Global Journal of Computer Science and Technology (GJCST)
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Review on the Application of Machine Learning to Cancer Research
Full text linkThis study reviews the application of machine learning through different algorithms in cancer research. In recent years, the introduction of machine learning has been an exciting tool that enhances cancer research which has improved statistical method of speeding up both fundamental and applied research considerably. The application of machine learning goes around in predicting the future events and outcomes with the available datasets. There is an indication that on yearly bases up to 14 million new cancer patients are diagnosed by Pathologists round the world, and they are people whose conditions are uncertain. Definitely, the diagnoses and prognoses of cancer have been performed by Pathologists. The research on machine learning flourished in 1980s and 1990s and information become digitalized through improved artificial network connectivity and computational power
Sentiment Polarity Identification of Social Media content using Artificial Neural Networks
Full text linkSentiment of people about consumer goods and government policies for decision making is normally collected through feedback forms, surveys etc. The social network sites and micro blogging sites are considered a very good source of information nowadays because people share and discuss their opinions about a certain topic freely. With the increased use of technology and social media, people proactively express their opinion through social media sites like Twitter, Facebook, Instagram etc. A social media sentiment analysis can help companies to understand how people feel about their products. On the other hand, extracting the sentiment from social media text is a challenging task due to the complexity of natural language processing of social media language. Often these messages reflect the emotion, opinion and sentiment of the public through a mix of text, image, emoticons etc. These statements are often called electronic Word of Mouth (eWOM) and are much prevalent in business and service industry to enable customers to share their point of view
Best Fit Method of Sample Selection in Data Hiding and Extraction
Full text linkToday data security and its transmission over the wireless network need special attention. Intruder always has a watch on sensitive data transmitted over a wireless network. This work proposes an approach that minimizes the quantization error between the original and result carrier by selecting optimize samples during Data Hiding. Propose work find out best matching carrier components during the data hiding process. Results also imply that achieved results are far better than any other steganographic method
A Call Graph Reduction based Novel Storage Allocation Scheme for Smart City Applications
Full text linkToday s world is going to be smart even smarter day by day Smart cities play an important role to make the world smart Thousands of smart city applications are developing in every day Every second very huge amount of data is generated The data need to be managed and stored properly so that information can be extracted using various emerging technologies The main aim of this paper is to propose a storage scheme for data generated by smart city applications A matrix is used which store the information of each adjacency node of each level as well as the weight and frequency of call graph It has been experimentally depicted that the applied algorithm reduces the size of the call graph without changing the basic structure without any loss of information Once the graph is generated from the source code it is stored in the matrix and reduced appropriately using the proposed algorithm The proposed algorithm is also compared to another call graph reduction techniques and it has been experimentally evaluated that the proposed algorithm significantly reduces the graph and store the smart city application data efficientl
Instrumental System of Distance Learning DL.GSU.BY and Examples of its Application
Full text linkThe basic capabilities of the distance learning instrumental system DL GSU BY hereinafter DL are described such as presentation of the theory references to students presentation of tasks to students sending by them files-solutions acceptance and automatic verification of the solutions checking files of arbitrary structure with arbitrary extensions by specialized programs interactive tasks manual verification of solutions assignment of tests differentiated presentation of task
Computational Thinking and the Curriculum of Mathematics in Portugal
Full text linkThe emphasis on the importance of programming and computational thinking has been a constant in recent pedagogical trends Wing 2006 2010 NRC 2011 In the same perspective Pollock et al 2019 characterize computational thinking as decomposition algorithms data and abstraction According to Selby Woolard 2013 and Tabesh 2017 computational thinking in addition to being associated with decomposition pattern recognition algorithms and abstraction identifies the importance of debugging that is the ability to test and evaluate the effectiveness of the solution correct errors and seek to refine and optimize the solution This was the framework that was taken into account for the start of the MatemaTIC pilot project promoted by the Directorate-General for Education DGE with the joint organization of the Association of Mathematics Teachers APM University of Coimbra UC and of the CCTIC of the University of vora CCTIC UE This project started in 2019 involved teachers of the 1st Cycle of Basic Education from 30 Groups of Schools in Portugal and its main objective was to create resources and training contexts for teachers of this level of education to support the development of their skills professional skills in the fields of mathematics and ICT so that they are able to work on issues of computational thinking algorithms and computing in the classroom with students The final considerations point to the importance of the theme in the awareness of the learning that they intend to consolidate in the students the importance of the contents to be developed in the process of supporting students with gradually more complex tasks helping to build reasoning and develop mathematical language the importance of generalizing and transferring the problem-solving process to a wide variety of similar tasks the importance of collaborative work in the active role of the student in the construction of knowledge and in the importance of involving the student in the evaluation process in the sense of self-assessment and self-correctio
Blind Assistance System using Image Processing
Full text linkEye diseases usually cause blindness and visual impairment As per the statistics there are over 285 million visually impaired people living worldwide They come across many troubles in their daily life especially while navigating from one place to another on their own They often depend on others for help to satisfy their day-to-day needs So it is quite a challenging task to implement a technological solution to assist them Several technologies were developed for the assistance of visually impaired people One such attempt is that we would wish to make an Integrated Machine Learning System that allows the blind victims to identify and classify real-time objects generating voice feedback and distance Which also produces warnings whether they are very close or far away from the thin
Work Output Level using ICT at in Twifo Atti-Morkwa District Assembly
Full text linkThe primary aim of this paper is to look at the speed level of Information and Communication Technology resources of staff of Twifo Atti-Morkwa District Assembly. The degree of impact of Information and Communication Technology have on activities of staff at TAMDA is about 70%. There is a relationship between work output, qualification, promotion and performance in the Assembly. From the findings and analysis of the data received, it was recommended the Assembly should look at adopting Information and Communication Technologies at the work place for an effective performance. The civil organisations management should also consider engaging the services of staff with high Information and Communication Technology proficiency for good job delivery. The district assembly should as well look at creating Information and Communication Technology workshops for its employees to facilitate them with the needed skills and resources they require for a better work output
CapillaryX: A Software Design Pattern for Analyzing Medical Images in Real-time using Deep Learning
Full text linkAbstract Recent advances in digital imaging, e.g., increased number of pixels captured, have meant that the volume of data to be processed and analyzed from these images has also increased. Deep learning algorithms are state-of-the-art for analyzing such images, given their high accuracy when trained with a large data volume of data. Nevertheless, such analysis requires considerable computational power, making such algorithms time- and resource-demanding. Such high demands can be met by using third-party cloud service providers. However, analyzing medical images using such services raises several legal and privacy challenges and do not necessarily provide real-time results. This paper provides a computing architecture that locally and in parallel can analyze medical images in real-time using deep learning thus avoiding the legal and privacy challenges stemming from uploading data to a third-party cloud provider. To make local image processing efficient on modern multi-core processors, we utilize parallel execution to offset the resource- intensive demands of deep neural networks. We focus on a specific medical-industrial case study, namely the quantifying of blood vessels in microcirculation images for which we have developed a working system. It is currently used in an industrial, clinical research setting as part of an e-health application. Our results show that our system is approximately 78% faster than its serial system counterpart and 12% faster than a master-slave parallel system architecture
On Baysian Estimation of Loss of Estimators of Unknown Parameter of Binomial Distribution
Full text linkThis paper aims at the Bayesian estimation for the loss and risk functions of the unknown parameter of the binomial distribution under the loss function which is different from that given by Rukhin 1988 The estimation involves beta distribution a natural conjugate prior density function for the unknown parameter Estimators obtained are conservatively biased and have finite frequentist ris