Challenges and Barriers of Using Low Code Software for Machine Learning

As big data grows ubiquitous across many domains, more and more stakeholders seek to develop Machine Learning (ML) applications on their data. The success of an ML application usually depends on the close collaboration of ML experts and domain experts. However, the shortage of ML engineers remains a fundamental problem. Low-code Machine learning tools/platforms (aka, AutoML) aim to democratize ML development to domain experts by automating many repetitive tasks in the ML pipeline. This research presents an empirical study of around 14k posts (questions + accepted answers) from Stack Overflow (SO) that contained AutoML-related discussions. We examine how these topics are spread across the various Machine Learning Life Cycle (MLLC) phases and their popularity and difficulty. This study offers several interesting findings. First, we find 13 AutoML topics that we group into four categories. The MLOps topic category (43% questions) is the largest, followed by Model (28% questions), Data (27% questions), Documentation (2% questions). Second, Most questions are asked during Model training (29%) (i.e., implementation phase) and Data preparation (25%) MLLC phase. Third, AutoML practitioners find the MLOps topic category most challenging, especially topics related to model deployment & monitoring and Automated ML pipeline. These findings have implications for all three AutoML stakeholders: AutoML researchers, AutoML service vendors, and AutoML developers. Academia and Industry collaboration can improve different aspects of AutoML, such as better DevOps/deployment support and tutorial-based documentation

Does the exchange rate influence the exports? Evidence from Bangladesh

Abstract. This paper attempts to examine the nature of the association between the exchange rate and exports of Bangladesh. The study uses the cointegration approach to show the long-run relationship between the variables using time series data from 1981 to 2015. The result suggests that the nonstationary data of export and exchange rate become stationary at the first difference and these two first degree autoregressive series don’t exhibit any long-run association. So, the findings provide a distinctive insight about future foreign exchange policy in the developing countries like Bangladesh. However, the policymakers also must be careful about the other macroeconomic and foreign trade factors before formulating any policy based on this study. The first section of the paper, introduction, objectives, is followed by the literature review, data and method, results and the concluding remarks.Keywords. Exchange rate, Depreciation, Cointegration.JEL. F31, F32, C18

Impact of Moral and Ethical Degradation on Poverty in Bangladesh: A Sustainable Solution from Islamic Perspective

The paper aimed to study the impact of degradation of moral and ethical values in some cases since this degradation had become a worried matter for our society In this study we also tried to mention some interior causes which have an exquisite interrelation with the poverty nature of Bangladesh Researchers followed the analytical method to complete this study The research shows there is a mentionable impact of educational political cultural and economic moral degradation of poverty Hence a critical proper sustainable solution from the Islamic perspective is needed to protect this degradation It is also proven that Islam as a comprehensive way of life encompasses a complete moral and ethical ground that is amplify in human social culture and their lifestyle So abide by the precept of Islamic views it is possible to build a sustainable social development in completing with moral ethical and Islamic perception with collectivel

Can We Use SE-specific Sentiment Analysis Tools in a Cross-Platform Setting?

In this paper, we address the problem of using sentiment analysis tools 'off-the-shelf,' that is when a gold standard is not available for retraining. We evaluate the performance of four SE-specific tools in a cross-platform setting, i.e., on a test set collected from data sources different from the one used for training. We find that (i) the lexicon-based tools outperform the supervised approaches retrained in a cross-platform setting and (ii) retraining can be beneficial in within-platform settings in the presence of robust gold standard datasets, even using a minimal training set. Based on our empirical findings, we derive guidelines for reliable use of sentiment analysis tools in software engineering.Comment: 12 page

Effects of reductive stripping of reactive dyes on the quality of cotton fabric

Some common problems of textile dyeing industries include uneven or faulty dyeing and formation of color patches on the fabric surface during dyeing and downstream processing of textiles materials. Such problems in the finished quality of fabric are generally tackled through a chemical stripping process which is a common practice in dyeing industries for the deep shade batches. However, reactive dyes cannot be stripped satisfactorily from cellulosic materials due to the formation of co-valent bonds between dye and fiber. This research was undertaken using 2.5% and 5% bi-hetero reactive dyes on pretreated cotton fabric and dye stripping was carried out in alkali reductive stripping process. The aim of the work was to investigate the effects of dye stripping on the quality of cotton fabric. Strength loss, weight loss, pilling resistance and absorbency of stripped fabric were calculated. Though with the increase of concentration of stripping chemicals and temperature, stripping percentages were improved; processing damage to the fabric such as losses in strength, weight and pilling resistance ratings was found. In contrast, increased fabric absorbency was found due to stripping. This is explained that during stripping, alkaline solution as an intracrystalline swelling agent is effective in loosening the crystalline region of cotton in addition to the amorphous region. Stripping agent can also attack such crystalline region. As a result, cotton fiber can release maximum number of hydroxyl groups which previously formed covalent bonds. This is the reason behind the stripped fabric having more water absorbency

Effects of reductive stripping of reactive dyes on the quality of cotton fabric

Some common problems of textile dyeing industries include uneven or faulty dyeing and formation of color patches on the fabric surface during dyeing and downstream processing of textiles materials. Such problems in the finished quality of fabric are generally tackled through a chemical stripping process which is a common practice in dyeing industries for the deep shade batches. However, reactive dyes cannot be stripped satisfactorily from cellulosic materials due to the formation of co-valent bonds between dye and fiber. This research was undertaken using 2.5% and 5% bi-hetero reactive dyes on pretreated cotton fabric and dye stripping was carried out in alkali reductive stripping process. The aim of the work was to investigate the effects of dye stripping on the quality of cotton fabric. Strength loss, weight loss, pilling resistance and absorbency of stripped fabric were calculated. Though with the increase of concentration of stripping chemicals and temperature, stripping percentages were improved; processing damage to the fabric such as losses in strength, weight and pilling resistance ratings was found. In contrast, increased fabric absorbency was found due to stripping. This is explained that during stripping, alkaline solution as an intracrystalline swelling agent is effective in loosening the crystalline region of cotton in addition to the amorphous region. Stripping agent can also attack such crystalline region. As a result, cotton fiber can release maximum number of hydroxyl groups which previously formed covalent bonds. This is the reason behind the stripped fabric having more water absorbency

Physiotherapy combined with dry needling among patients with chronic low back pain: Study protocol for a randomized controlled clinical trial

Background: Chronic low back pain (CLBP) is an extremely common public health concern responsible for pain-related disability. CLBP is challenging to manage despite having a plethora of treatment options. Physiotherapy is a guideline-recommended treatment for CLBP. Furthermore, some forms of complementary medicines, such as dry needling, spinal manipulation, Tai Chi, and yoga are also recommended for CLBP treatment. We hypothesized that the combined treatment would be more effective when managing CLBP. Therefore, this randomized clinical trial aims to examine the impact of combined therapy of dry needling and physiotherapy compared to the treatment effect of only physiotherapy among patients with CLBP. Methods: The study is a two-armed single-center, randomized controlled clinical superiority trial where participants are randomized to combined therapy of usual care physiotherapy and dry needling or only usual care physiotherapy (1:1). Individuals who are 18 years or older and experiencing LBP with or without leg pain for a minimum of three months will be considered eligible for the study. Pain severity, pain affective and physical interference, activity limitation, and insomnia symptoms of patients with CLBP will be measured at the baseline after four, 12 and 24-week treatment started. Conclusion: Finding a better management strategy for managing CLBP is an ongoing challenge. Most of the novel techniques that try to manage CLBP are limitedly tested. This study will allow testing of the combined effect of usual care physiotherapy and dry needling when managing CLBP in terms of clinical efficacy. If the combined therapy is proven significantly effective, compared to usual care physiotherapy alone will provide plausible evidence of an effective treatment option to manage CLBP. Trial registration: Clinical Trial Registry-India; trial registration number- CTRI/2022/09/045625