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Apr 2018 DOI 10.14302/issn.2768-0207.jbr-17-1925
Big data research has become popular and exciting studies in almost all scientific fields such as biology, chemistry, epidemiology, medicine and drug discovery. The various systems and platforms produce large amounts of data every day. It will be very helpful for the researchers and workers to deal with big data if the practical database and useful software are introduced in time. The Journal of Big Data Research (JBR) supplies an efficient and open access publishing platform for big data research. The first issue of JBR aims to foster the dissemination of high-quality big data studies in the biological, medical and chemical database as well as the new algorithm and software for big data processing. The database and computing framework are selected to introduce the development of big data in the biological, medicine and drug discovery. The mature and functional database can be serviced in big data research of scientific fields. It promotes the scientists to extract the useful and essential dataset from the massive data. The grid computing and cloud computing supplies a new paradigm that offers an effective framework of computing and services. The research papers are welcomed from the scopes of the practical database, new algorithm and software for big data studies. All these kinds of papers not only provide the effective application methods and platforms, but also give a good promising future for big data research.
Jul 2025 DOI 10.14302/issn.2766-8681.jcsr-25-5618
Humanity is persistently threatened by global pandemics- exemplified by the Black plague, the Spanish flu, and COVID-19, which reveal a continual absence of concern in real-time prevention. To forecast biological threats in the future and spur proactive human response, the term Global Biological Consciousness (GBC) is introduced.GBC requires an Extended Bioethics, a dynamic ethical framework for conscious management mediated by GBC. This perspective will enable preventive actions and will seek global biological resilience through the algorithmic responsibility of AI and systemic justice, as will be explained in the work. The GBC, through Extended Bioethics, will provide an ability to analyze biological data as it occurs using AI and quantum computing, expect outbreaks before they happen and attenuate their effects, here creates a new ethical contract for all humankind as they co-exist in a biological world.
Mar 2023 DOI 10.14302/issn.2768-0207.jbr-23-4478
Spatial data mining (SDM) is searching important relationships and characteristics that can clearly exist in spatial databases. This content aims to compare object clustering algorithms for spatial data mining, before identifying the most efficient algorithm. To this end, this paper compare k-means, Partionning Around Medoids (PAM) and Clustering Large Applications based on RANdomized Search (CLARANS) algorithms based on computing time. Experimental results indicate that, CLARANS is very efficient and effective.
Dec 2020 DOI 10.14302/issn.2641-4538.jphi-20-3427
Automation of human tasks has taken place for a long time now. Humans have in earlier periods dreamed of a world where machines capable of mimicking decision making would be created with some works of fiction describing in caricature, how machines would take over the human space in the world. Artificial intelligence has come to fruition in the last few decades following the development of fast computing capability and vast chip memory. Discussions of how the human space will look and feel when artificial intelligence have taken place at various levels of global organization geared towards ensuring that the new “thinking machines” do not rock human society in ways to render them obsolete. This article looks at the ethics of AI considering the issues that have been outlined by others in the light of communitarian ethics as seen in Africa. It describes the possible impact of thinking machines on society and how individuals would relate with each other and with AI systems.
Jul 2020 DOI 10.14302/issn.2643-2811.jmbr-20-3449
Electrical resistivity method is often used to estimate the subsurface structure of the earth. Many inversion algorithms are available to estimate the subsurface features. However, predicting the exact parameter in the non-linear subsurface of the earth is difficult because of its complex composition. Soft computing tools can approximate the subsurface parameters more clearly. Each soft computing tool has certain advantages and disadvantages. A hybrid formation of algorithms will make the decision more appropriate than depending on a single tool. Here in our study the data obtained through Vertical Electrical Sounding has been used to determine the sub surface characteristics of earth viz., true resistivity and thickness. Artificial Neural Networks (ANN) requires certain optimizing procedures. Here in this paper, Genetic Algorithm (GA) is applied to optimize Artificial Neural Networks (ANN). This coupled approach is tested with the field data. Error percentage of algorithm nearly mimics the behavior of earth and is verified. The best performance result shows that this technique can be implemented to estimate the non-linear characteristics of the earth more noticeably.
Jul 2020 DOI 10.14302/issn.2641-5526.jmid-20-3424
In the last decade, the amount of collected data, in various computer science applications, has grown considerably. These large volumes of data need to be analysed in order to extract useful hidden knowledge. This work focuses on association rule extraction. This technique is one of the most popular in data mining. Nevertheless, the number of extracted association rules is often very high, and many of them are redundant. In this paper, we propose an algorithm, for mining closed itemsets, with the construction of an it-tree. This algorithm is compared with the DCI (direct counting & intersect) algorithm based on min support and computing time. CHARM is not memery-efficient. It needs to store all closed itemsets in the memory. The lower min-sup is, the more frequent closed itemsets there are so that the amounts of memory used by CHARM are increasing.
Apr 2020
Geoelectrical resistivity data is used for estimating the subsurface features of earth. It is very difficult to estimate the depth and true resistivity analytically, therefore many mathematical models approximates the result. The approximation relies on many parameters as the heterogenous model of earth is difficult to map. Conventional interpretation algorithm mostly uses the forward modelling technique which is limited for different lithologies. Here we presented ResinvANFIS v1.0 software platform to invert any type (A, Q, K, H or any mixed data types) of resistivity data having AB/2 and apparent resistivity data as input. This kind of generalised platform has not been done elsewhere to invert data directly using soft computing approach.
Apr 2019 DOI 10.14302/issn.2470-0436.jos-19-2693
Given limited knowledge regarding validity of the Titmus vision screener, we sought to compare visual acuity measurements obtained from the Titmus with that from the Snellen chart and assess the validity properties of the Titmus as a screening instrument to detect vision impairment. Visual acuity was measured in 150 participants recruited from an academic ophthalmology practice, using the Snellen chart as well as the Titmus vision screener. Visual acuities from the Titmus and Snellen were compared and validity of the Titmus vision screener was assessed by computing sensitivity and specificity. Using Snellen visual acuity as the reference standard, the sensitivity of the Titmus vision screener to detect vision impairment, defined as visual acuity worse than 20/40, was 92% (95% CI (72.5, 98.6)) and the specificity was 64% (95% CI (57.9, 70.1)). Comparisons of the precise visual acuity level revealed poor agreement between the two methods (weighted Kappa: 0.15, 95% CI (0.08, 0.21)). Visual acuities obtained from the Titmus were, on average, two lines worse than Snellen visual acuities. ((logMAR Snellen – logMAR Titmus) = - 0.19 ± 0.29, 95% confidence interval (CI) (-0.23, -0.16)). Titmus vision screener is a sensitive tool to detect visual impairment. However high false positive results and poor agreement with Snellen limits its widespread use in clinical applications.
Feb 2016 DOI 10.14302/issn.2374-9431.jbd-15-890
Purpose Signal Transducer and Activator of Transcription 4 (STAT4) is important for signaling by interleukins (IL-12 and IL-23) and type 1 interferons and has been found to have several simple nucleotide polymorphisms (SNPs) associated with human disease. STAT4 SNPs were computationally examined with respect to changes in potential transcriptional factor binding sites (TFBS) and these changes were discussed in relation to human disease. Methods The JASPAR CORE and ConSite databases were instrumental in identifying the TFBS. The Vector NTI Advance 11.5 computer program was employed in locating all theTFBS in theSTAT4 gene from 4 kb upstream of the transcriptional start site to 8.3 kb past the 3’UTR. The JASPAR CORE database was also involved in computing each nucleotide occurrence (%) within the TFBS. Results The STAT4 SNPs in the 70 kb intron between exon 2 and 3 are in linkage disequilibrium and have previously been found to be significantly associated with several vasculitis diseases as well as diabetes. The SNP alleles were found to alter the DNA landscape for potential transcriptional factors (TFs) to attach resulting in changes in TFBS and thereby, alter which transcriptional factors potentially regulate the STAT4 gene. These STAT4 SNPs should be considered as regulatory (r) SNPs. Conclusion The alleles of each rSNP were found to generate unique TFBS resulting in potential changes in TF STAT4 regulation. These regulatory changes were discussed with respect to changes in human health that result in disease.
Feb 2016 DOI 10.14302/issn.2326-0793.jpgr-15-889
Purpose The endothetal Per-Arnt-Sim (PAS) domain protein 1 (EPAS1) gene which encodes hypoxia-inducible-factor-2 alpha (HIF2a) is a transcription factor that is involved in the response to hypoxia. EPAS1 has been found to have four (rs56721780, rs6756667, rs7589621, rs1868092) simple nucleotide polymorphisms (SNPs) associated with human disease.These SNPs were computationally examined with respect to changes in potential transcriptional factor binding sites (TFBS) and these changes were discussed in relation to disease and alterations in high altitude adaptation in humans. Methods The JASPAR CORE and ConSite databases were instrumental in identifying the TFBS. The Vector NTI Advance 11.5 computer program was employed in locating all theTFBS in theEPAS1 gene from 1.6 kb upstream of the transcriptional start site to 539 bps past the 3’UTR. The JASPAR CORE database was also involved in computing each nucleotide occurrence (%) within the TFBS. Results The EPAS1 SNPs in the promoter, intron two and the 3’UTR regions have previously been found to be significantly associated with disease and different levels of high-altitude hypoxia among native Tibetans. The SNP alleles were found to alter the DNA landscape for potential transcriptional factors (TFs) to attach resulting in changes in TFBS and thereby, alter which transcriptional factors potentially regulate the EPAS1 genesuch as for the glucocorticoid and mineralocorticoid nuclear receptor binding sites created by the rs7589621 rSNP EPAS1-G allele. These receptors regulate carbohydrate, protein and fat metabolism. Also the minor rs7589621 rSNP EPAS1-A creates a punitive TFBS for the FOXC TF which is an important regulator of cell viability and resistance to oxidative stress. These EPAS1 SNPs should be considered as regulatory (r) SNPs. Conclusion The alleles of each rSNP were found to generate unique TFBS resulting in potential changes in TF EPAS1 regulation. The punitive changes in TFBS created by the four rSNPs could very well influence the significant cline in allele frequencies seen in Tibetans with increasing altitude or the haplotype association with high altitude polycythemia in male Han Chinese. These regulatory changes were discussed with respect to changes in human health that result in disease and sickness.