Software Engineering: Factors Affect on Requirement Prioritization

Software engineering research is yet in its early stages hence it needs evaluation. So, software engineers think about experimental research and try to adopt analytical approaches to validate results like in other sciences. It should be asserting that requirement engineering process is to use requirements prioritization. The use of requirements prioritization helps the anatomy of requirements and isolates the most important requirements. A lot of prioritization techniques, practices and methodologies are used in software requirements. But lack of empirical search program and proficient methodology, was not decide which should be implemented. In this research, the requirement prioritization for systematical reviews was carried out. Based on systematic review, a framework is introduced for further research within requirement prioritization. This paper described a framework for scrutinize the discussion that take place during requirements elicitation and requirements prioritization. The survey presented in the paper gives a practical view how to prioritize the requirements. It also reflects the requirements prioritization in the industries needs. Which factors of the requirements engineering affect the requirements prioritization

Performance Comparison of DSR and AODV Routing Protocols for Soft Delay Deadlines in Wireless Multimedia Sensor Network

Wireless Multimedia Sensor Network (WMSN) is a collection of the vast amount of different types of sensors like camera sensor, video and scalar sensors which are involved in retrieving multimedia data from the large environment. The real-time sending of video and audio content to the destination before a strict playout deadline has been necessary for multimedia environment. Otherwise, it will be dropped at the destination. In WMSN sending real time multimedia data with soft play deadlines is a challenging task to solve this challenge, routing protocols play an important role in WMSN. Routing demands of multimedia content of WMSNs need to be perfect routing protocols to optimize path selection and guarantee communication. This paper presents a performance comparison between two reactive routing protocols; namely AODV and DSR, with soft delay deadlines and efficient utilization of resources in WMSN. The objective is to assess the real-time behavior of these two protocols upon sending multimedia content. Here, we evaluate the performance with respect to the use of these matrices like latency, Average jitter, Average delay and throughput and factors includes are CBR and multimedia traffic with varying packet size and bandwidth. DSR perform better as compared to AODV routing protocol since it discovers the routes more efficiently. AODV is better in term of Jitter than DSR. NS-2 simulator tool used for the purpose of this comparison

An Empirical Study of COTS components Persuasion, Evaluation & Selection and Integration in software houses Faisalabad, Pakistan

Abstract Under development countries (UDCs) like Faisalabad, Pakistan where information technology benefits are not yet fully utilized due to lack of resources and very old infrastructure. Selecting suitable commercial off-the-shelf (COTS) is the most critical phase in COTS-based software development. However, in research, numerous problems are faced during the COTS evaluation, selection and integration. All these major causes are due to the lack of familiarity about COTS products, the unawareness of the available number of methods for COTS evaluation, selection, integration and deployment phase, and the deficiency of supervision for selecting between these best methods for COTS evaluation and selection. In this research work, a closed questionnaire method was adopted to evaluate the user's perception about COTS evaluation, selection & integration in software houses and IT Professional in Faisalabad, Pakistan. The results of this work will contribute towards a framework development for COTS evaluating and selecting, integration

Factors affecting return to work following endoscopic lumbar foraminal stenosis surgery: A single-center series

Background: This study evaluates the factors affecting the return to work of endoscopic surgery for lumbar foraminal stenosis (LFS), including symptoms, functional status, complications, and reoperation rates. Methods: The authors' retrospective cohort study included 100 consecutive patients (50 males and 50 females) diagnosed with LFS who underwent endoscopic surgery at Trotsky National Research Center of Surgery between January 2018 and December 2021. Results: There were no significant differences in age and preoperative visual analog scale and Oswestry disability index scores between the male and female groups, time to return to work for different patient groups after undergoing endoscopic lumbar foraminotomy (ELF). However, patients with more severe stenosis and comorbidities may take longer to recover. Confounding factors were patient age, preoperative physical function, and job requirements. Conclusion: This study confirms that study ELF can effectively improve symptoms associated with lumbar radiculopathy, as well as back pain, and improve patients' quality of life. Comorbidity, smoking status, and complications prolong the time to return to work following ELF surgery compared to healthy subjects

Fagan Inspection: A Defects Finding Mechanism in Software Requirements Specification (SRS) Document

The preparation of Software Requirement Specification (SRS) document is a critical task as the successful completion of software depends heavely upon the SRS. The requirements gathering phase in Software Development Life Cycle SDLC is equally important as it witnesses the creation of an SRS document. The quality of an SRS document is dubious as there is a scarcity of proficient inspection methods for detecting the defects in the software. There are various reading based inspection techniques such as Checklist Based Reading technique (CBR), Defect Based Reading technique (DBR) and Perspective Based Reading technique (PBR). There are certain problems with these techniques such as the CBR only covers  potential types of defects, The DBR focused on various defects but the problem is that it is not structured in nature. Likewise, PBR is not suitable as it mainly focused on use-cases. As owing to the absence of a suitable inspection technique, the main focus of this study is to highlight the Fagan based inspection technique. This technique is not only formal and lightweight but it also overcome the limitations of reading base d techniques. The Fagan is a structured approach and finds defects in specification, programming code, design and also others during the SDLC. During analysis a questionnaire based survey is conducted in almost 300 national and international software industries. As a result, 150 responses are received. The likert scale is used for developing the questionnaire. SPSS tool is also utilized for data entry and analysis. The consequences are drawn by developing hypothesis and using the Chi-square test. More satisfactory results are gained at international level than at the national level. The satisfaction level of defect detection is 59.2%, time saved is 48.3% and cost reduction is 40.0%. Thus, the obtained outcome is positive and satisfies the requirements

Public’s Mental Health Monitoring via Sentimental Analysis of Financial Text Using Machine Learning Techniques

Public feelings and reactions associated with finance are gaining significant importance as they help individuals, public health, financial and non-financial institutions, and the government understand mental health, the impact of policies, and counter-response. Every individual sentiment linked with a financial text can be categorized, whether it is a headline or the detailed content published in a newspaper. The Guardian newspaper is considered one of the most famous and the biggest websites for digital media on the internet. Moreover, it can be one of the vital platforms for tracking the public’s mental health and feelings via sentimental analysis of news headlines and detailed content related to finance. One of the key purposes of this study is the public’s mental health tracking via the sentimental analysis of financial text news primarily published on digital media to identify the overall mental health of the public and the impact of national or international financial policies. A dataset was collected using The Guardian application programming interface and processed using the support vector machine, AdaBoost, and single layer convolutional neural network. Among all identified techniques, the single layer convolutional neural network with a classification accuracy of 0.939 is considered the best during the training and testing phases as it produced efficient performance and effective results compared to other techniques, such as support vector machine and AdaBoost with associated classification accuracies 0.677 and 0.761, respectively. The findings of this research would also benefit public health, as well as financial and non-financial institutions

Quality of Life Improves with Alemtuzumab Over 6 Years in Relapsing-Remitting Multiple Sclerosis Patients with or without Autoimmune Thyroid Adverse Events: Post Hoc Analysis of the CARE-MS Studies

Introduction In clinical trials of alemtuzumab, autoimmune thyroid adverse events (AEs) were frequent. Here, we assess the impact of thyroid AEs on health-related quality of life (HRQL) in alemtuzumab-treated patients with relapsing-remitting multiple sclerosis (RRMS). Methods In phase 3 CARE-MS I (NCT00530348) and II (NCT00548405) trials, patients with RRMS were administered alemtuzumab 12 mg/day on 5 consecutive days at baseline and on 3 consecutive days 12 months later. Patients could participate in an extension study (NCT00930553) through year 6. HRQL was assessed at baseline and annually using the Functional Assessment of Multiple Sclerosis (FAMS), EuroQoL-5 Dimension Visual Analog Scale (EQ-5D VAS), and 36-Item Short-Form Survey (SF-36) questionnaires. Outcomes were analyzed in patients with or without thyroid AEs (nonserious or serious). A subset of patients with thyroid AEs was analyzed to assess HRQL before and during the onset of thyroid AEs. Results A total of 811 CARE-MS patients were treated with alemtuzumab. Of these, 342 (42%) patients experienced thyroid AEs over 6 years; serious thyroid AEs occurred in 44 (5%) patients. At year 6, HRQL outcomes generally remained slightly improved or similar to core study baseline in alemtuzumab-treated patients with or without thyroid AEs: FAMS (least-squares mean change from baseline without thyroid AEs, 0.7; with nonserious thyroid AEs, 5.1; with serious thyroid AEs, − 5.3), EQ-5D VAS (2.0; 3.0; − 6.8), SF-36 mental component summary (MCS [0.6; 1.6; − 2.8]), SF-36 physical component summary (PCS [0.8; 1.0; 1.1]). Over 6 years, 63–82% of patients in each group had improved/stable SF-36 MCS and PCS scores. Among patients with thyroid AE onset in year 3 (peak incidence), there were minimal differences between HRQL outcomes before onset (year 2) and after onset (year 3). Conclusion Autoimmune thyroid AEs (serious and nonserious) had minimal impact on HRQL in alemtuzumab-treated patients. These data may aid therapeutic decisions in patients with relapsing MS