Journal of Current Science and Technology最新文献

{"title":"A systematic survey on deep learning techniques for chest disease detection using chest radiographs","authors":"Akanksha Soni, Avinash Rai","doi":"10.59796/jcst.v13n2.2023.1744","DOIUrl":"https://doi.org/10.59796/jcst.v13n2.2023.1744","url":null,"abstract":"The lung is one of the most sensitive internal organs of the human body that gets infected by constant exposure to chemicals, particles, and infectious organisms in the atmospheric air. Due to this, the most dangerous chest diseases take place which are the leading cause of human disability and death throughout the world. These pulmonary diseases can be recognized by medical imaging techniques i.e. Chest radiography, Computed tomography, Pulmonary and bronchial angiography, Magnetic resonance imaging, Ultrasonography, and Nuclear medicine techniques. A massive amount of chest reports are generated every day that contain a large amount of anatomical and potentially pathological information, but manual detection and classification of chest abnormalities are considered a tedious and time-taking task. In addition, it also requires skilled radiologists as these reports are often difficult to read and differentiate the pathologies of the chest. To eradicate this issue and give a value-added solution; artificial intelligence and deep learning-based algorithms show excellent performance and have proven their effectiveness for object recognition and image segmentation. The primary aim of this study is to present a comprehensive analysis of the deep learning approaches used to identify various types of pulmonary pathologies on CXRs. In addition, we provide a detailed analysis of the most popular open-access CXR datasets, taxonomy of the state-of-the-art works to assist the researchers in preparing the plan for their research contribution, and discuss potential future research directions in this field. More than 350 research papers from various indexing services, including Web of Science, Scopus, PubMed, and IEEE, were considered for this review article. After several selection parameters, it is observed that most of the literature focuses on the DL approach with CXRs. However, few publications have focused on CT scans and Ultrasound images. ","PeriodicalId":36369,"journal":{"name":"Journal of Current Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83986334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced artificial transgender longicorn algorithm & recurrent neural network based enhanced DC-DC converter for torque ripple minimization of BLDC motor","authors":"P. Rajesh, Francis H. Shajin, V. Ansal, Vijay Kumar B","doi":"10.59796/jcst.v13n2.2023.1735","DOIUrl":"https://doi.org/10.59796/jcst.v13n2.2023.1735","url":null,"abstract":"This paper proposes an enhanced DC-DC converter with hybrid control method for torque ripple minimization of BLDC motor. Initially, a BLDC motor is controlled with an enhanced Cuk converter. The application of a switched inductor is used to update the Cuk converter operation. In this method, the control mechanism incorporates two control loops, namely, the speed control loop and torque control loop, which are utilized to recover the execution of BLDC. Thus, the proposed system is the combined performance of the Enhanced Artificial Transgender Longicorn Algorithm (EATLA) and Recurrent Neural Network (RNN) to improve control loop operations. In the Artificial Transgender Longicorn Algorithm (ATLA), the crossover and mutation approach are used as part of the scattering process to build the accuracy search process. In this article, the EATLA-RNN algorithm for limiting speed and torque error of BLDC motor is explored. However, the proposed method output is subject to input of the speed and torque controllers. The proposed topology with the controller is executed on MATLAB/Simulink workstation, and torque ripple minimization is analyzed toother existing approaches such as particle swarm optimization (PSO) and bacterial foraging (BF) algorithm.","PeriodicalId":36369,"journal":{"name":"Journal of Current Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76998302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phytochemical screenings and evaluations of antibacterial and antioxidant activities of methanolic leaf extract of Senna auriculata (L). Roxb","authors":"Poornasundari Baluchamy, Arivoli Subramanian","doi":"10.59796/jcst.v13n2.2023.1734","DOIUrl":"https://doi.org/10.59796/jcst.v13n2.2023.1734","url":null,"abstract":"The current study examineed the \"Phytochemical contents, antimicrobial and antioxidant activities of the methanolic leaf extract of S. auriculata\". Methanol was used to extract a leaf sample from a plant. The phytoconstituents and functional groups in the leaf extract had been investigated using Gas Chromatography-Mass Spectroscopy (GC-MS) and Fourier Transform Infrared (FTIR) analysis. Concurrently, the agar well-plate method was used to assess antimicrobial activity against ten bacterial strains. DPPH (1,1-diphenyl-2-picrylhydrazyl), reducing power activity, phosphomolybdenum activity, hydrogen peroxide activity, and nitric oxide inhibitory activity were employed to assess antioxidant activity. Carbohydrates, protein, tannins, saponins, and terpenoids were found in the phytochemical analysis. The GC-MS study of the leaf extract revealed the presence of 13 major bioactive substances with antimicrobial, free radical scavenging, and anticancer properties. The appearance of distinctive peak values with various functional groups, such as alcohol, alkanes, aromatic, esters, and amines, was indicated by the FTIR result. The leaf extract exhibited a potent antibacterial effect against all pathogens tested. The highest activity against A. hydrophila (15±0.6 mm) was found at a 100 µg/mL concentration. The antioxidant properties of leaf extract increased as concentration was increased. The leaf extract contains 108.13 mg GAE/g and 61.25 mg RE/g of phenolic and flavonoid content, respectively. Finally, the methanolic leaf extract of S. auriculata was found to have powerful antibacterial and antioxidant features and could be a valuable source of natural compounds for creating new medications. Although S. auriculata has been extensively studied for its antibacterial activity against pathogenic organisms, the findings showed that it is also effective against the fish pathogen A. hydrophila. More investigation is required to find and identify the biologically active compounds responsible for the plant’s antibacterial and antioxidant activity.","PeriodicalId":36369,"journal":{"name":"Journal of Current Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73732170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Knowledge-based checkpointing strategy for spot instances in cloud computing","authors":"Sumit Tomar, Ashish Kumar Mishra, Dharmendra K Yadav","doi":"10.59796/jcst.v13n2.2023.1754","DOIUrl":"https://doi.org/10.59796/jcst.v13n2.2023.1754","url":null,"abstract":"The Amazon EC2 offers spot-priced virtual machines (VMs) at a reduced price compared to on-demand and reserved VMs. However, Amazon EC2 can terminate these VMs anytime due to the spot price and demand fluctuation. Using spot VMs results in a longer execution time and disrupts service availability. Users can use fault-tolerant techniques such as checkpointing, migration, and job duplication to mitigate the unreliability of spot VMs. In this paper, a knowledge-based checkpointing strategy is proposed to minimize the overall checkpointing overhead during the execution of jobs. The proposed scheme uses real-time price history to decide when to take a checkpoint. Results show that the proposed approach can significantly reduce the turnaround time by 18% compared to Hourly Checkpointing Strategy and 9% compared to Rising-Edge Checkpointing Strategy. One can also achieve 54% to 78% reliability with a cost saving of 78% for the workload used with the described approach.","PeriodicalId":36369,"journal":{"name":"Journal of Current Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78828841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal feature selection and detection of sickle cell anemia detection using enhanced whale optimization with clustering based boosted C5.0 algorithm for tribes of Nilgiris","authors":"C. Maria Sheeba, K. Sarojini","doi":"10.59796/jcst.v13n2.2023.1737","DOIUrl":"https://doi.org/10.59796/jcst.v13n2.2023.1737","url":null,"abstract":"Degradation of red blood cells (RBC) causes many diseases, like sickle cell anemia. Diagnosing this disease takes more time because peripheral blood samples must be examined under the microscope. Since the isolated RBC observation is subjective and high error rate leads to reduce the accuracy, the technology is needed to perform this approach. To fulfil these requirements, optimal feature selection and detection of sickle cell anemia using enhanced whale optimization with clustering based boosted C5.0 algorithm in tribes of Nilgiris is proposed in this manuscript. The input dataset is taken from real data set via non-government organization named NAWA (situated in Kotagiri). The reason behind of Nilgiri region is considered in this work is a collection of sickle cell anemia test results of the tribe people who lives in different areas of Nilgiri region. These images are pre-processed using wavelet packet transform cochlear filter bank method to eradicate the noises and to improve the superiority of image. After that, the features are extracted using force-invariant improved feature extraction method. To select the optimal features, enhanced whale optimization (EWO) algorithm is used. These optimal features are classified utilizing clustering based boosted C5.0 algorithm. The proposed method is activated on PYTHON. The proposed method shows 52.32%, 43.78%, 32.78% and 45.90% higher accuracy compared with the existing methods, such as RGSA-MLP-SCA, CRFA-SVM-SCA, AO-LSTM-SCA and BOA-CNN-SCA.","PeriodicalId":36369,"journal":{"name":"Journal of Current Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75169075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Visualisation and prediction of Covid-19 data using random forest regression","authors":"D. Sumathi, T. Poongodi, P. Suresh, S. Karthikeyan, N. Sree Chand1","doi":"10.59796/jcst.v13n2.2023.1738","DOIUrl":"https://doi.org/10.59796/jcst.v13n2.2023.1738","url":null,"abstract":"The outbreak of COVID-19 has spread among several parts of the world. The data pool increases tremendously, which needs excellent attention by researchers of various domains to analyze and determine the measures to handle it. Hence, researchers worldwide are looking into Artificial Intelligence (AI) to resolve the challenges due to this COVID-19. It could be stated that AI can examine huge data mounds so that several new findings can be determined. AI could be deployed in various fields, such as the pharmaceutical industry, the analysis and development of vaccines and antibodies, and drug designing. Due to the impressive progress that AI has made in the latest few years, still, it proves to be the essential quality of the technology and evidence of humans' creativity towards the contribution of developing tools and products which could be statistically and computationally complex. It is observed that AI technology aids in tracing the outburst, patient diagnosis and fastening the procedure of finding a treatment. This work provides an overview of COVID-19, along with the convergence of technologies that could be applied in various sections to handle this pandemic. An extensive exploration of multiple techniques and models has been implemented for the prediction of COVID-19 has been done. Additionally, numerous models have been deployed for predictions of covid states. It has been inferred that XGBoost showed considerable progress in the prophecy.","PeriodicalId":36369,"journal":{"name":"Journal of Current Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87182366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of 2% w/w sodium fluoride oral gels for prevention of dental caries in patients with xerostomia","authors":"Chidchonnee Kosolpatanadurong, Chirasak Kusonwiriyawong","doi":"10.59796/jcst.v13n2.2023.1743","DOIUrl":"https://doi.org/10.59796/jcst.v13n2.2023.1743","url":null,"abstract":"For prevention of dental caries in xerostomic patients, 2% w/w sodium fluoride oral gel is frequently prescribed; however, the product has not been officially approved for clinical use in Thailand. Therefore, this study aimed to develop 2% w/w sodium fluoride oral gels dispensed specifically to patients in Rajavithi Hospital. Both single and combined gel bases were prepared from different gelling agents, including gelatin, xanthan gum, hydroxypropyl methylcellulose, sodium carboxymethylcellulose, and Carbopol 940P. They were subsequently characterized according to their physicochemical properties, i.e., clarity, spreadability, pH values, and apparent viscosity. All the gel bases were clear viscous liquids of good spreadability, except the xanthan gum gel bases, which were slightly cloudy. The pH values indicate that the gelatin, xanthan gum, and Carbopol 940P gel bases were acidic, while the cellulose gel bases were neutral. The apparent viscosity ranged from 3 to 11.5 x 105 cPs, depending mainly on type and concentration of the gelling agents. After preparation, the gel bases were then incorporated with 1 M pH 7.4 phosphate buffer solution to the final concentration of 5% w/w. Macroscopic characteristics of the buffered gel bases were generally unchanged, except for the apparent viscosity, which decreased slightly. Sodium fluoride was subsequently added to the selected buffered gel bases. The resulting sodium fluoride gels were neutral and transparent viscous liquids of good spreadability and exhibited good stability against the heating-cooling cycle and accelerated testing. Thus, it is conceivable that 2% w/w sodium fluoride oral gels with acceptable physicochemical characteristics and excellent stability were successfully developed.","PeriodicalId":36369,"journal":{"name":"Journal of Current Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82567026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physical and psychological effects of post-COVID-19 syndrome on patients in Bandar Lampung, Indonesia: a descriptive prospective study","authors":"Dyah Wulan Sumekar Rengganis Wardani, Bayu Anggileo Pramesona, Yuni Nirmala","doi":"10.59796/jcst.v13n2.2023.1746","DOIUrl":"https://doi.org/10.59796/jcst.v13n2.2023.1746","url":null,"abstract":"Although there have been many cases of reports on post-COVID-19 syndrome (PCS) worldwide, studies related to the long-term physical and psychological effects of COVID-19 have not been widely conducted in Indonesia. This study aimed to identify PCS's long-term physical and psychological symptoms in patients who had confirmed COVID-19. This descriptive prospective study was conducted from April to June 2022 with 79 respondents who had been confirmed positive for COVID-19 and whose medical records were reported at one of the public health centers in Bandar Lampung, Indonesia, from January to December 2020 by purposive sampling. The COVID‐19 Yorkshire Rehabilitation Screening Scale (C19‐YRS) was used to identify PCS symptoms. Descriptive analysis was used to analyze the frequency distribution data and the percentage of PCS cases. The results showed that 20.3% of respondents had at least one PCS symptom. Nearly a third (32.9%) of the respondents had deteriorated general health conditions after being infected with COVID-19. The most common physical symptoms of PCS were shortness of breath when climbing stairs (6.3%), resting, dressing, changes in throat sensitivity, voice (each 5.1%), swallowing problems, and pain (each 2.5%). At the same time, the most psychological effects of PCS were illness-related nightmares (12.6%), PTSD (11.4%), anxiety (7.6%), still avoiding thoughts of their illness (2.5%), and depression (1.3%). With varying severity, the physical and psychological symptoms of PCS were still felt by respondents. Although the symptoms of PCS are relatively mild, the follow-up treatment of post-recovery patients after being diagnosed with COVID-19 is crucial.","PeriodicalId":36369,"journal":{"name":"Journal of Current Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79271226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preparation and characterization of akara and senke cakes made from cowpea flour paste","authors":"Deborah Oluyemisi Opaleke, Tunrayo Taibat Adebisi, Olayinka Ramota Karim, Ayodele Adenike Oluwadare, Isoken Ihensekhien, Simbiat Mojeed Lawal","doi":"10.59796/jcst.v13n2.2023.1750","DOIUrl":"https://doi.org/10.59796/jcst.v13n2.2023.1750","url":null,"abstract":"Despite commercial acceptability as diets in some West African and South American households, the bulk of the world's population does not consider akara and senke to be foods due to a lack of scientific proof demonstrating their intrinsic benefits and formulation processes. The focus of this study, therefore, was to prepare and characterize akara and senke developed from dehulled (DH) and undehulled (UDH) cowpea. Sample A (100% DH), Sample B (100% UDH), Sample C (25% UDH: 75% DH), Sample D (75% UDH:25% DH), Sample E (50% UDH:50% DH). Analysis was carried out using standard methods. Results showed that samples E and A had the highest and lowest values for oil absorption capacity (OAC), water absorption capacity (WAC), and loose-packed density (LBD), respectively. Protein (17.40%), carbohydrate (42.33%), and energy (541.72 kcal/g) were the highest for samples A, D, and C, respectively. The fat content (14.44%) was the lowest in sample D, while sample B had the lowest ash content (3.18%). While sample C had the highest L value (50.94), a (13.14) and b (-6.13) were the lowest in sample A. The sensory qualities showed that senke made from Sample E had the highest ratings (except for color) in all the sensory parameters. The average overall acceptability was 7.13, and statistical analysis revealed no significant (p<0.05) differences among the samples. Formulation of dehulled and undehulled cowpea flour paste as cakes has intrinsic nutritional benefits and their consumption should be encouraged globally.","PeriodicalId":36369,"journal":{"name":"Journal of Current Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84544576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Supramolecular structure of five-coordinate [(4-methyl-2,6-dinitrophenolato)(octaethylporphinato)iron(III)] heme complex","authors":"Saifon A. Kohnhorst","doi":"10.59796/jcst.v13n2.2023.1752","DOIUrl":"https://doi.org/10.59796/jcst.v13n2.2023.1752","url":null,"abstract":"The crystallographic and spectroscopic characterization of the phenolate complex of [(4-methyl-2,6-dinitrophenolato)(2,3,7,8,12,13,17,18-octaethylporphinato)Fe(III)], [FeIII(OEP)(DNOC)] is reported. The 4-methyl-2,6-dinitrophenol (DNOC) ligand was coordinating with the FeIII(OEP) moiety through the phenylato-O-atom. The complex crystallizes in the triclinic P-1 with Z=2. The crystallographic information showed the average Fe—Np distance of 2.053(18) Å, with the Fe displacement from the 24 atoms porphyrin plane of 0.41(6) Å, and the Fe—O distance of 1.881(15) Å showing a five-coordinate square-pyramidal geometry. The characteristic of the formation of the Fe—O bond was found near 537 cm-1 for IR spectra and the n4 band was near 534 cm-1 for Raman spectra. The major supramolecular interactions involved an intermolecular hydrogen bond C—H···O with a minimum distance of 2.732(5) Å, and the shortest plane-plane contact distance of 3.689(3) Å. The FT-IR characteristic showed the new band near 3400 cm-1, which was broadened due to the formation of hydrogen bonds. The role of these weak C—H···O hydrogen bonds concerted to stabilized the crystal packing in the heme complex. Thus, the number of excellent hydrogen bond acceptors of the axial ligand contributes to its supramolecular structure.","PeriodicalId":36369,"journal":{"name":"Journal of Current Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81929964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}