivery in 74.3% (26 in 35 of cases) and blood transfusion was performed in 17.1% (6 in 35 cases). Maternal prognosis was satisfactory in 77.1% (27 in 35 cases); a residual anemia was observed in 74.3% (26 in 35 cases) postnatally. Fetal outcome was fatal; live births were noted in 34.2% (12 in 35 of cases), fresh still births in 65.7% (23 in 35 of cases), and prematurity in 57.1% (20 in 35 of cases).
Conclusion: The fetal prognosis remains poor; its improvement requires the eviction of the extent of the placental disruption by medical consultation and early management.
Keywords: placental abruption

An efficient Multimodal Biometric System Using Adaptive Gabor Filtering based Feature Extraction
D. Gayathri, R. Uma Rani
Multimodal Biometric system making a personal identification by integrating multiple biometrics. The features extracted from the biometrics are fused either at feature level, score level or decision level for recognizing the patterns. The feature level fusion is focused in this paper. From the literature it is studied that the Gabor filter based feature extraction achieves better classification accuracy for multimodal biometric systems. Further log-Gabor filter outperforms the conventional Gabor filter based feature extraction. However, it is challenging to choose the appropriate number of scales and orientation for the construction of such filter banks, which affects the classification performance. In this paper an efficient Gabor filter is proposed to choose the orientations adaptively, the same has been applied with log-Gabor filter also. Experiments are conducted with face and fingerprint biometrics, and the performance of the proposed system is analysed and compared with the conventional Gabor and log-Gabor filters.

Effect of Fly Ash Concentration on Wear Behavior of Cotton Fiber Polyester Composites and Predicting Dry Sliding Wear Behavior Using Response Surface Method
Hiral H. Parikh, Piyush P. Gohil
This present article describes the effect of thermal power station waster like Fly Ash on the wear response of cotton fiber reinforced polyester composites. The untreated cotton fibers were taken for the wear studies as reinforcement along with polyester resin and Fly Ash fillers. Fly Ash, polyester and cotton fiber of different weight proportions were taken for the study. Hand lay-up compression molding technique has been used for preparing the specimens. Tribo studies were carried out by using a pin on disc wear tester for the specimens prepared as per ASTM G99 standard. Response surface Box Behnken design approach is used to create designs of experiments. Response surface methodology (RSM) has been used to enumerate the relationship between the input parameters and output parameters. Minitab software was used for design of experiments. Regression models for different materials were obtained and its competence was verified. Further the models were validated by performing validation experiments. The validation results show that experimental outputs are in a good match with the predicted values. Using Minitab, 3D surface plots were produced for wear response. These plots give an idea about the influenced process variable, and also show the variable interaction effect on the response.
This work has importance in the sense of utilizing a thermal power station waster like Fly Ash for the composite making purpose with good wear strength, minimum number of design experiments and reliable regression model to predict the wear.
Keywords: Wear; Tribology; Composites; Pin on disc; RSM; Box Behnken