VOLUME 5, ISSUE 2, FEBRUARY 2018

Abstract: Drilling operations is the only proven method to extract the oil and gain the profit, during the last decade the oil price decreases, which led to reduce the capital investments, reduces expenses and lied off huge number of expertise in all oil and gas sectors. Ended with reducing the level of competency of most of oil and gas companies. Performance optimization is a key for all companies to evaluate their work plan, magnitude budget and to have more control in oil well expenditures AFE to reduce the overall cost. Strategic planning cannot be effective without strong database for any historical work, successful business-planning team has to collect the assets requirements evaluated and allocate the required resources to complete the assigned tasks. One of the most important operations that require extensive planning in all oil and gas companies is drilling operations, where huge resources are required such as rigs, cementing, bits, mud, directional etc. When the oil and gas crises are resolved, prices increased. Oil and gas companies started to resume drilling activities and maximize their business plan. One of the drilling projects in one of leading companies in the Middle East had been selected to implement new performance methodology to check the method effectiveness. The aim of this study is to provide drilling team with clear and effective methodology and process to improve drilling performance and set up benchmarking process. Share project results to be implemented with other projects. This paper represents one of success case history for a unique performance optimization methodology and well- structured process, resulted in significant cost saving exceed 3.4 MM$. This technique will reduce the number of rigs required per project and save significant number of days. If similar performance is extrapolated to 6 rigs for a period of one year, the potential value addition of USD 26 MM will be achieved. Such performance projects can be initiated across all the assets of any company in the project-planning phase creating a huge and consistent impact on the number of wells drilled per year.

Keywords: AFE, NPT, Bit, BHA

Abstract: Austenitic stainless steel (German and USA (AISI) designations respectively X2CrNiMo18-14-3 and 316L) was studied in stress controlled tests on the high cycle fatigue (HCF) regime in air at room temperature. Stress-strain responses were carefully measured to clarify the stress amplitude dependent fatigue behaviour of this steel. The fatigue tests were performed at constant-amplitude cyclic loading with load ratio of R=-1. Results showed that the fatigue limit of AISI 316L stainless steel at room temperature was 190-200 MPa.

Keywords: Fatigue strength, stainless steel, HCF.

Abstract: Monogeneans are ubiquitous, less understood parasite in context of aquaculture practices which generate a potentially stressful environment to the cultured animals, with the possible suppression of the immune system, rendering the fish more susceptible to different infectious diseases. Among the different parasites, monogenean ectoparasites are known to parasitize a large number of fish. Fish hosts susceptible to a certain parasite show an ability to mount a protective response after infection. The innate host factors like complement, lectins, acute phase reactants, macrophages are reported to bind monogeneans and elicit severe damage to the parasites by targeting the monogenean tegument, gastro-dermis and glands. Increase in the host's production of adaptive and non-adaptive factors following monogenean infections of certain duration explains the acquired response. However, clever skill of the monogenean to avoid and even exploit the wide array of immunological elements of the host poses an interesting event in the dynamic interactions between host and monogenean. Understanding of diverse monogenean morphology in context of its life-cycle and host interaction may give clue to avoid negative impact of this parasite.

Keywords: Monogenean, Aquaculture, Morphology, Immune response

Abstract: Cost estimating is one of the most important and challenging activities during project planning, which occurs at the early stages of a project life where limited information is available and many unknown factors affecting the project costs. ANN is a new advent that is used in cost estimation, which is able to lucubrate from experience and examples and deal with non-linear problems. It can perform tasks involving deficient data sets, fuzzy or insufficient information and for highly complex problems. The objective of this study is to review cost estimation models which used Artificial Neural Network (ANN) tool and to suggest the most effectual algorithm for cost prediction and the factors predominantly affecting the total construction costs of building projects. To build CEM, the most effective factors affecting cost in construction projects were identified based on a comprehensive survey among a collected sample of construction relevant model studies. The developed neural network model examines the data set into distinct cases classified on the basis of hidden layers. Each of them containing the independent input neurons, hidden layers and a dependent output neuron. The results of the trained models indicated that neural network reasonably succeeded in estimating the Total construction cost of building projects at the planning stage itself. The average error of test dataset for the adapted model was largely acceptable and can perform as a good indicator regarding the ability of the proposed model to predict the total construction cost of any future construction project at an appreciated degree of accuracy. This paper gives a clear review of implementing the ANN tool in prediction of total cost of building construction projects and the relevant factors affecting it.

Keywords: Artificial Neural Network (ANN), Cost Estimation Model (CEM), effective algorithm, prediction.

Abstract: Most of the civil engineering constructions are going-on by using conventional materials such as sand, other natural minerals and metals etc. But the availability of these materials is limited since the production due to natural cycle is slow. Thus, there is need of material that can replace such conventional material. Blast furnace slag is one of such material which can replace the conventional materials. In this present experiment, the study related to the Blast Furnace Slag (BFS) and plastic waste bottles used in civil engineering works as a way to minimize their disposal and in the direction of sustainable development. The sample was prepared by using Blast Furnace Slag (BFS) and plastic strips cut manually from used and waste plastic water bottles with four different Aspect Ratios (AR) 1, 2, 3 and 4. The experiments were conducted with the different mix ratio percentages 1, 2 and 3. The plastic strips of different aspect ratios 1, 2, 3 and 4 were added with different mix ratios 1%, 2% and 3% with respect to weight of blast furnace slag. Series of un-drained un-consolidate triaxial tests for cell pressure 100 kPa, 200 kPa and 300 kPa were performed on reinforced blast furnace slag. From the test results we observed that deviator stress increases with increase in aspect ratios and mix ratios. Also the shear strength parameters were found to be influenced with the change in aspect ratios and mix ratios.

Keywords: Blast furnace slag, Plastic strips, triaxial tests, aspect ratios, mix ratios, deviator stress.

Abstract: In the performance analysis of production systems by using the traditional methods of engineering the knowledge of machine reliability factors is assumed to be precisely known. The current study entitled performance evaluation of food industry in India. To analyze and determine the availability of plant a case study has been undertaken from Moga Nestle food private limited industry in India. Various studies evaluating the performance of automated production systems with the help of modeling and simulation and analytical methods have always given priority to steady state performance as compared to transient performance. Production systems in which such kind of situations arises include systems with dysfunctional states and deadlocks, not stable queueing systems. This research work presents an approach for analyzing the performance of unreliable manufacturing systems that take care of uncertain machine factor estimates. The method that is being proposed is on the basis of Markov chain and probability density function discretization techniques for studying manufacture lines consist unreliable machines. To determine the performance of plant, important information has been collected from different systems and subsystems to find out long run availability of whole system.

Keywords: Maintenance policy, Maintenance, Reliability, Replacement, Optimization.

Abstract: It is very important to extract the right features from transactional data in implementing a credit card fraud detection model. It is normally done by combining the transactions in order to observe the spending patterns of the customers. We propose to create a new set of features based on analyzing the periodic behavior of the time of a transaction using the von Mises distribution in this paper. We compare credit card fraud detection models, and evaluate how the different sets of features have an impact on the results with the help of a real credit card fraud dataset provided by a large European card processing company. The results show an average increase in savings of 13% by including the proposed periodic features into the methods. The methodology proposed in this paper is currently being incorporated into the fraud detection system of aforementioned card processing company.

Keywords: Cost sensitive learning; Fraud detection; von Mises distribution.

Abstract: In the construction industry, project time & project cost are given upmost priority. But since there are innumerable uncertainties involved in construction, delays in project completion are fairly common which lead to an increase in project's total cost. Thus project time crashing plays an important role in project management determining which activities duration to crash to complete the project in the stipulated time. But crashing the duration will mean adding more resources which will lead to an increased additional cost of the project. Thus, the paper deals with determining how to crash the project duration so as to complete the project at the earliest with minimum added cost obtaining a Time-Cost Trade-off for the project. Therefore for reducing total project time at the least added total cost and crashing the duration of an actual residential building construction by using primavera to schedule the project with CPM crashed using the Solver add-in of Microsoft Excel.

Keywords: Project management, project crashing, Excel Solver, Critical path method.

Abstract: High-Pressure Processing (HPP) is for the seafood industry a relatively young technology that successfully evolved into one of the most engaging alternatives to conventional thermal processing. HPP has been widely applied to prolong shelf life of predominantly additive-free foods. At refrigeration, ambient or moderate heating temperature HPP inactivates pathogenic and spoilage microorganisms in foods, with fewer changes in sensorial characteristics and a better retention of micronutrients when compared to other technologies in place. HP treatments affect the main constituents of fish (proteins, lipids, and enzymes), influence its sensorial properties.

Keywords: Seafood, High Pressure Processing, non-thermal processing, Quality.

Abstract: The design, implementation and testing of an automobile Engine Control Unit (ECU) data acquisition system is presented. The ECU parameters are graphically analyzed on a PC (Windows/Linux) or a smart phone. The graphical analysis software for real-time data monitoring are developed on Qt framework for PC use and android platform for smart phone use. The use of open source software Qt framework and android SDK for GUI development is a highlight of this system. The wireless communication features of the system using Zigbee technology allows remote real-time monitoring of the vehicle on test track.

Keywords: Android, Engine Control Unit, OBD protocol, Qt Framework, Zigbee.

Abstract: This paper presents the co-operative based database for ad hoc Mobile Networks (MANET). The main focus of the system is on the nodes that save the queries sent. Queries are used as an index of the data stored in the caches of the nodes. This paper deals about the system formation and detection of demanded data from the cache or from the external database. Different parameters like upper and lower bonds for query caching nodes, average load experience, node bandwidth and hit ratio are analyzed and derived. The proposed method is simulated using NS-2. The proposed system has achieved a better success rate and a lower delay compared to other caching systems.

Keywords: Mobile ad hoc networks, distributed cache, cache indexing, database queries.

Abstract: Computer networking- Topology-Wired and wireless technologies- Routers- Switches- Bridges and firewalls-Internet-Intranet (Difference between internet and intranet).

Keywords: Topologies, Networking devices, Internet and Intranet, various protocols.

Abstract: Freshly extracted juice of lemon fruits was subjected to treatments such as pasteurization, addition of potassium metabisulphite and sodium benzoate. Processed and control samples of juice were stored at room and refrigeration temperature for 90 days and analyzed for chemical properties at 15 days of interval during storage. Total soluble solids and pH of juices increased during storage. On the contrary, ascorbic acid content and titratable acidity of juices decreased during storage period. Potassium metabisulphite was found most effective in preservation and keeping quality of juice showing little changes in chemical properties of juice during storage. Results suggested that processed lemon juice can be stored safely at room and refrigeration temperature for 90 days.

Keywords: Lemon, pasteurization, potassium metabisulphite, juice, refrigeration

Abstract: The industrial wastewater released into the environment causes water pollution. High content of toxic metals in the water is a main criteria for the water pollution. Lead is one of the toxic metal present in wastewater at a high rate. Hence, Removal of lead is considered to be a best reason to maintain hygienic environment. Removal of lead is found to be more efficient using packed adsorption processes by acidified neem saw dust. Adsorption kinetics, Thermodynamics parameters like Free energy (G),Change in Enthalpy (H), Change in Entropy (S) were observed. Experimental data is carried away for Langmuir, Freundlich and Temkin isothermal models and the overall yield at a rate of 6.493 mg/gm shows the best fit in Langmuir model.

Keywords: Lead, Enthalpy, Entropy, Free energy, Acidified Neem Saw Dust, Isothermal models.