103 research outputs found
IDENTIFICATION AND QUANTIFICATION OF VARIABILITY MEASURES AFFECTING CODE REUSABILITY IN OPEN SOURCE ENVIRONMENT
Open source software (OSS) is one of the emerging areas in software engineering, and
is gaining the interest of the software development community. OSS was started as a
movement, and for many years software developers contributed to it as their hobby
(non commercial purpose). Now, OSS components are being reused in CBSD
(commercial purpose). However, recently, the use of OSS in SPL is envisioned
recently by software engineering researchers, thus bringing it into a new arena. Being
an emerging research area, it demands exploratory study to explore the dimensions of
this phenomenon. Furthermore, there is a need to assess the reusability of OSS which
is the focal point of these disciplines (CBSE, SPL, and OSS). In this research, a mixed
method based approach is employed which is specifically 'partially mixed sequential
dominant study'. It involves both qualitative (interviews) and quantitative phases
(survey and experiment). During the qualitative phase seven respondents were
involved, sample size of survey was 396, and three experiments were conducted. The
main contribution of this study is results of exploration of the phenomenon 'reuse of
OSS in reuse intensive software development'. The findings include 7 categories and
39 dimensions. One of the dimension factors affecting reusability was carried to the
quantitative phase (survey and experiment). On basis of the findings, proposal for
reusability attribute model was presented at class and package level. Variability is one
of the newly identified attribute of reusability. A comprehensive theoretical analysis
of variability implementation mechanisms is conducted to propose metrics for its
assessment. The reusability attribute model is validated by statistical analysis of I 03
classes and 77 packages. An evolutionary reusability analysis of two open source
software was conducted, where different versions of software are analyzed for their
reusability. The results show a positive correlation between variability and reusability
at package level and validate the other identified attributes. The results would be
helpful to conduct further studies in this area
Exploring Deep Learning Techniques for Glaucoma Detection: A Comprehensive Review
Glaucoma is one of the primary causes of vision loss around the world,
necessitating accurate and efficient detection methods. Traditional manual
detection approaches have limitations in terms of cost, time, and subjectivity.
Recent developments in deep learning approaches demonstrate potential in
automating glaucoma detection by detecting relevant features from retinal
fundus images. This article provides a comprehensive overview of cutting-edge
deep learning methods used for the segmentation, classification, and detection
of glaucoma. By analyzing recent studies, the effectiveness and limitations of
these techniques are evaluated, key findings are highlighted, and potential
areas for further research are identified. The use of deep learning algorithms
may significantly improve the efficacy, usefulness, and accuracy of glaucoma
detection. The findings from this research contribute to the ongoing
advancements in automated glaucoma detection and have implications for
improving patient outcomes and reducing the global burden of glaucoma
IDENTIFICATION AND QUANTIFICATION OF VARIABILITY MEASURES AFFECTING CODE REUSABILITY IN OPEN SOURCE ENVIRONMENT
Open source software (OSS) is one of the emerging areas in software engineering, and
is gaining the interest of the software development community. OSS was started as a
movement, and for many years software developers contributed to it as their hobby
(non commercial purpose). Now, OSS components are being reused in CBSD
(commercial purpose). However, recently, the use of OSS in SPL is envisioned
recently by software engineering researchers, thus bringing it into a new arena. Being
an emerging research area, it demands exploratory study to explore the dimensions of
this phenomenon. Furthermore, there is a need to assess the reusability of OSS which
is the focal point of these disciplines (CBSE, SPL, and OSS). In this research, a mixed
method based approach is employed which is specifically 'partially mixed sequential
dominant study'. It involves both qualitative (interviews) and quantitative phases
(survey and experiment). During the qualitative phase seven respondents were
involved, sample size of survey was 396, and three experiments were conducted. The
main contribution of this study is results of exploration of the phenomenon 'reuse of
OSS in reuse intensive software development'. The findings include 7 categories and
39 dimensions. One of the dimension factors affecting reusability was carried to the
quantitative phase (survey and experiment). On basis of the findings, proposal for
reusability attribute model was presented at class and package level. Variability is one
of the newly identified attribute of reusability. A comprehensive theoretical analysis
of variability implementation mechanisms is conducted to propose metrics for its
assessment. The reusability attribute model is validated by statistical analysis of I 03
classes and 77 packages. An evolutionary reusability analysis of two open source
software was conducted, where different versions of software are analyzed for their
reusability. The results show a positive correlation between variability and reusability
at package level and validate the other identified attributes. The results would be
helpful to conduct further studies in this area
Challenges of conducting animal based research and teaching in medical colleges of Karachi, Pakistan
Three siblings with Charcot-Marie-tooth Disease with no other family history
Charcot-Marie-Tooth (CMT) disease is one of the most common inherited disorders of the peripheral nervous system. Patients diagnosed with CMT disease have axonal degeneration which results in muscle wasting, sensory loss and weakness. These patients have a very characteristic walking gait and shape of hands, along with other changes. Despite many common visible changes, no singular common genetic mutation for this disease or its cure has been identified. Therefore more case series for this disease needs to be identified so that future studies increase our knowledge about this disease. Here, we present a case series of 3 out of 4 siblings who have been diagnosed with CMT disease. Based on their age, these siblings show the different developmental stages of this disease. More of such case series need to be identified and reported so that we can identify the true genetic cause of this disease and develop a definitive cure for it
Association of Etiological and Pathological Features of Brain Abscess with Outcome
To study the etiological andpathological factors of brain abscess and to relatewith the final outcome.Methods: In this observational study patients withbrain abscess were observed in detail with theclinical profile, etiology, microbiology and theirfinal outcome after one year.Chi-square test wasapplied to associate etiological and pathologicalfactors with management outcome.Results: The majority of patients were in their 2ndand 3rd decade of life with two third proportioncomprising of males. The most frequent etiologicalfactor was chronic suppurative otitis media (CSOM)( 55%),followed by head injury (12% ) and congenitalheart disease (10%). Microbiological data revealed16% streptococci, 10% staph. aureus, 7% staph.epidermidis and 5% proteus as major pathogens inthe study patients. Head injury and CSOM werefound associated with death and morbidity in thisstudy.Conclusion: Brain abscess has multi dimensionalcauses. CSOM and head injury were foundassociated with death and severe morbidity ashemiparesis and fits. CT findings andmicrobiological data were not associated withoutcome
A Weighted Linear Combining Scheme for Cooperative Spectrum Sensing
AbstractCooperative spectrum sensing exploits spatial diversity of secondary-users (SUs), to reliably detect the availability of a spectrum. Soft energy combining schemes have optimal detection performance at the cost of high cooperation overhead, since actual sensed data is required at the fusion center. To reduce cooperation overhead, in hard combining only local decisions are shared; however the detection performance is suboptimal due to the loss of information. In this paper, a weighted linear combining scheme is proposed in which a SU performs a local sensing test based on two threshold levels. If local test result lies between the two thresholds then the SU report neither its local decision nor sequentially estimated unknown SNR parameter values, to the fusion center. Thereby, uncertain decisions about the presence/absence of the primary-user signal are suppressed. Simulation results suggest that the detection performance of the proposed scheme is close to optimal soft combining schemes yet its overhead is similar to hard combining techniques
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