• Journal of Plant Biotechnology
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• v.5 no.4
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• pp.193-195
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• 2003

A major goal of agricultural biotechnology is the discovery of genes or genetic loci which are associated with characteristics beneficial to crop production. This knowledge of genetic loci may then be applied to improve crop breeding. Agriculturally important genes may also benefit crop production through transgenic technologies. Recent years have seen an application of high throughput technologies to agricultural biotechnology leading to the production of large amounts of genomic data. The challenge today is the effective structuring of this data to permit researchers to search, filter and importantly, make robust associations within a wide variety of datasets. At the Plant Biotechnology Centre, Primary Industries Research Victoria in Melbourne, Australia, we have developed a series of tools and computational pipelines to assist in the processing and structuring of genomic data to aid its application to agricultural biotechnology resear-ch. These tools include a sequence database, ASTRA, for the processing and annotation of expressed sequence tag data. Tools have also been developed for the discovery of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) molecular markers from large sequence datasets. Application of these tools to Brassica research has assisted in the production of genetic and comparative physical maps as well as candidate gene discovery for a range of agronomically important traits.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3619-3637
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• 2022

Big data analytics offers endless opportunities for operational enhancement by extracting valuable insights from complex voluminous data. Hadoop is a comprehensive technological suite which offers solutions for the large scale storage and computing needs of Big data. The performance of Hadoop is closely tied with its configuration settings which depends on the cluster capacity and the application profile. Since Hadoop has over 190 configuration parameters, tuning them to gain optimal application performance is a daunting challenge. Our approach is to extract a subset of impactful parameters from which the performance enhancing sub-optimal configuration is then narrowed down. This paper presents a statistical model to analyze the significance of the effect of Hadoop parameters on a variety of performance metrics. Our model decomposes the total observed performance variation and ascribes them to the main parameters, their interaction effects and noise factors. The method clearly segregates impactful parameters from the rest. The configuration setting determined by our methodology has reduced the Job completion time by 22%, resource utilization in terms of memory and CPU by 15% and 12% respectively, the number of killed Maps by 50% and Disk spillage by 23%. The proposed technique can be leveraged to ease the configuration tuning task of any Hadoop cluster despite the differences in the underlying infrastructure and the application running on it.

• Journal of Information Technology Services
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• v.15 no.3
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• pp.195-209
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• 2016

IoT (Internet of Things) is a collective term referring to application services that provide information through sensors/devices connected to the internet. The real world application of IoT is expanding fast along with growing number of sensors/devices. However, since IoT application relies on vertical combination of sensors/devices networks, information sharing within IoT services remains unresolved challenge. Consequently, IoT sensors/devices demand high construction and maintenance costs, rendering the creation of new IoT services potentially expensive. One solution is to launch an IoT open market for information sharing similar to that of App Store for smart-phones. Doing so will efficiently allow novel IoT services to emerge across various industries, because developers can purchase licenses to access IoT resources directly via an open market. Sharing IoT resource information through an open market will create an echo-system conducive for easy utilization of resources and communication between IoT service providers, resource owners, and developers. This paper proposes the new business model of IoT open market for information sharing, and the requirements for ensuring security and standardization of open markets.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.277-286
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• 2021

This paper examines the readiness of Jordanian insurance companies to apply the International Financial Reporting Standards (IFRS 17), and the challenges of its application. The study developed a questionnaire based on prior related studies, and in the light of IFRS 17, the study used different statistical methods and techniques such as means, standard deviation, and t-test to achieve its goals. The results indicate that Jordanian insurance companies are not ready to apply IFRS 17, for several reasons. Most importantly, insurance companies have a low level of ability to define the scope of IFRS 17, study the impact of IFRS 17 application to financial reports, and develop new internal monitoring methods to apply IFRS 17. As for the challenges for applying IFRS 17, the biggest is the data challenge, followed by the challenges of first-time implementation, systems, and results and presentation. Finally, this paper advocates that it has become important for Jordanian insurance companies and supervisory bodies to enhance their readiness to apply IFRS 17 within a scheduled time framework and by taking several preparatory steps: performing simulations consisting of procedures to deal with IFRS 17 requirements and the impact on financial reports, and helping human resources with familiarization and application of IFRS 17.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.632-657
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• 2022

Detecting web attacks is a major challenge, and it is observed that the use of simple models leads to low sensitivity or high false positive problems. In this study, we aim to develop a robust two-stage deep learning based stacked ensemble web application firewall. Normal and abnormal classification is carried out in the first stage of the proposed WAF model. The classification process of the types of abnormal traffics is postponed to the second stage and carried out using an integrated stacked ensemble model. By this way, clients' requests can be served without time delay, and attack types can be detected with high sensitivity. In addition to the high accuracy of the proposed model, by using the statistical similarity and diversity analyses in the study, high generalization for the ensemble model is achieved. Within the study, a comprehensive, up-to-date, and robust multi-class web anomaly dataset named GAZI-HTTP is created in accordance with the real-world situations. The performance of the proposed WAF model is compared to state-of-the-art deep learning models and previous studies using the benchmark dataset. The proposed two-stage model achieved multi-class detection rates of 97.43% and 94.77% for GAZI-HTTP and ECML-PKDD, respectively.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.342-352
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• 2021

Multicast Routings is a big challenge due to limitations such as node power and bandwidth Mobile Ad-hoc Network (MANET). The path to be chosen from the source to the destination node requires protocols. Multicast protocols support group-oriented operations in a bandwidth-efficient way. While several protocols for multi-cast MANETs have been evolved, security remains a challenging problem. Consequently, MANET is required for high quality of service measures (QoS) such infrastructure and application to be identified. The goal of a MANETs QoS-aware protocol is to discover more optimal pathways between the network source/destination nodes and hence the QoS demands. It works by employing the optimization method to pick the route path with the emphasis on several QoS metrics. In this paper safe routing is guaranteed using the Secured Multicast Routing offered in MANET by utilizing the Ant Colony Optimization (ACO) technique to integrate the QOS-conscious route setup into the route selection. This implies that only the data transmission may select the way to meet the QoS limitations from source to destination. Furthermore, the track reliability is considered when selecting the best path between the source and destination nodes. For the optimization of the best path and its performance, the optimized algorithm called the micro artificial bee colony approach is chosen about the probabilistic ant routing technique.

• Genomics & Informatics
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• v.15 no.4
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• pp.178-182
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• 2017

Next-generation sequencing (NGS) technology has become a trend in the genomics research area. There are many software programs and automated pipelines to analyze NGS data, which can ease the pain for traditional scientists who are not familiar with computer programming. However, downstream analyses, such as finding differentially expressed genes or visualizing linkage disequilibrium maps and genome-wide association study (GWAS) data, still remain a challenge. Here, we introduce a dockerized web application written in R using the Shiny platform to visualize pre-analyzed RNA sequencing and GWAS data. In addition, we have integrated a genome browser based on the JBrowse platform and an automated intermediate parsing process required for custom track construction, so that users can easily build and navigate their personal genome tracks with in-house datasets. This application will help scientists perform series of downstream analyses and obtain a more integrative understanding about various types of genomic data by interactively visualizing them with customizable options.

• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.103-110
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• 2015

The biggest challenge of managing mobile interpretative device is that visitors do not have the mobile experience. Thus, in the research of the mobile application of the Leeum (Samsung Museum of Art), a short orientation session as a treatment was provided to survey participants to make them use of a mobile experience. The orientation solved the problem of hesitancy of using smartphone in other researches, it was simultaneously the uniqueness of the methodology. Based on the research data, their satisfaction with visiting experience and with using the application appeared to be relatively high. A half of participants used the application for 10 minutes which is accounted for 20-30% of the total viewing time. Participants (80.3%) engaged in each exhibit with the application in less than 30 sec.-1 minute. Comparing with the average time of engagement (10-30 sec.) for each exhibit without using mobile applications, it is possible to conclude that the mobile application notably contributed to make participants engage with exhibits longer.

• Journal of Microbiology
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• v.43 no.3
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• pp.308-312
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• 2005

The global RNA transcription profiles of Bacillus lentimorbus WJ5 under an in vitro co-culture with Colletotrichum gloeosporioides were analyzed in order to study the antagonistic bacteria-fungi interactions. Using a filter membrane system, B. lentimorhus WJ5 was exposed to the spores of C. gloeosporioides at the late exponential stage. The transcription profiles of the B. lentimorhus WJ5, both with and without a challenge from C. gloeosporioides, were analyzed using custom DNA chips containing 2,000 genome fragments. A total of 337 genes were expressed, with 87 and 47 up- and down-regulated, respectively. Of these, 12 genes, which were involved in central carbon metabolisms, and 7 from minor catabolism were relatively highly up-regulated (> 10 fold) and down-regulated (< 0.2 fold), respectively. Nine genes, which were thought to be related to the antifungal activity, were also up-regulated, but their levels were not so high (2.0 - 9.7 folds). From the results, during the early stage of the co-culture of B. lentimorbus WJ5 and C. gloeosporioides, nutrient competition seemed to occur; therefore, the genes from central carbon metabolisms could be up-regulated, while those from minor catabolism could be down-regulated.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.392-404
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• 2010

Recently, as both business processes and IT systems become ever more complex. Especially, enterprise applications tend to become unmanageably complex and increasingly costly to maintain. Therefore complexity is the insidious enemy of software development. It is critical to have a methodology that recognizes and manages this enemy effectively. In this paper, we propose ISIS (Integrated System of Independent Subsystems) - the architectural style needed to develop the complex enterprise applications. The ISIS was developed to meet the challenge of reducing the complexity of a larger enterprise application today. It gives us architecture models for reducing development complexity and composite application. The enterprise application is partitioned into a collection of independent subsystems using ISIS decomposition schemes and equivalence relations. We use middleware named ISIS engine that provides a service for subsystems interoperability by enabling the integration of distributed, cross-platform subsystems. We have implemented an ITSM system that achieves our objectives, reducing development complexity, using the ISIS architecture. Finally, ISIS architecture provides greater flexibility and productivity when an organization needs either to change its business processes, or to update the underlying systems.