IMPACT : International Journal of Research in Engineering & Technology

9-14

Authors: Venkata Rohit Gandikota & A. Mary Sowjanya

With the advent of powerful computing machines and advances in technology, more and more machines are being used on a daily basis. With the increase in the infrastructure, monitoring of said infrastructure has been playing a key role in keeping the working of an organization streamlined and efficient. While modern machines are more than capable of running for days together without the risk of failing, there can be no shortcuts when coming to infrastructure as any of the machines can go down without warning if not properly looked after. This can cause delays which can sometimes extend to days or even months if not attended to immediately. However, the major gripe with the existing manual system is that problem identification has become a roadblock and also there are no ways to predict a failure of a system in advance. A person is always required to constantly keep looking at a screen in order to see if alerts are generated and when indeed they are, if that person is missing from his station then there will be a delay as to when the alert is generated and when it is actually notified to the concerned team. This human involvement becomes time-consuming as the alerts may or may not be generated. Since there is not a lot of work involved and the skills of the person can be put to better use at a different place. The aim of this work is to eliminate the human factor involved by automating the monitoring of infrastructure with the help of software tools and also integrate the alert generation and notification process by using machine learning algorithms and natural language processing. The monitoring tool can be configured according to the needs of the company and the generated alerts can be sent to the concerned team immediately without any delay. As the tool displays real-time data we can predict which system needs to be taken care of immediately and which machine is likely to go down in the future.

19-30

Authors: Saleh H. Al-Sharidi, Husin Sitepu & Noktan M. AlYami

The World Health Organization has raised concerns about the accidental fuel leakage during storage and transportation and, therefore extensive methyl tertiary butyl ether (MTBE) use has led to cases of natural water contamination [1-9]. This article describes the (i) visible light reaction condition for MTBE, (ii) solid-phase microextraction (SPME) technique incorporated with gas chromatography-mass spectrometry (GC-MS) to assist the MTBE photo-oxidation process, (iii) catalyst syntheses from different concentration of Ru in tungsten oxide (WO3), nano-WO3, Pt in nano-WO3, and (iv) formation of byproducts during photocatalytic degradation of MTBE by using the GC-MS [10-15]. The experimental results indicated that the MTBE removal can quickly and accurately be achieved in presence of Pt-loaded nanostructured WO3 under visible light radiation, i.e., 96-99% removal between 2.5 hours and 3 hours. The Pt/WO3 nano-composite showed much better photocatalytic MTBE removal than those of the Ru/WO3 and pure nanostructured and micron-sized WO3 [10]. Additionally, the by-products formation during photocatalytic degradation of MTBE obtained from GC-MS revealed that the degradation of MTBE proceeds essentially via formation of formic acid and 1, 1-dimethyl ethyl ester before its complete degradation [10].

39-56

Authors: Mohamed El-Wakeel, Said Abdelkader & Ahmed Kassar

During the end of the last century, marine accidents triggered the maritime community to apply and develop the international regulations for safety and environmental protection. Consequently, Port State Control (PSC) regulations were introduced as a new mechanism to enforce the implementation of such regulations, which aim to exclude the substandard ships from the seaborne fleet and ensure ships safety and reliability in clean seas. However, PSC of a port cannot inspect every ship calling at the port at any time; and a selecting ship for inspection system should be adopted due to time and resource limitations. Two Multi-Criteria Decision Making (MCDM)approaches were first used to rank the alternatives; these approaches are the Weighted Sum Model (WSM) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS).In this endeavor, ships to be inspected represent the alternatives and targeting factors represent the attributes; initial results are in favor of TOPSIS.

7-12

Authors: Jai Prakash Nayak

The present study was envisaged to estimate low flow characterization of Satluj River. For the present study, Satluj river basin uptoKasol gauging site has been considered and the low flow characterization has been done at three locations viz. Rampur, Suni, and Kasol. The daily discharges of Satluj River at these sites for the years 1964-2011 were used for low flow characterization. The flow characteristics related to low flow domain estimated in the present study were MAR, AMF, Q20, Q50, Q90,Q20/Q90,Q50/Q90, and Q90/Q50. Mean annual runoff of Satluj river varies from 10,606.43 MCM (Rampur) to 13,192.72 MCM (Kasol); Absolute minimum flow from 44.18 cumecs (Rampur) to 73.05 cumecs (Kasol); Q20 from 625.75 cumecs (Rampur) to 826.55 cumecs (Kasol), Q50 from 167.25 cumecs (Rampur) to 206.14 cumecs (Kasol), Q90 from 84.60 cumecs (Rampur) to 98.34 cumecs (Kasol), Q20/Q90 from 7.39 (Rampur) to 8.41 (Kasol), Q50/Q90 from 1.98 (Rampur) to 2.10 (Kasol), and Q90/Q50 from 0.47 (Kasol) to 0.51 (Rampur) respectively. MAM10 value of Satluj River varies from 80.67 cumecs (Rampur) to 92.30 cumecs (Kasol); 10Q2 varies from 78.45 cumecs (Rampur) to 89.91 cumecs (Kasol) and 10Q10 varies from 102 cumecs (Rampur) to 112.46 cumecs (Kasol). Similarly, for average weekly flow, minimum 7-day average flow (MAM 7) varies from 79.02 cumecs (Rampur) to 91.10 cumecs (Kasol); 7Q2 varies from 78.05 cumecs (Rampur) to 89.11 cumecs (Kasol) and 7Q10 varies from100.1 cumecs (Rampur) to 109.63 cumecs (Kasol) respectively. All these values are a very good indicator of aquatic habitat for various species during different growth stages and environmental flows globally are used for recommending.

9-20

Authors: A. Sugumaran & P. Kasirajan

A proper coloring of a graph = ( , ) is a mapping : → {1,2,3, …}such that if = , then ( ) ≠ ( ). A graph G is said to admit star – in – coloring if it satisfies the following conditions. • No path of length three( ) is bicolored. • If any path of length two ( ) with end vertices are of the same color, then the edges of are directed towards the middle vertex. In this paper, we have proved that the splitting graph of fan graph, the splitting graph of double fan graph, Cartesian product of path and fan graph, Cartesian product of path and double fan graph, tensor product of path and fan graph, tensor product of path and double fan graph and Cartesian product of and the path graph is star – in – coloring graphs. In addition, we have given the general pattern of colors for all these graphs and their star – in – chromatic number.

15-26

Authors: Paul Nyagorme

This study has been reported on the extent to which Distance Learners are ready to take up the deployment of eLearning as an alternative mode to the fortnightly face to face sessions organized at the various study centres across the Country, Ghana. Specifically, this study sought to predict the rate of eLearning utilization taking into consideration determinants such as eLearning perceived usefulness, self-efficacy, and attitude of Distance Learners. The theory guiding this study was the Theory of Reasoned Action (TRA). According to Fishbein and Ajzen (1980), people behave in a certain direction, if they perceived that the outcome of the antecedent behavior will be beneficial to them. In this context, this study hypothesized that UCC Distance students will tend to use eLearning if they perceived usage to be beneficial to them. Three sets of questionnaires, with Cronbath’s Alpha reliability coefficients above 0.70, were used to collect data. Statistical Package for Social Sciences (SPSS) was used to analyze the data collected from 472 distance students of the University of Cape Coast. Regression and one way anova statistical tools were used to test the hypotheses. The results of the study indicated that there are regional differences shown by UCC distance students in relation to how they perceived the usefulness of eLearning, their self-efficacy and attitude towards eLearning. This study also revealed that the University of Cape Coast, distance students’ use of eLearning is not dependent on how they perceived eLearning to be useful. Again the study found that distance students’ use of eLearning cannot be predicted by their attitude towards eLearning. Rather, Distance learners’ perceived eLearning self-efficacy is a major predictor of eLearning usage at the College of Distance Education, university of Cape Coast. This study, therefore recommends that ICT- based training programmers should be periodically organized for the distance students, which should take cognizance of the regional differences established by this study.

33-40

Authors: Adeoye, A. O, Adewoyin, A. G& Akande E.A

Locust beans have been utilized as condiment (seasoning agent, flavor enhancer) from time immemorial. It is produced locally and so can be purchased in the local market all over Nigeria. The local processing operation which does not have standard control procedure has been known to attract various hazards which can affect its qualities. As a result, microbiological study of each unit operation is necessary to assess the hazard points and possible attention and remedy. Samples of the locust beans were collected at each of the processing steps of the unit operation. The bacterial populations of the samples were estimated using pour plate technique, identification of the bacterial isolate by standard microbiological methods (disc agar diffusion method). Characterization of bacteria isolates were based on gram staining, morphological, cultural characteristics and biochemical test. The antibiotic susceptibility profile of the isolate was also determined. The bacterial load obtained ranges from 0.50 TVC X 108 to 32.0 TVC X 108. The number of distinct colonies obtained per plate ranges from 2.0 to 5.0 colonies. The Statistical analysis showed that Staphylococcus aureus and Bacillus cereus have the highest frequency of occurrence (19.40 %), Pseudomonas auraginosa and staphylococcus epidermis have the lowest occurrence (4.48 %). Bacterial isolated include Staphilococcus aureus, Staphylococcus epidermis, Bacillus subtilis, E. coli. Among the organisms isolated Staphylococcus aureous, Bacillus subtilis, Clostridium spp, Bacillus cereus and Pseudomonas aeuraginosa showed multiple Antibiotic Resistance. The percentage MAR ranges between 22-44 %. This study showed that there is a need for improvement in the processing methods starting from the collection of seeds on the farm to the final product.