M. Narendhar ¹, K. Anuradha ²

Affiliations
1 Department of CSE, SNTI, JNTUH, Kukatpally, Hyderabad - 500085, Telangana, IN
2 Department of CSE, GRIET, JNTUH, Kukatpally, Hyderabad - 500085, Telangana, IN

Abstract

Objective: This paper presents an automated requirement ranking approach for identifying software requirements, which combines the project requirements of the order of approximation calculated through learning techniques. Method: We proposed an algorithm RRA, which automatically calculates, approximate ranks for the requirements based on priority rules. Findings: The algorithm considers requirements as inputs and outputs the best suitable requirements for software development in three stages namely Pairing of requirements, Extraction of priority and Learning of Priority. The proposed algorithm is more effective compared to CBRank, especially for more number of extracted pairs. Improvement: The work can be extended to produce accurate ranks for more number of extracted requirement pairs.

Keywords

Automation, Requirement Ranking Process, Software Requirement.

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B. Dhanalaxmi ¹, G. Apparao Naidu ², K. Anuradha ³

Affiliations
1 Department of Information Technology, Institute of Aeronautical Engineering, Dundigal, Hyderabad –500 043, Telangana, IN
2 Department of Computer Science and Engineering, J. B. Institute of Engineering and Technology, Bhaskar Nagar, Moinabad Mandal, R. R. District, Hyderabad – 500075, Telangana, IN
3 Department of Computer Science and Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Nizampet Road, Bachupally, Kukatpally, Hyderabad – 500090, Telangana, IN

Abstract

Objective: Software development is a multitask activity performed by a team. Each activity involves with different tasks and complexity. To achieve quality of improvement it is important that each activity task should be fault free. But, finding and correcting faults are most expensive and time consuming. Methods: Software inspection is a static analysis technique which does not required program execution, instead it use inspector to make decision during the development. Findings: But it was observed in literature that inspection has bad records in finding accurate defects in software development. In this paper, we present a novel Fault Prediction Approach (FPA) based on the probabilistic model to improvise the software inspection to detect the defect accurately and cost effective for the quality software development. Application/ Improvement: Inspection is an effective activity to find the defects using empirical data in the initial stage of development. The proposed FPA investigate a probabilistic methods using modified Naive Bayes classification to estimate the probable faults in an experiment context to suggest fault controlling development. Further, the analysis investigates how FPA effectively identifying the faults during the inspection and impact in the quality development performance.

Keywords

Fault Prediction, Probabilistic Model, Software Inspection, Software Quality.

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K. Anuradha ¹, N. Sairam ²

Affiliations
1 School of Electrical and Electronics Engineering, SASTRA University, Tirumalaisamudram, Thanjavur - 613401, Tamil Nadu, IN
2 School of Computing, SASTRA University, Tirumalaisamudram, Thanjavur – 613401, Tamil Nadu, IN

Abstract

The objective of this review article is to study the spatio-temporal approaches for addressing the key issues such as multi-view, cluttering, jitter and occlusion in recognition of human action. Based on high-level action units, a new sparse model was developed for recognition of human action in static background. Relevant to multi-camera view, a negative space approach for identifying actions taken from different viewing angles was proposed. An approach was based on space-time quantities was proposed to acquire the changes of the action instead of camera motion. This space-time based approach has handled both cluttering and camera jitter. In static background, a sparse model presented for recognition of human action acquires the fact that actions from the same class share same units. The presented method was assessed on numerous public data sets. This method has achieved a recognition rate of 95.49% in KTH dataset and 89% in UCF datasets. Based on negative space, a region based method was offered. This approach has managed the issue of long shadows in human action recognition. The approach was assessed by most common datasets and has attained higher precision than contemporary techniques. An approach based on space-time quantities was proposed to manage cluttering. This approach achieves a recognition rate of 93.18% in KTH dataset and 81.5% in UCF dataset. To handle occlusion, a model was presented with spatial and temporal consistency. The algorithm was appraised on an outdoor dataset with background clutter and a standard indoor dataset (HumanEva-I). Results were matched with advanced pose estimation algorithms.

Keywords

Action Recognition, Camera Jitter, Clutter, Multi-view, Occlusion, Segmentation

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P Naga Padma ¹, P. Sravani ¹, Prity Mishra ¹, N. Sneha ¹, K. Anuradha ¹

Affiliations
1 Bhavan's Vivekananda College, Nirmala Nagar X Road, Neredmet, Sainikpuri Post, Near CDM, Sainikpuri, Secunderabad - 500094, Telangana State, IN

Abstract

Objectives: To clarify the apple juice enzymatically using different commercial enzymes like amylase, pectinase and cellulase at a standard concentration of 1U/ml both in isolation and in combination. To standardize the clarification conditions like temperature (40°C and 50°C) and different incubation time intervals (15 and 30 minutes). Methods/ Statistical Analysis: Apple juice was prepared from good cleaned fruits using distilled water by blending and extraction of juice. The extracted juice was filtered centrifuged and pasteurized before subjecting it to clarification. Different commercial enzymes like amylase, pectinase and cellulose were taken at a concentration of 1U/ml in sodium acetate buffer (pH 5) for clarification studies both in isolation and in combination. The clarification was measured in terms of viscosity reduction. The tested parameters for the present study were time of incubation (15-30 min), concentration of enzyme ( 1 U/ml) and temperature (40-50 °C). Findings: The apple juice was clarified using pectinase at 1U/ml in 30 min with reduction of viscosity to 1500 cP units at 40°C. When amylase and cellulase are used separately for apple juice clarification under similar enzymatic conditions there was viscosity reduction to 500 cP units at 40°C for 30 min incubation time and viscosity reduction to 600 cPunits 50° C for 30 min incubation time respectively. Pectinases in combination with amylases showed viscosity reduction up to 510 cP units and with cellulases 609 cP units at 50°C for 30 min of incubation time. Clarification of apple juice was found to be taking 30 min and there was reduction of viscosity to 400 (cP) when I U/ml concentration of amylase, pectinase and cellulase was used at 50°C in combination. Application/Improvements: The results indicated that there was a significant viscosity reduction of apple juice when enzymes were used in combination for fruit juice clarification. This can be applied for clarification of other fruit juices The study is significant as perishable and seasonal Indian apples grown in abundance can be used for commercial production of clarified juices.

Keywords

Amylase, Apple Juice, Pectinase and Cellulase, Viscosity.

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