Showing papers in "International Journal of Health Sciences (IJHS) in 2022"
TL;DR: In addition to the consequences derived from the effects of the virus, the mental health of people was impacted with high repercussions at the social and family level, as well as the teaching processes at the different levels of education where many students abandoned their studies.
Abstract: Current experiences at a global level are an inspiration for research in the academic field. There is much to learn, and society must carefully reflect on the moments lived in two years that for many have meant two centuries. Many difficulties remain to be resolved and a wide field to discover the unknown by medicine. With the difficulties that have arisen on a global scale because of COVID-19, health has been affected at the societal level; In addition to the consequences derived from the effects of the virus, the mental health of people was impacted with high repercussions at the social and family level, as well as the teaching processes at the different levels of education where many students abandoned their studies.
613 citations
TL;DR: In this paper, an improved method based on machine learning was proposed to analyze the sequencing and tumor sequencing patterns of the human gene and analyzes the circulatory problems of patients with different tumor types for analysis in the public domain.
Abstract: In general, the various medical systems currently available provide insights into changes in the tumor genome of patients with tumor sequencing. Most of the tumor DNA sequencing can also be referred to as genetic specification or genetic testing. The sequence results help clinical decision-making to develop a personalized cancer treatment plan based on the molecular characteristics of the tumor rather than a one-size-fits-all treatment approach. The tumor sequencing also plays a major role in cancer research. In this paper, an improved method based on machine learning was proposed to analyze the sequencing and tumor sequencing patterns of the human gene. This proposed method analyzes the circulatory problems of patients with different tumor types for analysis in the public domain. It also constantly monitors large data sets of cancer or tumor genetic sequences to calculate tumor size and location. This allows the doctor to get an accurate report on the type of tumor and the problems it can cause to the patient. The Analysis of these datasets of cancer tumor gene sequences reveals that the genetic makeup of each patient is different and that no two cancers are the same.
164 citations
TL;DR: Systematic review and meta-analysis of experiences of nurses working during respiratory infection pandemic in hospitals providing management of the acute conditions found the nursing teams offered high-quality care despite facing significant emotional, social and physical consequences, and lack of responsiveness of formalised managerial reaction.
Abstract: Aim: To carry out systematic review and meta-analysis of experiences of nurses working during respiratory infection pandemic in hospitals providing management of the acute conditions. Background: The major portion of the health professionals working as the main frontline workers in COVID -19 pandemics and other respiratory pandemics are constituted by nurses. In recent literature there has been evaluation of the increased risk among health workers. But very few studies have been put forward which have provided data especially regarding risk among the nurses irrespective of the other health activists and analysed the experience of nurses regarding their involvement in the pandemic. Review Results: The systematic and meta-analysis contained reports from 15 qualitative research including 397 nurses. The study was primarily phenomenological in nature. The majority of the nurses were female and between the ages of twenty to fifty years. The review and meta-analysis included 136 findings of the study, 111 of which were unambiguous and 25 of which were convincing. The nursing teams offered high-quality care despite facing significant emotional, social and physical consequences, and lack of responsiveness of formalised managerial reaction.
112 citations
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TL;DR: In this paper, a triangular method is proposed which takes into account the needs of the patients, calculates the time management of the doctors and analyzes the facilities available in the healthcares.
Abstract: In general, the number of diseases is increasing in the current era. There is also a growing fear among the patients about the nature of the growing number of new diseases and their consequences. Thus the patients are interested in getting treatment from healthcares for minor physical problems. But factors such as lack of space in healthcares and lack of time for doctors make patients uncomfortable. Sometimes doctors recommend that patients come to the healthcare only for emergency treatment. In this paper, a triangular method is proposed which takes into account the needs of the patients, calculates the time management of the doctors and analyzes the facilities available in the healthcares. Designed with the help of medical IoT devices, efficient sensors fitted to patients' bodies monitor their physical condition. Furthermore based on this sensor information the doctor can provide the patient with the necessary instructions from where they were. These sensors send information directly to the healthcare when further emergency treatment is needed. Thus healthcares can make the necessary arrangements to provide the necessary treatments to the patient immediately.
85 citations
TL;DR: Since coronaviruses do not differ structurally to any great exent, the SARS-CoV-2 virus – as well as possible future mutations – will very likely be highly UV sensitive, so that common UV disinfection procedures will inactivate the new Sars- CoV- 2 virus without any further modification.
Abstract: Background: To slow the increasing global spread of the SARS-CoV-2 virus, appropriate disinfection techniques are required. Ultraviolet radianon (UV) has a well-known antiviral effect. But measurements on the radiation dose necessary to inactivate SARS-CoV-2 have not been pub- lished so far. Methods: Coronavirus inactivation experiments with ultraviolet light performed in the past were evaluated to determine the UV radiation dose required for a 90% virus reduction. This analysis is based on the fact that all coronaviruses have a similar structure and similar RNA strand length. Results: The available data reveals large variations, which are apparently not caused by the coronaviruses but by the experimental conditions selected. If these are excluded as far as possible, it appears that coronaviruses are very UV sensitive. The upper limit determined for the log-reduction dose (90% reduction) is approximately 10.6 mJ/cm2 (median), while the true value is probably only 3.7 mJ/cm2 (median). Conclusion: Since coronaviruses do not differ structurally to any great exent, the SARS-CoV-2 virus – as well as possible future mutations – will very likely be highly UV sensitive, so that common UV disinfection procedures will inactivate the new SARS-CoV-2 virus without any further modification.
49 citations
TL;DR: A novel hybrid framework based on three classifiers, including SVM, logistic regression, and random forest, is proposed in this paper and has worked well and has been compared to other methods based on several performance metrics, such as accuracy, precision, recall, and recall.
Abstract: The Sentimental Analysis approach is typically used for analyzing a user's ideas, sentiments, and text subjectivity, all of which are expressed through text. Sentimental analysis, also known as "opinion mining," is a type of data mining that follows the concept of emotional analysis presented by people in a thoughtful manner. Based on historical evidence, websites are the most effective venue for soliciting customer feedback. Existing methodologies based on sentimental analysis are ineffective. As a result, a novel hybrid framework based on three classifiers, including SVM, logistic regression, and random forest, is proposed in this paper. Based on user feedback or historical data, the hybrid model serves as an effective classifier, assisting in the development of more accurate classification results. Furthermore, the proposed model has worked well and has been compared to other methods based on several performance metrics, such as accuracy, precision, recall, and recall.
29 citations
TL;DR: There was high prevalence of typhoid fever in urban than rural in Balad City and acute infections were dominant and the most cases were in middle age groups in hot seasons.
Abstract: One thousand nine hundred and twenty individuals admitted to the general teaching hospital in Balad City, suffer from abdominal pain, fever, a headache and nausea. Acute and chronic Typhoid-patients caused by S.typhi were diagnosed according to positive blood and stool culture respectively, and using serological test IgG/ IgM. Out of total 1920 individuals, we documented 312 typhoid-patients caused by S.typhi; 209(67%) in urban and 103(33%) in rural region and there were 263(84%) acute cases and 49(16%) chronic. The results recorded 180(57.7%) male and 132(42.3%) female and the age group 31-40 was the most infected with 130 cases (41.7%). There was high incidence of typhoid fever in quarter three and two which recorded 96 (30.8%) and 95 (30.5%) cases respectively. In conclusion: There was high prevalence of typhoid fever in urban than rural in Balad City and acute infections were dominant. The most cases were in middle age groups in hot seasons.
19 citations
TL;DR: In this paper , a study aimed to look further at the immunity possessed by humans who live in rural areas compared to urban areas, and the results showed that humans living in forests have a robust immune system compared to those living in cities, so when the COVID-19 pandemic occurs, it is not a problem.
Abstract: This study aimed to look further at the immunity possessed by humans who live in rural areas compared to urban areas. The method of this research is qualitative with the literature method, in which to answer this research, the researcher looks for evidence from various international journal publications published in the last ten years. Then, to prove the above assumption, the researcher first collects evidence of study findings that sound for health reasons, then chooses to live in a peaceful and pollution-free tree area. Next, we study and analyze in-depth evaluation and coding systems to draw conclusions that answer the above issues validly and convincingly. The findings of this study are that humans who live in forests have a robust immune system compared to those who live in cities, so when the COVID-19 pandemic occurs, it is not a problem. Suggestions for the findings of this study are expected to be meaningful input for the development of environmental health sciences in further studies, both for academics and environmental health practitioners.
15 citations
TL;DR: This project aims to create a real-time Graphics User Interface based Automated Facial Recognition as well as Mask Detection System that achieves 99% accuracy.
Abstract: The COVID-19 pandemic is producing a global health pandemic. According to the World Health Organization (WHO), the utmost effective protection is to wear a face mask in crowded regions/areas. During this pandemic, it is compulsory for every person to wear a mask and maintain social distancing. In the field of Image Processing, Convolutional Neural Networks (CNNs) have risen to prominence as the most common type of image realization/recognition model. Our project's purpose is to research and assess Machine Learning (ML) technologies for identification and recognition of people wearing face masks in any pre-recorded videos, photos, or in actual-time (real- time) circumstances. Our project aims to create a real-time Graphics User Interface based Automated Facial Recognition as well as Mask Detection System. The algorithms used in the proposed methodology are Principal Component Analysis (PCA) and the HAAR Cascade Algorithm. Finally, the result is indicated by a “GREEN” color rectangle box, which would be drawn around the section of the face, which indicates that the person on the camera is wearing a mask, or a “RED” color rectangle box, which indicates that the person on the camera is not wearing a mask. This model achieves 99% accuracy.
15 citations
TL;DR: Patients with CagA strains infection are at risk of developing a duodenal ulcer and stomach cancer.
Abstract: Nearly half of the world's population is infected with Helicobacter pylori (H.pylori). A duodenal ulcer or stomach cancer can be caused by the infection by this bacterium. The aim of this work is to assess the levels of CD14 and CD163 in H.Pylori-positive patients infected with duodenal ulcer (DU) and gastric cancer (GC) and determine the prevalence of Helicobacter Pylori-oncogenic protein cytotoxin-associated gene A strains (H.pylori-CagA). This study included 89 individuals distributed as follows: 20 healthy individuals as controls and 69 patients infected with H. Pylori have been divided as follows: 27 patients infected with H.pylori only (H.Pylori+), 22 H.pylori+DU and 20 H.pylori+GC. H. Pylori-oncogenic protein cytotoxin-associated gene A strains (H-pylori-CagA) were diagnosed based on a qualitative reverse-phase Enzyme Immunoassay Technique. CD163 and CD14 were measured in all individuals' serum using the Enzyme-Linked Immunoassay (ELISA) test. Out of 69 patients infected with H.pylori, there was one CagA strain in H.pylori+; two and five strains were recorded in H.pylori+DU and H.pylori+GC, respectively. CD14 and CD163 serum concentrations were significantly higher (P≤0.05) in H. pylori+, H. pylori+DU and H. pylori+GC than in controls. Conclusions: Patients with CagA strains infection are at risk of developing a duodenal ulcer and stomach cancer.
13 citations
TL;DR: Entrepreneurship refers to a person usually someone who wants to implement that idea with the idea of disrupting the market with a new product or service as mentioned in this paper . But they are also responsible for the risks involved.
Abstract: Entrepreneurship refers to a person usually someone who wants to implement that idea with the idea of disrupting the market with a new product or service. Perfect for research and development with practices, entrepreneurs are new, they bring innovations that open new ventures, markets, products and technology Opens the doors. Entrepreneurs need to play a role in solving problems that are still unresolved by existing products and technology. Traditionally, Entrepreneurship is classified into four main categories: small businesses, scalable start-ups, large companies and social entrepreneurs. These models cover the basics of starting a business and focus more the company is more than the qualities of an entrepreneur. An entrepreneur will usually start a new business and run it. At the same time, they are responsible for the risks involved. Entrepreneurship is the process of starting a new business, which involves risks and opportunities preparing one for both. An entrepreneur coordinates essential needs a company. Make sure you do the work, and no one will look over your shoulder. As an entrepreneur, you must learn to take responsibility for yourself, otherwise you will not succeed.
TL;DR: This study proposes employing Gabor Features (GF) and three distinct machine learning algorithms: Random Forest (RF), Support Vector Machine (SVM), and Deep Neural Net, a more efficient way of liver and tumour segmentation from CT images (DNN).
Abstract: Automatically segmenting the liver is a challenging process, and segmenting the tumour from the liver adds another layer of complexity. Because of the overlap in intensity and fluctuation in location and form of soft tissues, segmenting the liver and tumour from abdominal Computed Tomography (CT) images merely based on grey levels or shape is very undesirable. To address these challenges, this study proposes employing Gabor Features (GF) and three distinct machine learning algorithms: Random Forest (RF), Support Vector Machine (SVM), and Deep Neural Net, a more efficient way of liver and tumour segmentation from CT images (DNN). The texture data produced by GF should be consistent and homogeneous across numerous slices of the same organ. In the first, pixel level features are extracted using an array of Gabor filters. Second, utilising three separate classifiers: RF, SVM, and DNN trained on GF, liver segmentation is conducted to remove liver from an abdominal CT picture. Finally, using GF and the same set of classifiers, tumour segmentation is performed on the segmented liver image.
TL;DR: The article reveals the content and essence of digital technologies, which are introduced in medicine, require training in the provision of medical care, and analyzes the directions of development of medicine in the context of philosophical reflection, and tests the effectiveness of their use.
Abstract: A concise and factual abstract The purpose of scientific research is to trace the patterns of change in the development of education and medicine and justify the direction in which they will develop so that people will be ready for rapid change, and education prepares professionals capable of implementing new digital technologies that improve human health. The methodology of the study is to use such methods as analysis and synthesis, categorical analysis, comparative analysis, sociological method, and other methods of scientific knowledge. The purpose of the study was to identify patterns of change in the development of medicine and education due to the impact on them of digital technology. The article reveals the content and essence of digital technologies, which are introduced in medicine, require training in the provision of medical care; analyzes the directions of development of medicine in the context of philosophical reflection, and tests the effectiveness of their use. The practical significance of the study lies in the philosophical understanding of the interaction between education and medicine, according to which the future of our civilization, based on cellular medicine, the discovery of stem cells, which are developed using modern technology and new standards of medicine.
TL;DR: In this paper , the authors analyze the implementation of the KRISNA Special Allocation Fund in budget planning at the Regional Development Planning Agency of Rokan Hilir Regency.
Abstract: This study aims to analyze the implementation of the KRISNA Special Allocation Fund in budget planning at the Regional Development Planning Agency of Rokan Hilir Regency. The Collaborative Application System for Planning and Budgeting Performance Information functions to carry out budgeting or proposals for the use of website-based Special Allocation Funds since 2018 in Rokan Hilir Regency. This research uses qualitative research method with descriptive research type. The main informants in this research were the Head of Bappeda, Head of Bappeda Division, Head of Sub Division of Bappeda, Head of Education Office, Head of Department of Housing and Settlements Service, and Head of Agriculture Service in Rokan Hilir Regency. Sample selection is done by (purposive sampling). Based on the results of research and data analysis, it shows that: (1) The implementation of the application system policy since the second quarter for the 2019 budget still has several question marks, including those related to the amount of funds approved by the central government which is not fixed.
TL;DR: Several advantages of using digital applications in public health services in the current digital era are found, including that digital applications have been able to innovate the work of paramedics in improving services to the public about health.
Abstract: This study explored the advantages of using digital applications in public services in the era of automation. We have searched data in many applications, including scientific journals, books, academic residences, and many telling applications in the medical world. A series of data studies involving coding system analysis, evaluation, and interpretation, became more in-depth so that the data we found could be digested to answer this research question. Our data search was conducted electronically on secondary data published from 2010 to 2022. While the format of this study report is suitable from problem formulation to reporting on water, we chose a descriptive qualitative design with a phenomenological approach, trying to obtain the broadest possible data that is useful in answering questions of research questions. Based on the data and discussion, this study found several advantages of using digital applications in public health services in the current digital era. The reason is that digital applications have been able to innovate the work of paramedics in improving services to the public about health. Hopefully, this salary buddy will be full of supporting data for future health and technology studies.
TL;DR: This research focused on neurological problems in COVID-19 patients, as well as probable SARS-CoV-2 infection routes like hematogenous, direct/neuronal, lymphatic tissue, cerebrospinal fluid, or infiltration by infected immune cells, and inhibition of the NF-B signaling pathway shows promising therapeutically.
Abstract: The current COVID-19 epidemic caused by the new SARS-CoV-2 has severely harmed global healthcare (severe acute respiratory syndrome coronavirus). COVID-19's pulmonary and cardiovascular effects have been known from its inception, but its causes, mechanisms, and neuropath logical consequences remain unknown. Our research focused on neurological problems in COVID-19 patients, as well as probable SARS-CoV-2 infection routes like hematogenous, direct/neuronal, lymphatic tissue, cerebrospinal fluid, or infiltration by infected immune cells. Late December 2019 in Wuhan, China, a mysterious viral pneumonia struck. The disease was caused by a new corona virus. Corona virus infection spread rapidly from person to person in 2019. The WHO has called it a global public health emergency (WHO). Activation of NF-B in SARS-CoV-2 infection may be linked to immune cell pathogenicity, cytokine storms, and multi-organ failure. COVID-19's inhibition of the NF-B signaling pathway shows promising therapeutically. Inhibiting IKK phosphorylation, a critical downstream consequence of the NF-B signaling cascade, reduces COVID-19 levels. All three disorders have been linked to COVID-19 gene mutations. This study provides a biological basis for future research on COVID-19-related neurological disease. W
TL;DR: IL-4, IL-17, CD8 and CD22 serum levels increase in typhoid-patients caused by S.typhi in humans, and a significant increase in all markers in acute and chronic infections as compare with control is proved.
Abstract: A case-control study was carried out in the General Teaching Hospital in Balad City, Iraq. Eighty-eight male and female were included in this study; 58 typhoid-patients infected with S.typhi and 30 healthy individuals as controls. Acute typhoid-patients have been diagnosed according to positive blood culture and IgM and chronic typhoid-patients have been diagnosed according to positive stool culture and IgG. Four immunological markers have been measured in all individuals' serum; interleukin 4 (IL-4), interleukin 17 (IL-17), cluster of differentiation 8 (CD 8) and cluster of differentiation 22 (CD 22) using an Enzyme-Linked Immunosorbent Assay (ELISA). We diagnosed 32 and 26 patients infected with acute and chronic infection respectively, the results proved a significant increase (P-value=<0.05) in all markers in acute and chronic infections as compare with control. A significant differences P-value (0.0003 and <0.0001) has been proved between acute and chronic infection in IL-4 and IL-17 respectively. While, there was no significant differences P-value (0.13 and 0.32) between acute and chronic infection in CD8 and CD22 respectively. Conclusions: IL-4, IL-17, CD8 and CD22 serum levels increase in typhoid-patients caused by S.typhi in humans.
TL;DR: In this paper , the authors assess the effects of blend learning on the learning outcomes of Computer and Basic Network courses during the Covid-19 Pandemic and find that it is difficult and timeconsuming to adapt to the fact that not all parents are able to use IT and internet-based work gadgets.
Abstract: The Covid-19 pandemic is increasing, and the online learning system can facilitate learning and make it easier for students and teachers. This research intends to assess the effects of Blend Learning on the learning outcomes of Computer and Basic Network courses during the Covid-19 Pandemic. This study employs literature research, with data collected from various publications and books assessed in light of existing issues. According to the findings of this study, there are a number of issues from the perspectives of teachers, students, and parents. During the current pandemic, teachers must be able to adapt to blended learning methods. Changes to the learning environment will impact students' psychological issues. Students suffer the stigma that learning activities school must take place at educational facilities; if they occur at home, it is assumed that they are on vacation. It is difficult and time-consuming to adapt to the fact that not all parents are able to use IT and internet-based work gadgets. Due to the fact that each student has a distinct learning style, this obstacle can be circumvented through the use of a combination of learning material.
TL;DR: For brain tumor detection, marker based watershed classification on MRI images with the use of gray scale images was performed, then the tumor's location and size were determined by noise removal and morphological operations.
Abstract: Medical imaging is extremely important in the domain of medicine. Image classification is now utilized to distinguish aberrant tissues from healthy tissue in brain imaging. The brain tumor is identified from MRI images by using some classification techniques, where the area of the tumor as well as the tumor size is detected. Automatic tumor detection using brain MRI is efficient and time- saving, assisting the neurologists in diagnosis. Tumors can increase the risk of cancer, which is the most common cause of death or major cause of mortality worldwide. To detect brain tumors at the moment, effective automation of tumor detection is essential. Marker based Watershed algorithm is a typical segmentation technique which is used for identifying brain tumors. For brain tumor detection, we performed marker based watershed classification on MRI images with the use of gray scale images, then by noise removal and morphological operations. The steps in the methodology are as follows: Gray-level and sharpening was used in the pre-processing, and the image was segmented using thresholding as well as the marker based watershed algorithm, and the CNN was used for classifying the images. Finally, the tumor's location and size were determined.
TL;DR: The Internet of Things has become one of the most important technologies and everyday items combine Kitchen appliances, cars, Thermostats, baby screens through devices embedded on the Internet, making seamless communication between people, processes and objects possible.
Abstract: The Internet of Things (IoT) Physical objects (or Groups of such materials) sensors, processing Skills, software and the Internet or other Communication connects with other devices and systems and other in exchange via networks Described as technologies. Invalid due to Internet of Things Devices Considered by name, they are associated with the public Internet. No need to connect, just the network Should only be connected and can be addressed individually. The ability to provide Machinery and digital machines, Objects, animals or personal Identifiers (UIDs) and from man to man or without the need for man-to-computer Data transfer over a network communication. In the last few years, IoT too it is too much 21st century Has become one of the most important technologies. Nowadays, everyday items combine Kitchen appliances, cars, Thermostats, baby screens through devices embedded on the Internet, making seamless communication between people, processes and objects possible. With Low-cost computing, cloud, big data, analytics and mobile technologies, physics minimal human intervention data share and let’s collect. In this high-connected world, digital Between system connected objects collaborate.
TL;DR: A proposed DLNNSVM approach outperforms existing learning approaches for ovarian cyst classification and is better in precision, recall, accuracy and f1-measure.
Abstract: This research presents a solution for classifying ultrasound diagnostic images describing five types of ovarian cyst as Hemorrhagic cyst, PCOS, Dermoid cyst, Endometriotic cyst, Malignant cyst. This work proposed a hybrid algorithmic technique for ovarian cyst image classification. Automatic feature extraction is implemented using recent deep learning neural network (DLNN) that extracts images. The DLNN consists of three dense layers. A proposed DLNNSVM approach outperforms existing learning approaches for ovarian cyst classification. Compared with DLNN and DLNNSVM, the performance of proposed method is better in precision, recall, accuracy and f1-measure.
TL;DR: A systematic survey on feature extracting and classifying the medical images using deep learning methods using supervised and poorly supervised learning techniques is presented.
Abstract: Deep Learning has indeed been widely used in many fields/areas of medicinal images classification, and a large number of publications have been published documenting its success. The key for achieving effective diagnosis and therapy is accurate characterization of medical pictures. However, because image interpretation is highly dependent on the subjective opinion of doctors, the results of image processing vary greatly amongst clinicians at different levels. Picture classification, target identification, and image analysis have all improved dramatically in recent years with environmental image data sets in domain of Image Processing. In this paper, we have presented a systematic survey on feature extracting and classifying the medical images using deep learning methods. Two new ideas are presented in this work. First and foremost, we classified presently trendy publications in a multi-level configuration. Second, this research article concentrates on supervised and poorly supervised learning techniques.
TL;DR: In this article , the authors employed the golden ratio to alleviate transportation concerns and determined the optimal cost of converting amounts from supply to supply peaks, where desired results have been obtained which are solutions that are close to the optimal solution.
Abstract: Transportation problem is critical component of optimization field, as it aims to reduce the total cost of distribution from a set of sources to a set of destinations. Numerous transportation alternatives have been examined in the literature. Certain strategies, such as the northwest corner method (NWC), the low cost method (LCM), and the Vogel approximation method (VAM) were designed to identify the simplest possible solution, while others were designed to identify the optimal solution. The Golden Ratio is employed in this study to approximate the ideal solution. This technique employs the golden ratio to alleviate transportation concerns (1.61803). To begin with, the said ratio is raised to the second lowest cost and we determine the optimal cost of converting amounts from supply to supply peaks, where desired results have been obtained which are solutions that are close to the optimal solution.
TL;DR: This survey paper analyzes all the widely used Machine Learning Approaches for Sentiment Analysis to create an accurate and precise model.
Abstract: Sentiment Analysis or Opinion Mining is popular task of Natural Language Processing (NLP) performed on textual data generated by users to know the orientation or sentiment of the text. To perform Sentiment Analysis, it is critical to create an accurate and precise model, machine learning techniques are heavily utilized to build an accurate model. Deep learning and transfer learning techniques have been found to have increased utilization and better results, making them one of the most popular research areas around the world. Hotel and restaurant industries analyze reviews to obtain a deeper understanding of their client’s needs, likes and dislikes, whereas specialists use Twitter data and stock market news items to forecast stock market trends. Machine Learning algorithms are most essential part of a Sentiment Analysis model, this survey paper analyze all the widely used Machine Learning Approaches for Sentiment Analysis. A brief introduction on Methodology for Sentiment Analysis is given along with conclusion and future scope and in the field of Sentiment Analysis.
TL;DR: In this paper , a pilot study was conducted to identify the level of understanding of future elementary school teachers of the phenomenon of "communicative competence" and its importance for further professional activity, and a survey of students-future teachers of primary classes on the understanding of the essence and necessity of formation of communicative competence during professional training in higher educational institutions of Ukraine is presented.
Abstract: The article is devoted to the problem of forming communicative competence of future elementary school teachers. The objectives of the study were to highlight the conceptual pedagogical foundations and components on which the process of forming communicative competence in future elementary school teachers is based. The task of scientific exploration was to conduct a pilot study to identify the level of understanding of the future elementary school teachers of the phenomenon of “communicative competence” and its importance for further professional activity. The organized research was based on theoretical (study, analysis, systematization, and generalization of scientific-pedagogical, psychological, and methodological literature on the problem under study) and empirical (diagnostic evaluation, questioning, monitoring and educational experiment) methods. The concepts of “competence”, “competence”, “communicative competence”, “communicative competence of a future elementary school teacher” were revealed. The problem of development of communicative competence as a professional value of a modern elementary school teacher is outlined. The results of the survey of students-future teachers of primary classes on the understanding of the essence and necessity of formation of communicative competence during professional training in higher educational institutions of Ukraine are presented.
TL;DR: In this article , the authors highlight one of the important heterocyclic rings i.e., Morpholine and highlight its applicability for more and more applicability in various applications.
Abstract: The invention of newer chemical entities, which have some therapeutically worth is always a great challenge. It is no doubt that it is a lengthier process. We have several drugs in the market for treatment of wide variety of diseases. The marketed drugs available may be heterocyclic or non-heterocyclic derivatives. Always it was found that heterocyclic derivatives have wide variety of pharmacological activity. The intension of this review is to highlight one of the important heterocyclic rings i.e.: Morpholine. Several works have been done on this nucleus, which should be enlighten for more and more applicability.
TL;DR: In this paper , a review summarizes the better nanotechnological systems that can be used in future for better and effective treatment of acne, including lipid nanocarriers, which can promote skin hydration, enhance drug permeation, improve its targeting properties and retention time on the skin, increase drug solubility and protect it from degradation, provide sustained drug release and reduce dosing frequency.
Abstract: Acne is one of the most common chronic inflammatory dermatological disorder associated with multifactorial pathogenesis. Approximately 95 % of the population suffers from it at some point in their lifetime. Antibiotics, acids, benzoyl peroxide, and retinoids are the most commonly drugs used for the treatment of acne. However, conventional formulations of these drugs are associated with undesirable toxicities, inadequate penetration across stratum corneum, short retention time of the drug in the target site, and poor aqueous solubility of drugs, that limited their medicinal applications. As a consequence pharmaceutical researchers are turning towards novel drug delivery systems to overcome these limitations.With respect to their small particle size, lipid occlusive nature and unique surface characteristics, lipid nanocarriers can promote skin hydration, enhance drug permeation, improve its targeting properties and retention time on the skin, increase drug solubility and protect it from degradation, provide sustained drug release and reduce dosing frequency. The current review summarizes the better nanotechnological systems that can be used in future for better and effective treatment of acne.
TL;DR: This study provides a method for recognizing exudates and veins in retinal images for the purpose of examining the retinal vasculature and proposes recognizing diabetics by fundus retinal picture arrangement utilizing return for capital invested.
Abstract: Diabetic Retinopathy (DR) is quite possibly the main widely recognized diabetic disease found in the vast majority. Advancement of diabetic retinopathy is grouped by its seriousness. Be that as it may, critical lacks of master spectators have incited supercomputer helped observing frameworks to distinguish the DR. In retinopathy, the kind of vascular organization of the natural eye is a crucial indicator element. This study provides a method for recognizing exudates and veins in retinal images for the purpose of examining the retinal vasculature. Convolution Neural Network (CNN) is used for image identification and preparation of retinal images following image processing stages to arrange the retinal fundus images. The proposed recognizing diabetics by fundus retinal picture arrangement utilizing return for capital invested (Region of Interest) assumes significant parts in recognition of certain illnesses in beginning phase diabetes by contrasting its exactness and existing strategies like the conditions of retinal veins.
TL;DR: In this paper , the authors investigate the influence that marketing communication and information sharing have on the performance of businesses and investigate the relationship between marketing communication, information sharing, client retention, and personalization, as well as the success of the firm.
Abstract: The purpose of this research is to investigate the influence that marketing communication and information sharing have on the performance of businesses. The relationship between marketing communication, information sharing, client retention, and personalization, as well as the success of the firm, is investigated in this approach. In this research endeavour, a questionnaire was the instrument of choice for data collecting. A questionnaire was constructed with the help of previously discovered scale items relevant to marketing communication, information sharing, customer retention, personalization, and business performance. This led to the development of the questionnaire. The staff members of India's small and medium-sized firms (SMEs) each received one of the 500 questionnaires that were handed out to them. Partial Least Square was the statistical tool that was used to do the analysis of the data (PLS). It has been discovered that effective marketing communication has a beneficial effect on the retention of existing customers, which in turn leads to improved company performance. Additionally, the exchange of information has a beneficial effect on customisation, which ultimately leads to the performance of the company.
TL;DR: Experimental results validate that the MISR algorithm outperforms the state-of-the-arts in terms of both reconstruction accuracy and computational efficiency.
Abstract: This paper mainly focus on multispectral image for Entertainment purpose, with such application the quality of the image is an important factor that affects the accuracy of the recognition. Due to hardware limitation, multispectral imaging device may fails to generate high resolution (HR) image. In order to overcome the issue, here we proposes multispectral image super-resolution algorithm (MISR), by fusing low-resolution (LR) multispectral images. In this algorithm the computed response function is used to fuse the multiple images into a single high dynamic range radiance image. It deals with the radiance of the images by mapping. The referred algorithm solves the pre-processing and registration. It uses CNN model to fuse the multiple images into a single high dynamic range image. This fusing technique establishes the common points in the image. Experimental results validate that the MISR algorithm outperforms the state-of-the-arts in terms of both reconstruction accuracy and computational efficiency.