Ansal University

Gurgaon, India

Ansal University

Gurgaon, India
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Khatter K.,Ansal University | Kalia A.,Himachal Pradesh University
Proceedings of the International Conference on Industrial Engineering and Operations Management | Year: 2016

A defective module not only increases the development time and development cost but also increases the maintenance time and maintenance cost. According to the available literature survey, many systems failed due to schedule and time budget overruns. Therefore a software defect detection technique is needed to identify those software modules that are very likely to include defects and thereby improves the software quality by contributing in the efficient removal software defects. The main objective of the paper is to help software developers in identifying the software defects based on the various software metrics using various classification and machine learning techniques. In this paper, we are performing empirical classification comparison on 5 real world datasets. © IEOM Society International. © IEOM Society International.


Srivastava P.,Ansal University | Singh R.M.,Motilal Nehru National Institute of Technology
Journal of Irrigation and Drainage Engineering | Year: 2017

Real-world problems in the agricultural sector are usually multiobjective in nature. More than one objective needs to be fulfilled simultaneously to incorporate economic and social requirements in an acceptable and optimal cropping pattern. Fuzzy multiobjective goal programming (FMGP) techniques can be used to solve optimization formulations. The purpose of this paper is to present a fuzzy multiobjective-based goal programming (GP) model for optimal allocation of land under cultivation to optimize cropping patterns. In this work, goal programming is implemented in two parts. In the first part, only two objectives, maximization of benefit and production, are considered. In the second part, seven objectives are considered in goal programming: maximization of benefit, maximization of production, minimization of investment, minimization of fertilizer application [i.e., minimization of nitrogen (N) application, minimization of phosphorus (P) application, and minimization of potash (K) application], and minimization of water application. FMGP is used to solve multiobjective formulations. Multiobjective solutions provide the necessary aspiration and tolerance levels for goal programming. Performance evaluation of the methodology is demonstrated for a real canal command area. © 2017 American Society of Civil Engineers.


Khatri M.,Ansal University | Kumar A.,Ansal University
International Journal of Renewable Energy Research | Year: 2017

The power quality issues in the grid tied solar photovoltaic system are important to address to know about the actual power production and consumption in the existing system. This paper investigates the presence of voltage and current harmonics due to the linear, nonlinear loads and the reactive power transferred between plant, grid and load. The digital power analyzers are kept in the system to know the amount of power import and export between the plant and grid, so as to serve the load. In order to control the effect of harmonics a compensator in incorporated in the phase locked loop of the inverter as well as a power quality conditioner is connected at the point of common coupling. It has been found that by switching the conditioner unit, the quality of power and power factor of the system gets improved and it also reduces the export of reactive power to the load so as to obtain the reliable and efficient operation of the grid tied solar photovoltaic system.


Sharma R.,Ansal University
Environment, Development and Sustainability | Year: 2017

The major problem associated with gravity dam was siltation of reservoir which reduced its effective water storage capacity. In order to maintain effective storage capacity of reservoir, dredging of deposits was required and dredged material was disposed of haphazardly causing damage to the sensitive environment. A better alternative could be the possibility of utilization of dredged deposits in construction works involving large quantities of material. The dredged material consisted of very fine sandy silt possessing poor geotechnical characteristics and was required to be stabilized with suitable additives before use as construction material. This laboratory investigation evaluated geotechnical properties of dredged reservoir material stabilized with cement, fly ash and fiber for its probable use as subbase in lightly trafficked roads. Compaction, unconfined compressive strength and tensile strength tests were performed on appropriate combinations of the constituent materials. The results of study revealed significant improvement in unconfined compressive strength and split tensile strength after stabilization with cement and fly ash. The unconfined compressive strength and split tensile strength of cement–fly ash-stabilized dredged reservoir material improved further upon addition of polypropylene fiber. The composite possessed the potential to be utilized as sustainable material in subbase of roads subject to further validation before application in the field. The dredging of sediments improved effective storage capacity of reservoir and increased its sustainable life period. The utilization of fly ash could diminish the environmental and economic concerns arising out of its haphazard disposal. © 2017 Springer Science+Business Media Dordrecht


Kaur A.,Ansal University | Sharma P.C.,Ansal University
Environment, Development and Sustainability | Year: 2017

The purpose of the paper is to assess the inclusion of social sustainability in the decisions of supply chain in multinational manufacturing organisations in India. Indian organisations are resorting to sustainability-based reporting for greater transparency and for creation of brand value for their organisations. There are tremendous economic upheavals and changes across the complete value chain, and thus, responsible business practices are becoming a necessity for the long-term survival of organisations. Sustainability, as a strategy, is responsible utilisation of resources and is reported through social, economic and environmental factors in an organisation. For sustainability as a strategy, there has to be a complete organisational inclusion and employee engagement through decision making at operational levels along the value chain. The research paper is an empirical study done through a survey using a structured questionnaire to collect information to evaluate decision criteria particularly for social sustainability, from the middle and top level executives in Indian manufacturing organisations. Multinational manufacturing organisations in India are trying to be more responsible because of mandated CSR policy, and thus, sustainability through social factors is getting more prominence. A multiple linear regression analysis is used to explain the correlation and inclusion of social factors on the decision-making process in the supply chain of multinational manufacturing organisations in India. This study reveals that decision making in the supply chain of multinational manufacturing organisations in India specifically in manufacturing industry is incorporating social sustainability. The study highlights that decision making involving social sustainability needs larger frameworks for organisational preference. While the study provides evidence of social sustainability-based practices in multinational manufacturing organisations in India, it does not deal with social sustainability practices. The study also has limitation as has been limited to organisations which follow sustainability practices and make disclosures through GRI framework. © 2017 Springer Science+Business Media Dordrecht


Sharma R.,Ansal University
Jordan Journal of Civil Engineering | Year: 2017

This experimental study highlights the results of compressive strength tests performed on different specimens of concrete consisting of construction demolition waste and/or glass waste with or without superplasticizer and fiber. The 28-day compressive strength of concrete increases on the use of construction and demolition waste aggregates compared to that of control specimen. When fine aggregate is replaced with glass waste to the extent of 30%, an increase in compressive strength is observed. Utilization of construction and demolition waste aggregates and glass waste replacing fine aggregate yields improved compressive strength. The replacement of fine aggregate with glass waste including the use of superplasticizer and fiber tends to increase compressive strength. However, if construction and demolition waste aggregates and waste glass replacing fine aggregate including superplasticizer and fiber are used, the compressive strength achieved is less. The construction demolition waste and/or glass waste can be used in concrete yielding improved compressive strength, thereby solving the problem of disposal as well as preserving the environment. © 2017 JUST. All Rights Reserved.


Bahl S.,Ansal University | Sharma S.K.,Ansal University
International Conference on Computing, Communication and Automation, ICCCA 2015 | Year: 2015

Intrusion detection system (IDS) research field has grown tremendously in the past decade. Improving the detection rate of user to root (U2R) attack classes is an open research problem. Current IDS uses all data features to detect intrusions. Some of the features may be redundant to the detection process. The purpose of this empirical study is to identify important features to improve the detection rate of U2R attack class. The investigated correlation feature selection improved the overall accuracy, detection rate of U2R attack. The empirical results have given a noticeable improvement in detection rate of U2R. © 2015 IEEE.


Aggarwal P.,Ansal University | Sharma S.K.,Ansal University
International Conference on Advanced Computing and Communication Technologies, ACCT | Year: 2015

The massive data exchange on the web has deeply increased the risk of malicious activities thereby propelling the research in the area of Intrusion Detection System (IDS). This paper aims to first select ten classification algorithms based on their efficiency in terms of speed, capability to handle large dataset and dependency on parameter tuning and then simulates the ten selected existing classifiers on a data mining tool Weka for KDD'99 dataset. The simulation results are evaluated and benchmarked based on the generic evaluation metrics for IDS like F-score and accuracy. © 2015 IEEE.


Aggarwal P.,Ansal University | Sharma S.K.,Ansal University
Advances in Intelligent Systems and Computing | Year: 2016

Imbalance in data is quite obvious while studying intrusion detection system (IDS). Classification algorithms are used to identify the attacks in IDS, which has many parameters for its performance evaluation. Due to imbalance in data, the classification results need to be revisited given that IDS generally evaluates detection rate and false alarm rate which belongs to two different classes. This paper validates a new metric NPR used for ranking the classifiers for IDS. The metric is made functional on KDD data set and then the classifiers are ranked and compared with results on another data set. © Springer India 2016.


Aggarwal P.,Ansal University | Sharma S.K.,Ansal University
Procedia Computer Science | Year: 2015

The KDD data set is a well known benchmark in the research of Intrusion Detection techniques. A lot of work is going on for the improvement of intrusion detection strategies while the research on the data used for training and testing the detection model is equally of prime concern because better data quality can improve offline intrusion detection. This paper presents the analysis of KDD data set with respect to four classes which are Basic, Content, Traffic and Host in which all data attributes can be categorized. The analysis is done with respect to two prominent evaluation metrics, Detection Rate (DR) and False Alarm Rate (FAR) for an Intrusion Detection System (IDS). As a result of this empirical analysis on the data set, the contribution of each of four classes of attributes on DR and FAR is shown which can help enhance the suitability of data set to achieve maximum DR with minimum FAR. © 2015 Published by Elsevier Ltd.

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