Exact Requirements Engineering for Developing Business Process Models

Process modeling is a suitable tool for improving the business processes. Successful process modeling strongly depends on correct requirements engineering. In this paper, we proposed a combination approach for requirements elicitation for developing business models. To do this, BORE (Business-Oriented Requirements Engineering) method is utilized as the base of our work and it is enriched by the important features of the BDD (Business-driven development) method, in order to make the proposed approach appropriate for modeling the more complex processes. As the main result, our method eventuates in exact requirements elicitation that adapts the customers' needs. Also, it let us avoid any rework in the modeling of process. In this paper, we conduct a case study for the paper submission and publication system of a journal. The results of this study not only give a good experience of real world application of proposed approach on a web-based system, also it approves the proficiency of this approach for modeling the complex systems with many sub-processes and complicated relationships.Comment: (IEEE) 3th International Conference on Web Researc

Detecting circular shapes from areal images using median filter and CHT

One of the challenging topics in image processing is extracting the shapes from noisy backgrounds. There are some methods for doing it from different kinds of noisy backgrounds. In this paper, we are going to introduce another method by using 4 steps to extract circular shapes from impulse noisy backgrounds. First step is applying median filter to disappear "salt and pepper" noise. This step causes edge smoothing. So, as the second step, a laplacian sharpening spatial filter should be applied. It highlights fine details and enhances the blurred edges. Using these two steps sequentially causes noise reduction in an impressive way. Third step is using Canny edge detection for segmenting the image. Its algorithm is talked during the paper. Finally, forth step is applying Circular Hough Transform (CHT) for detecting the circles in image. At the end of paper different use cases of this method is investigated

A Sociological Study of Domestic Violence Against Women in Iran:A Narrative Review

Background and Aim: Domestic violence against women has always been a social problem and has continued in the social history of Iran. A wide range of studies have examined the causes and contexts of this problem from different perspectives. This study aimed to achieve a comprehensive theoretical model of the causes and contexts of domestic violence against women in Iran. Methods and Data: The research method of this study was a narrative review, examining 95 studies in Persian published over 20 years from 2002 to 2021. The variables that had a significant effect or correlation with violence against women in previous studies were categorized and the relationships of new variables were determined. Findings: Findings indicated that patriarchal values and beliefs and differences in socioeconomic status and low social and cultural, and economic capital are the leading causes of domestic violence against women in Iran. Other variables shown in the final model were all affected by one of these two main variables. Conclusion: In this study, social and cultural factors are put together to provide a more complete picture of the factors and contexts explaining domestic violence against women in Iran. The final proposed model can be used as a theoretical framework in future studies.<br/

Exploring SARS-COV-2 structural proteins to design a multi-epitope vaccine using immunoinformatics approach: An in silico study

In December 2019, a new virus called SARS-CoV-2 was reported in China and quickly spread to other parts of the world. The development of SARS-COV-2 vaccines has recently received much attention from numerous researchers. The present study aims to design an effective multi-epitope vaccine against SARS-COV-2 using the reverse vaccinology method. In this regard, structural proteins from SARS-COV-2, including the spike (S), envelope (E), membrane (M), and nucleocapsid (N) proteins, were selected as target antigens for epitope prediction. A total of five helper T lymphocytes (HTL) and five cytotoxic T lymphocytes (CTL) epitopes were selected after screening the predicted epitopes for antigenicity, allergenicity, and toxicity. Subsequently, the selected HTL and CTL epitopes were fused via flexible linkers. Next, the cholera toxin B-subunit (CTxB) as an adjuvant was linked to the N-terminal of the chimeric structure. The proposed vaccine was analyzed for the properties of physicochemical, antigenicity, and allergenicity. The 3D model of the vaccine construct was predicted and docked with the Toll-like receptor 4 (TLR4). The molecular dynamics (MD) simulation was performed to evaluate the stable interactions between the vaccine construct and TLR4. The immune simulation was also conducted to explore the immune responses induced by the vaccine. Finally, in silico cloning of the vaccine construct into the pET-28 (+) vector was conducted. The results obtained from all bioinformatics analysis stages were satisfactory; however, in vitro and in vivo tests are essential to validate these results

Comparative study of goldfish growth and survival rate feeding by fairy shrimp (Phallocryptus spinosa), Artemia and concentrate diet

The diet quality and type has a great role in aquatic animals and leads to increase of resistance against diseases and good growth. Cultured andornamental fish do not access to live and selected food due to captivity condition. Threfore, they should be provided with complete diet similar to natural food in captive condition. Carotenoid pigments are responsible of flesh pigmentation of edible fish and skin color of ornamental fish. The accumulation of this pigments in fish tissue has a greate importance in marketing and hence due to lack of its synthesis, carotenoids shoud be added to diet of cultured fish. As the synthetic carotenoids are harmful to the environment , there is a greate interest to use natural carotenoids in ornamental fish diets to obtain bright color. This study was carried out to compare the effects of diets containing Artemia urmiana and Phallocryptus spinosa supplements and commercial feed on growth and survival of goldfish fingerlings, quality of skin color, amounts of total carotenoids, Astaxantin, Canthaxantin and beta-carotene inCultured Carassius auratus during 90 days. The culture medium were contained glass aquaria in controlled condition and suitable for goldfish growth with 12 L: 12 D photoperiod and water temperature of 28±1 oC 3 test groups were included: treatment 1 fed with concentrate diet , treatment 2 fed with concentrate and frizzed Phallocryptus spinosa with tha same concentrations and treatment 3 fed with concentrate and frizzed Artemia urmiana with the same concentrations . Each treatment contains 2 replications and each replication consisted of 30 goldfish. In this study, The amounts of total carotenoids using spectrophotometer modelWPA, astaxantin, canthaxantin and beta-carotene using HPLC model Younglin, UK, were determined in the skin of Carassius auratus at the end of the exprement period. The results revealed that the most growth rate (GR), specific growth rate and condition factor (CF) were 0.11 ±0.006, 0.34 ± 0.015 and 3.96 ± 0.10, respectively which due to treatment 3 and the most weight gain and length gain including 8.57± 1.18g and 31.54± 3.33 mm, respectively due to treatment 2 .During rearing period, there was not any significant difference among treatments (p>0.05). The analysis of obtained data showed that there was a significant difference between diets containing live food and concentrate diet (p<0.05). The results revealed that live food enhanced skin color of Carassius auratus compared to concentrate diet. Also, the most pigmentation obtained from the diet contained fairy shrimp. As, in concentrate, concentrate and fairy shrimps, concentrate and Artemia diets amounts of total carotenoids at 450 nm wave length were 1.09, 3.90 and 2.07 mg/100, asthaxantin were 84.57, 205.82 and 102.24 ng/g and canthaxanthin were 0.24, 35.79 and 30.64 ng/g and carotenoid were 34.73, 138.78 and 69.77 ng/g, respectively. The use of fairy shrimp compared to Artemia in the diet can be significantly increased the amounts of carotenoids especially asthaxanthin in the skin of goldfish (p<0.05). Therefore fairy shrimps can be used as a suitable for artemia and high cost synthetic pigments to enhance color of ornamental fish

The global burden of adolescent and young adult cancer in 2019 : a systematic analysis for the Global Burden of Disease Study 2019

Background In estimating the global burden of cancer, adolescents and young adults with cancer are often overlooked, despite being a distinct subgroup with unique epidemiology, clinical care needs, and societal impact. Comprehensive estimates of the global cancer burden in adolescents and young adults (aged 15-39 years) are lacking. To address this gap, we analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, with a focus on the outcome of disability-adjusted life-years (DALYs), to inform global cancer control measures in adolescents and young adults. Methods Using the GBD 2019 methodology, international mortality data were collected from vital registration systems, verbal autopsies, and population-based cancer registry inputs modelled with mortality-to-incidence ratios (MIRs). Incidence was computed with mortality estimates and corresponding MIRs. Prevalence estimates were calculated using modelled survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated as age-specific cancer deaths multiplied by the standard life expectancy at the age of death. The main outcome was DALYs (the sum of YLLs and YLDs). Estimates were presented globally and by Socio-demographic Index (SDI) quintiles (countries ranked and divided into five equal SDI groups), and all estimates were presented with corresponding 95% uncertainty intervals (UIs). For this analysis, we used the age range of 15-39 years to define adolescents and young adults. Findings There were 1.19 million (95% UI 1.11-1.28) incident cancer cases and 396 000 (370 000-425 000) deaths due to cancer among people aged 15-39 years worldwide in 2019. The highest age-standardised incidence rates occurred in high SDI (59.6 [54.5-65.7] per 100 000 person-years) and high-middle SDI countries (53.2 [48.8-57.9] per 100 000 person-years), while the highest age-standardised mortality rates were in low-middle SDI (14.2 [12.9-15.6] per 100 000 person-years) and middle SDI (13.6 [12.6-14.8] per 100 000 person-years) countries. In 2019, adolescent and young adult cancers contributed 23.5 million (21.9-25.2) DALYs to the global burden of disease, of which 2.7% (1.9-3.6) came from YLDs and 97.3% (96.4-98.1) from YLLs. Cancer was the fourth leading cause of death and tenth leading cause of DALYs in adolescents and young adults globally. Interpretation Adolescent and young adult cancers contributed substantially to the overall adolescent and young adult disease burden globally in 2019. These results provide new insights into the distribution and magnitude of the adolescent and young adult cancer burden around the world. With notable differences observed across SDI settings, these estimates can inform global and country-level cancer control efforts. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe

Artificial Intelligence in Regenerative Medicine: Applications and Implications

The field of regenerative medicine is constantly advancing and aims to repair, regenerate, or substitute impaired or unhealthy tissues and organs using cutting-edge approaches such as stem cell-based therapies, gene therapy, and tissue engineering. Nevertheless, incorporating artificial intelligence (AI) technologies has opened new doors for research in this field. AI refers to the ability of machines to perform tasks that typically require human intelligence in ways such as learning the patterns in the data and applying that to the new data without being explicitly programmed. AI has the potential to improve and accelerate various aspects of regenerative medicine research and development, particularly, although not exclusively, when complex patterns are involved. This review paper provides an overview of AI in the context of regenerative medicine, discusses its potential applications with a focus on personalized medicine, and highlights the challenges and opportunities in this field

Prior Knowledge for Targeted Object Segmentation in Medical Images

Medical image segmentation, the task of partitioning an image into meaningful parts, is an important step toward automating medical image analysis and is at the crux of a variety of medical imaging applications, such as computer aided diagnosis, therapy planning and delivery, and computer aided interventions. However, existence of noise, low contrast and objects\u27 complexity in medical images preclude ideal segmentation. Incorporating prior knowledge into image segmentation algorithms has proven useful for obtaining more accurate and plausible results on targeted objects segmentation. In this thesis, we develop novel techniques to augment optimization-based segmentation frameworks with different types of prior knowledge to identify and delineate only those objects (targeted objects) that conform to specific geometrical, topological and appearance priors. These techniques include employing prior knowledge to segment multi-part objects with part-configuration constraints and encoding priors based on images acquired from different imaging equipment and of differing dimensions. Our objective is to satisfy two important aspects in optimization-based image segmentation: (1) fidelity-optimizability trade-off, and (2) space and time complexity.Particularly, in our first contribution, we adopt several prior information to build a faithful objective function unconcerned about its convexity to segment potentially overlapping cells with complex topology. In our second contribution, we improve the space and time complexity and augment the level sets framework with the ability to handle geometric constraints between boundaries of multi-region objects. In our first two contributions we opt for ensuring the objective function is flexible enough (even if it is non-convex) to accurately capture the intricacies of the segmentation problem. In our third contribution, we focus on optimizability. We propose a convex formulation to augment the popular Mumford-Shah model and develop a new regularization term to incorporate similar geometrical and distance prior as our second contribution while maintaining global optimality. Lastly, we efficiently incorporate different types of priors based on images acquired from different imaging equipment (different modalities) and of dissimilar dimensions to segment multiple objects in intraoperative multi-view endoscopic videos. We show how our technique allows for the inclusion of laparoscopic camera motion model to stabilize the segmentation