Pub Date : 2022-07-30DOI: 10.56828/jser.2022.1.2.4
J. Cheng
{"title":"Improved Method of Filling Incomplete Information in Network Database Simulation","authors":"J. Cheng","doi":"10.56828/jser.2022.1.2.4","DOIUrl":"https://doi.org/10.56828/jser.2022.1.2.4","url":null,"abstract":"","PeriodicalId":13763,"journal":{"name":"International Journal of Applied Science and Engineering Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81129023","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}
Pub Date : 2022-07-30DOI: 10.56828/jser.2022.1.2.2
D. Taniar
{"title":"Particle Swarm Optimization Algorithm for Data Distribution Model Design","authors":"D. Taniar","doi":"10.56828/jser.2022.1.2.2","DOIUrl":"https://doi.org/10.56828/jser.2022.1.2.2","url":null,"abstract":"","PeriodicalId":13763,"journal":{"name":"International Journal of Applied Science and Engineering Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87038347","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}
Pub Date : 2022-07-30DOI: 10.56828/jser.2022.1.2.1
Stephanie M Y Poon
{"title":"Simulation of Vehicle Target Detection based on Embedded System","authors":"Stephanie M Y Poon","doi":"10.56828/jser.2022.1.2.1","DOIUrl":"https://doi.org/10.56828/jser.2022.1.2.1","url":null,"abstract":"","PeriodicalId":13763,"journal":{"name":"International Journal of Applied Science and Engineering Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87188495","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}
Pub Date : 2022-07-30DOI: 10.56828/jser.2022.1.2.5
Wolfgang Bellotti, Daniela N. Davies, Y. H. Wang
{"title":"Development and Replication of Improved Recommendation Algorithm for Network Representation Learning","authors":"Wolfgang Bellotti, Daniela N. Davies, Y. H. Wang","doi":"10.56828/jser.2022.1.2.5","DOIUrl":"https://doi.org/10.56828/jser.2022.1.2.5","url":null,"abstract":"","PeriodicalId":13763,"journal":{"name":"International Journal of Applied Science and Engineering Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86945370","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}
Pub Date : 2022-07-30DOI: 10.56828/jser.2022.1.2.3
Somenath Chakraborty
{"title":"Point-of-Interest (POI) Recommendation Model Simulation using Social Relationships and Geographical Factors","authors":"Somenath Chakraborty","doi":"10.56828/jser.2022.1.2.3","DOIUrl":"https://doi.org/10.56828/jser.2022.1.2.3","url":null,"abstract":"","PeriodicalId":13763,"journal":{"name":"International Journal of Applied Science and Engineering Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83523204","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}
Pub Date : 2022-01-30DOI: 10.56828/jser.2022.1.1.1
Jacky Chun-ki Tang
: In the information age, the intelligent data mining method represented by deep learning is playing an important role in various fields at present. It is necessary to study how to efficiently use the intelligent data mining method to obtain valuable information from massive information. Open-set voiceprint recognition is realized by intelligent data mining technology. Therefore, it is of great practical significance to achieve rapid and accurate identification of the speaker's identity. Because the traditional voiceprint recognition method has insufficient ability to distinguish the speakers inside and outside the set, it often leads to a high false recognition rate. Mining parameters containing more speakers’ personality characteristics and how to calculate the threshold become the bottleneck problems of open set voiceprint recognition. Therefore, this paper adopts the deep confidence network stacked by three layers of restricted Boltzmann machines as the deep acoustic feature extractor. The mel-frequency cepstral coefficients of 24-dimensional basic acoustic features are mapped to 256-dimensional feature space, and the parameters of deep acoustic features containing more speaker's personality characteristics are obtained. Then, an open-set adaptive threshold calculation algorithm is obtained. In this paper, the similarity value of deep acoustic features is calculated by the Gaussian mixture model, and the maximum inter-class variance of the similarity value is calculated by the OTSU algorithm. When the inter-class variance is the maximum, the similarity value is the best threshold. The experimental test shows that the algorithm for calculating threshold based on deep learning proposed in this paper has a lower false rejection rate and lower false rejection rate.
{"title":"Deep Learning-based Analysis of Voiceprint Data Mining","authors":"Jacky Chun-ki Tang","doi":"10.56828/jser.2022.1.1.1","DOIUrl":"https://doi.org/10.56828/jser.2022.1.1.1","url":null,"abstract":": In the information age, the intelligent data mining method represented by deep learning is playing an important role in various fields at present. It is necessary to study how to efficiently use the intelligent data mining method to obtain valuable information from massive information. Open-set voiceprint recognition is realized by intelligent data mining technology. Therefore, it is of great practical significance to achieve rapid and accurate identification of the speaker's identity. Because the traditional voiceprint recognition method has insufficient ability to distinguish the speakers inside and outside the set, it often leads to a high false recognition rate. Mining parameters containing more speakers’ personality characteristics and how to calculate the threshold become the bottleneck problems of open set voiceprint recognition. Therefore, this paper adopts the deep confidence network stacked by three layers of restricted Boltzmann machines as the deep acoustic feature extractor. The mel-frequency cepstral coefficients of 24-dimensional basic acoustic features are mapped to 256-dimensional feature space, and the parameters of deep acoustic features containing more speaker's personality characteristics are obtained. Then, an open-set adaptive threshold calculation algorithm is obtained. In this paper, the similarity value of deep acoustic features is calculated by the Gaussian mixture model, and the maximum inter-class variance of the similarity value is calculated by the OTSU algorithm. When the inter-class variance is the maximum, the similarity value is the best threshold. The experimental test shows that the algorithm for calculating threshold based on deep learning proposed in this paper has a lower false rejection rate and lower false rejection rate.","PeriodicalId":13763,"journal":{"name":"International Journal of Applied Science and Engineering Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89464050","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}
Pub Date : 2022-01-01DOI: 10.56293/ijasr.2022.5445
Irunkwor T. C, Omoruyi C. I, Ogboi K. C
The natural radioactivity and radiological health risk associated with the use of water from hand-dug wells, tap/boreholes and river/creeks in three communities with history of oil spillage, gas flaring, oil bunkering and operation of illegal artisanal oil refining activities in Rivers State, Nigeria was here assessed and measured with gamma ray spectroscopy. The results showed that the mean activity concentration of water samples for hand-dug well water ranged from 11.94±1.12 to 12.77± 1.12Bq/l for 238U, 7.88±1.05 to 9.20±1.82Bq/l for 232Th and 13.50±0.62 to 20.13±3.88Bq/l for 40K. The mean activity concentration for the tap/borehole water ranged from 2.42±0.45Bq/l to 5.31±0.80Bq/l for 238U, 1.02±1.01 to 2.24±0.90Bq/l for 232Th and 9.71±5.04 to 11.73±3.77Bq/l for 40K. The 238U, 232Th and 40K activity concentrations in the river/creek waters ranged respectively from 6.81±0.80 to 8.82±1.20Bq/l, 4.25±0.65 to 9.52±1.16Bq/l and 25.01±3.23 to 30.03±1.96Bq/l. These values are higher than the mean activity concentrations of the 3 radionuclides in the control samples and some are higher than the international permissible standards. Results further revealed that there was statistically significant difference at p
{"title":"Risk Assessment of Natural Radionuclides in Surface and Ground Water of Oil and Gas Producing Communities, Rivers State, Nigeria","authors":"Irunkwor T. C, Omoruyi C. I, Ogboi K. C","doi":"10.56293/ijasr.2022.5445","DOIUrl":"https://doi.org/10.56293/ijasr.2022.5445","url":null,"abstract":"The natural radioactivity and radiological health risk associated with the use of water from hand-dug wells, tap/boreholes and river/creeks in three communities with history of oil spillage, gas flaring, oil bunkering and operation of illegal artisanal oil refining activities in Rivers State, Nigeria was here assessed and measured with gamma ray spectroscopy. The results showed that the mean activity concentration of water samples for hand-dug well water ranged from 11.94±1.12 to 12.77± 1.12Bq/l for 238U, 7.88±1.05 to 9.20±1.82Bq/l for 232Th and 13.50±0.62 to 20.13±3.88Bq/l for 40K. The mean activity concentration for the tap/borehole water ranged from 2.42±0.45Bq/l to 5.31±0.80Bq/l for 238U, 1.02±1.01 to 2.24±0.90Bq/l for 232Th and 9.71±5.04 to 11.73±3.77Bq/l for 40K. The 238U, 232Th and 40K activity concentrations in the river/creek waters ranged respectively from 6.81±0.80 to 8.82±1.20Bq/l, 4.25±0.65 to 9.52±1.16Bq/l and 25.01±3.23 to 30.03±1.96Bq/l. These values are higher than the mean activity concentrations of the 3 radionuclides in the control samples and some are higher than the international permissible standards. Results further revealed that there was statistically significant difference at p","PeriodicalId":13763,"journal":{"name":"International Journal of Applied Science and Engineering Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73931775","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}
Pub Date : 2022-01-01DOI: 10.56293/ijasr.2022.5470
Usman F, Azuaga, I. C, Tahir R, Barnabas D
Natural products are also known as secondary metabolites, compounds that are naturally produced by biological organisms. These natural products have a broad range of functions which include agents that solubilize and transport nutrients, like siderophores which transport iron Fe3+ across membranes in bacteria and fungi; they are often structurally complex molecules that possess a well-defined spatial orientation. These compounds have evolved to interact efficiently with their biological targets, as their producers evolved alongside their target organisms. This work aimed at reviewing modern trends in isolation and structural elucidation of Alkaloids and Terpenes. Alkaloids are the main secondary metabolites which have medical properties. It can be used to avoid the several degenerative sicknesses by scavenging free radical or binding with catalyst, the oxidative reaction. Terpenes or terpenoids are the major diverse group occurring in plants naturally, depending on isoprene unit’s number. Humans used several of terpenoid compounds to produce important compounds such as vitamin A from βcarotene. Generally, terpenes in foods contain a main effect on our eating practice. Terpenoid as pigments, like bixin, astaxanthin, and lycopene are utilized in the food manufacturing industry. The modern techniques as well as the advanced instruments that employed in the discovery programme of bioactive natural products facilitated the task of the natural product chemists and permitted them to detect, target, isolate and elucidate the structure of the pharmacologically active natural product in significantly short times compared with that done in the not too distant past. Conclusively, the review identified the various modern methods that are in use in the isolation, purification and structure elucidation of alkaloids and terpenoids. these include NMR,MS and hyphenated HPLC system.
{"title":"Isolation and Structure Elucidation of Natural Products Chemistry – Review of Modern Trends (Alkaloids and Terpenes)","authors":"Usman F, Azuaga, I. C, Tahir R, Barnabas D","doi":"10.56293/ijasr.2022.5470","DOIUrl":"https://doi.org/10.56293/ijasr.2022.5470","url":null,"abstract":"Natural products are also known as secondary metabolites, compounds that are naturally produced by biological organisms. These natural products have a broad range of functions which include agents that solubilize and transport nutrients, like siderophores which transport iron Fe3+ across membranes in bacteria and fungi; they are often structurally complex molecules that possess a well-defined spatial orientation. These compounds have evolved to interact efficiently with their biological targets, as their producers evolved alongside their target organisms. This work aimed at reviewing modern trends in isolation and structural elucidation of Alkaloids and Terpenes. Alkaloids are the main secondary metabolites which have medical properties. It can be used to avoid the several degenerative sicknesses by scavenging free radical or binding with catalyst, the oxidative reaction. Terpenes or terpenoids are the major diverse group occurring in plants naturally, depending on isoprene unit’s number. Humans used several of terpenoid compounds to produce important compounds such as vitamin A from βcarotene. Generally, terpenes in foods contain a main effect on our eating practice. Terpenoid as pigments, like bixin, astaxanthin, and lycopene are utilized in the food manufacturing industry. The modern techniques as well as the advanced instruments that employed in the discovery programme of bioactive natural products facilitated the task of the natural product chemists and permitted them to detect, target, isolate and elucidate the structure of the pharmacologically active natural product in significantly short times compared with that done in the not too distant past. Conclusively, the review identified the various modern methods that are in use in the isolation, purification and structure elucidation of alkaloids and terpenoids. these include NMR,MS and hyphenated HPLC system.","PeriodicalId":13763,"journal":{"name":"International Journal of Applied Science and Engineering Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75109924","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}
Pub Date : 2022-01-01DOI: 10.56293/ijasr.2022.5408
Peter OMOLOLU SUBAIR
The study investigated the influence of self-esteem on academic performance of male and female college students and established relationships between self-esteem and academic performance. Specifically, it described the demographic characteristics of students and analysed the relationship between self-esteem and students’ attitude of male and female college students in the study area. Descriptive correlation type of research designed was used to sample 36 male and 66 females with the use of Krecie and Margan (1970) sample size formula. Structured questionnaire was used for data collection and the response rate was about 85.7%. Data collected were described with frequency counts, percentages, mean and standard deviation while the t-statistic in regression was used for data analysis. Among the results, it was found that more female enrolment was recorded in the study area. Respondents were found in their adolescent ages and students with the required experience were sampled for the study. It was found that self-esteem never influenced the academic performance of the male students but it did for the female because their perception had influence on their self-esteem. Therefore, any intervention that will be geared towards improving academic performance of male and female students must be based on their self-esteem with the use of gender less. This will allow stakeholders’ interventions to produce desired effects. Parents and government should design programs that will attract and encourage more male enrolment and work on improving their self-esteem through counselling unit of the College.
{"title":"Gender analysis of Self-esteem and Academic Performance of College Students in Manuel S. Enverga University Foundation, Lucena City","authors":"Peter OMOLOLU SUBAIR","doi":"10.56293/ijasr.2022.5408","DOIUrl":"https://doi.org/10.56293/ijasr.2022.5408","url":null,"abstract":"The study investigated the influence of self-esteem on academic performance of male and female college students and established relationships between self-esteem and academic performance. Specifically, it described the demographic characteristics of students and analysed the relationship between self-esteem and students’ attitude of male and female college students in the study area. Descriptive correlation type of research designed was used to sample 36 male and 66 females with the use of Krecie and Margan (1970) sample size formula. Structured questionnaire was used for data collection and the response rate was about 85.7%. Data collected were described with frequency counts, percentages, mean and standard deviation while the t-statistic in regression was used for data analysis. Among the results, it was found that more female enrolment was recorded in the study area. Respondents were found in their adolescent ages and students with the required experience were sampled for the study. It was found that self-esteem never influenced the academic performance of the male students but it did for the female because their perception had influence on their self-esteem. Therefore, any intervention that will be geared towards improving academic performance of male and female students must be based on their self-esteem with the use of gender less. This will allow stakeholders’ interventions to produce desired effects. Parents and government should design programs that will attract and encourage more male enrolment and work on improving their self-esteem through counselling unit of the College.","PeriodicalId":13763,"journal":{"name":"International Journal of Applied Science and Engineering Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78349621","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}
Pub Date : 2022-01-01DOI: 10.56293/ijasr.2022.5420
May Lheena Fontila, Cherissa DE Jesus Delmita, Renee Maye G. Basila, M. J. Dantic
Due to the impact of COVID-19 pandemic, the world is facing the new setup of the education system, where blended learning will be used. The teachers' challenges are integrating the innovative programs in different subject areas effectively, how to motivate the students' learning process and ensure that learning continues for all the students. This descriptive survey assessed different factors affecting the effectiveness of Science teachers during COVID-19 pandemic. A total of 44 Science teachers from the schools of Subic National High School, Castillejos National High School and San Guillermo National High School responded to the researcher-crafted survey questionnaire (α=0.962). Results of the study showed that majority of the respondents strongly agree on factors affecting the effectiveness of Science teaching in which expertise in the subject matter is the primary factor followed by teaching performance, administrative support, student’s level of understanding, teacher communication, digital proficiency, instructional materials and professional development. Based on the descriptions of an effective science teaching given by the science teachers, it is said that teaching science concepts can be apply in real life situations. The strategies use to be effective in teaching Science during pandemic must be engage flexible learning. In other factors that may affect the effectiveness of Science teaching is teaching resources. There was no significant difference on the teacher’s perspective of the eight factors affecting the effectiveness of science teaching when grouped according to profile variables. Furthermore, positive significant moderate to high correlations were observed among factors affecting the effectiveness of science teaching in the current pandemic. The study suggests that training and seminars that focuses on enhancing content knowledge and pedagogy in teaching science during pandemic should be given among Science teachers that highlights on techniques and strategies on science teaching during COVID-19 pandemic. Correspondingly, future studies that focus on determining other factors that can affect the effectiveness of science teaching in the current pandemic must be conducted.
{"title":"FACTORS AFFECTING THE EFFECTIVENESS OF SCIENCE TEACHING DURING COVID – 19 PANDEMIC","authors":"May Lheena Fontila, Cherissa DE Jesus Delmita, Renee Maye G. Basila, M. J. Dantic","doi":"10.56293/ijasr.2022.5420","DOIUrl":"https://doi.org/10.56293/ijasr.2022.5420","url":null,"abstract":"Due to the impact of COVID-19 pandemic, the world is facing the new setup of the education system, where blended learning will be used. The teachers' challenges are integrating the innovative programs in different subject areas effectively, how to motivate the students' learning process and ensure that learning continues for all the students. This descriptive survey assessed different factors affecting the effectiveness of Science teachers during COVID-19 pandemic. A total of 44 Science teachers from the schools of Subic National High School, Castillejos National High School and San Guillermo National High School responded to the researcher-crafted survey questionnaire (α=0.962). Results of the study showed that majority of the respondents strongly agree on factors affecting the effectiveness of Science teaching in which expertise in the subject matter is the primary factor followed by teaching performance, administrative support, student’s level of understanding, teacher communication, digital proficiency, instructional materials and professional development. Based on the descriptions of an effective science teaching given by the science teachers, it is said that teaching science concepts can be apply in real life situations. The strategies use to be effective in teaching Science during pandemic must be engage flexible learning. In other factors that may affect the effectiveness of Science teaching is teaching resources. There was no significant difference on the teacher’s perspective of the eight factors affecting the effectiveness of science teaching when grouped according to profile variables. Furthermore, positive significant moderate to high correlations were observed among factors affecting the effectiveness of science teaching in the current pandemic. The study suggests that training and seminars that focuses on enhancing content knowledge and pedagogy in teaching science during pandemic should be given among Science teachers that highlights on techniques and strategies on science teaching during COVID-19 pandemic. Correspondingly, future studies that focus on determining other factors that can affect the effectiveness of science teaching in the current pandemic must be conducted.","PeriodicalId":13763,"journal":{"name":"International Journal of Applied Science and Engineering Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72795107","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}
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