• Title/Summary/Keyword: Pre-form

Search Result 910, Processing Time 0.031 seconds

Combination of Brain Cancer with Hybrid K-NN Algorithm using Statistical of Cerebrospinal Fluid (CSF) Surgery

  • Saeed, Soobia;Abdullah, Afnizanfaizal;Jhanjhi, NZ
    • International Journal of Computer Science & Network Security
    • /
    • v.21 no.2
    • /
    • pp.120-130
    • /
    • 2021
  • The spinal cord or CSF surgery is a very complex process. It requires continuous pre and post-surgery evaluation to have a better ability to diagnose the disease. To detect automatically the suspected areas of tumors and symptoms of CSF leakage during the development of the tumor inside of the brain. We propose a new method based on using computer software that generates statistical results through data gathered during surgeries and operations. We performed statistical computation and data collection through the Google Source for the UK National Cancer Database. The purpose of this study is to address the above problems related to the accuracy of missing hybrid KNN values and finding the distance of tumor in terms of brain cancer or CSF images. This research aims to create a framework that can classify the damaged area of cancer or tumors using high-dimensional image segmentation and Laplace transformation method. A high-dimensional image segmentation method is implemented by software modelling techniques with measures the width, percentage, and size of cells within the brain, as well as enhance the efficiency of the hybrid KNN algorithm and Laplace transformation make it deal the non-zero values in terms of missing values form with the using of Frobenius Matrix for deal the space into non-zero values. Our proposed algorithm takes the longest values of KNN (K = 1-100), which is successfully demonstrated in a 4-dimensional modulation method that monitors the lighting field that can be used in the field of light emission. Conclusion: This approach dramatically improves the efficiency of hybrid KNN method and the detection of tumor region using 4-D segmentation method. The simulation results verified the performance of the proposed method is improved by 92% sensitivity of 60% specificity and 70.50% accuracy respectively.

Pre-processing Method of Raw Data Based on Ontology for Machine Learning (머신러닝을 위한 온톨로지 기반의 Raw Data 전처리 기법)

  • Hwang, Chi-Gon;Yoon, Chang-Pyo
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.24 no.5
    • /
    • pp.600-608
    • /
    • 2020
  • Machine learning constructs an objective function from learning data, and predicts the result of the data generated by checking the objective function through test data. In machine learning, input data is subjected to a normalisation process through a preprocessing. In the case of numerical data, normalization is standardized by using the average and standard deviation of the input data. In the case of nominal data, which is non-numerical data, it is converted into a one-hot code form. However, this preprocessing alone cannot solve the problem. For this reason, we propose a method that uses ontology to normalize input data in this paper. The test data for this uses the received signal strength indicator (RSSI) value of the Wi-Fi device collected from the mobile device. These data are solved through ontology because they includes noise and heterogeneous problems.

A Comparative Analysis of Personalized Recommended Model Performance Using Online Shopping Mall Data (온라인 쇼핑몰 데이터를 이용한 개인화 추천 모델 성능 비교 분석)

  • Oh, Jaedong;Oh, Ha-young
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.26 no.9
    • /
    • pp.1293-1304
    • /
    • 2022
  • The personalization recommendation system means analyzing each individual's interests or preferences and recommending information or products accordingly. These personalized recommendations can reduce the time consumers spend searching for information by accessing the products they need more quickly, and companies can increase corporate profits by recommending appropriate products that meet their needs. In this study, products are recommended to consumers using collaborative filtering, matrix factorization, and deep learning, which are representative personalization recommendation techniques. To this end, the data set after purchasing shopping mall products, which is raw data, is pre-processed in the form of transmitting the data set to the input of the recommended system, and the pre-processed data set is analyzed from various angles. In addition, each model performs verification and performance comparison on the recommended results, and explores the model with optimal performance, suggesting which model should be used when building the recommendation system at the mall.

Bending characteristics of Prestressed High Strength Concrete (PHC) spun pile measured using distributed optical fibre strain sensor

  • Mohamad, Hisham;Tee, Bun Pin;Chong, Mun Fai;Lee, Siew Cheng;Chaiyasarn, Krisada
    • Smart Structures and Systems
    • /
    • v.29 no.2
    • /
    • pp.267-278
    • /
    • 2022
  • Pre-stressed concrete circular spun piles are widely used in various infrastructure projects around the world and offer an economical deep foundation system with consistent and superior quality compared to cast in-situ and other concrete piles. Conventional methods for measuring the lateral response of piles have been limited to conventional instrumentation, such as electrical based gauges and pressure transducers. The problem with existing technology is that the sensors are not able to assist in recording the lateral stiffness changes of the pile which varies along the length depending on the distribution of the flexural moments and appearance of tensile cracks. This paper describes a full-scale bending test of a 1-m diameter spun pile of 30 m long and instrumented using advanced fibre optic distributed sensor, known as Brillouin Optical Time Domain Analysis (BOTDA). Optical fibre sensors were embedded inside the concrete during the manufacturing stage and attached on the concrete surface in order to measure the pile's full-length flexural behaviour under the prescribed serviceability and ultimate limit state. The relationship between moments-deflections and bending moments-curvatures are examined with respect to the lateral forces. Tensile cracks were measured and compared with the peak strains observed from BOTDA data which corroborated very well. By analysing the moment-curvature response of the pile, the structure can be represented by two bending stiffness parameters, namely the pre-yield (EI) and post-yield (EIcr), where the cracks reduce the stiffness property by 89%. The pile deflection profile can be attained from optical fibre data through closed-form solutions, which generally matched with the displacements recorded by Linear Voltage Displacement Transducers (LVDTs).

A Study on the Use of Stopword Corpus for Cleansing Unstructured Text Data (비정형 텍스트 데이터 정제를 위한 불용어 코퍼스의 활용에 관한 연구)

  • Lee, Won-Jo
    • The Journal of the Convergence on Culture Technology
    • /
    • v.8 no.6
    • /
    • pp.891-897
    • /
    • 2022
  • In big data analysis, raw text data mostly exists in various unstructured data forms, so it becomes a structured data form that can be analyzed only after undergoing heuristic pre-processing and computer post-processing cleansing. Therefore, in this study, unnecessary elements are purified through pre-processing of the collected raw data in order to apply the wordcloud of R program, which is one of the text data analysis techniques, and stopwords are removed in the post-processing process. Then, a case study of wordcloud analysis was conducted, which calculates the frequency of occurrence of words and expresses words with high frequency as key issues. In this study, to improve the problems of the "nested stopword source code" method, which is the existing stopword processing method, using the word cloud technique of R, we propose the use of "general stopword corpus" and "user-defined stopword corpus" and conduct case analysis. The advantages and disadvantages of the proposed "unstructured data cleansing process model" are comparatively verified and presented, and the practical application of word cloud visualization analysis using the "proposed external corpus cleansing technique" is presented.

How Effective Is Toothbrush Education through Environmental Changes in Elementary School Children

  • Pratamawari, Dyah Nawang Palupi;Balgies, Grandyna Ansya;Buunk-Werkhoven, Yvonne A.B.
    • Journal of dental hygiene science
    • /
    • v.22 no.1
    • /
    • pp.30-36
    • /
    • 2022
  • Background: Nowadays, dental health problems in Indonesia are still quite high. It is one of which influenced by low public awareness of the importance of maintaining the health of teeth and mouth that can be measured by toothbrushing behavior. Based on the results of RISKESDAS 2018, only 2.8 percent of the population has a proper toothbrushing behavior. Behavior tends to form at age 6 to 12 years. At this age, children begin to develop habits that tend to settle until adulthood, including toothbrushing behavior. Social cognitive theory is a theory of behavioral change that explains that behavioral changes are influenced by the environment, personal, behavior where these three factors influence each other. This study aims to identify changes in the dental behavior of second grades students before and after the joint toothbrushing at school for 21 days. Methods: A pre-experimental study-design was conducted on elementary school by pre-post treatment method where there are 2 classes that get intervention and 2 other classes as control. A joint toothbrush is performed every morning before the school activities begin. Before and after the joint toothbrushing, all classes are given questionnaires to see if there are any changes in behavior seen through knowledge, attitudes, and practice. Results: Respondent group showed increasement on their knowledge, attitudes, and behaviors towards toothbrushing. In contrast, the control groups showed no significant differences in the 3 factors. Conclusion: In this study the education of toothbrushing through environmental changes is quite effective in elementary school children. Insights into the benefits of this program and refinements of optimally targeted intervention, including longitudinal studies are needed to improve the results.

Network Operation Support System on Graph Database (그래프데이터베이스 기반 통신망 운영관리 방안)

  • Jung, Sung Jae;Choi, Mi Young;Lee, Hwasik
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2022.05a
    • /
    • pp.22-24
    • /
    • 2022
  • Recently, Graph Database (GDB) is being used in wide range of industrial fields. GDB is a database system which adopts graph structure for storing the information. GDB handles the information in the form of a graph which consists of vertices and edges. In contrast to the relational database system which requires pre-defined table schema, GDB doesn't need a pre-defined structure for storing data, allowing a very flexible way of thinking about and using the data. With GDB, we can handle a large volume of heavily interconnected data. A network service provider provides its services based on the heavily interconnected communication network facilities. In many cases, their information is hosted in relational database, where it is not easy to process a query that requires recursive graph traversal operation. In this study, we suggest a way to store an example set of interconnected network facilities in GDB, then show how to graph-query them efficiently.

  • PDF

Test Dataset for validating the meaning of Table Machine Reading Language Model (표 기계독해 언어 모형의 의미 검증을 위한 테스트 데이터셋)

  • YU, Jae-Min;Cho, Sanghyun;Kwon, Hyuk-Chul
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2022.10a
    • /
    • pp.164-167
    • /
    • 2022
  • In table Machine comprehension, the knowledge required for language models or the structural form of tables changes depending on the domain, showing a greater performance degradation compared to text data. In this paper, we propose a pre-learning data construction method and an adversarial learning method through meaningful tabular data selection for constructing a pre-learning table language model robust to these domain changes in table machine reading. In order to detect tabular data sed for decoration of web documents without structural information from the extracted table data, a rule through heuristic was defined to identify head data and select table data was applied. An adversarial learning method between tabular data and infobax data with knowledge information about entities was applied. When the data was refined compared to when it was trained with the existing unrefined data, F1 3.45 and EM 4.14 increased in the KorQuAD table data, and F1 19.38, EM 4.22 compared to when the data was not refined in the Spec table QA data showed increased performance.

  • PDF

A Study on Structural Behavior of Composite Deck Plate using a Pre-assembled Re-bar Truss (철근 선조립형 복합 데크플레이트의 하부근 선경축소에 따른 구조적 거동 평가)

  • Yoo, Byung-Uk
    • Journal of the Korea institute for structural maintenance and inspection
    • /
    • v.10 no.5
    • /
    • pp.129-138
    • /
    • 2006
  • Composite deck plate using a pre-assembled re-bar truss for slab with corrugated zinc galvanized sheet iron at manufactory, is given the improvement on design, manufacture, and performance for construction work of cast-in-place reinforced concrete slab by enabling to cast concrete directly without the form work. There are two methods in analyzing composite deck : Simplified 2D analysis and 3D analysis. Although simplified 2D analysis is being used up to date, the use of 3D analysis, allowing for the vierendeel behavior of composite deck by real configuration correlating to bar reducing, is demanded. To compare the simplified 2D analysis applied to allowable stress design with 3D analysis applied to limit state design, 8 specimen are manufactured. Main variables include the depth of slab, the length of span, the diameter of bottom bar and lattice bar, and the presence of corrugated zinc galvanized sheet iron. The comparison from the experimental result and analytical result indicates that applying of simplified 2D analysis is possible for the use of D10 with bottom bar. However, it is more reasonable to apply 3D analysis which allows to indicate vierendeel behavior considered the real configuration.

The Effectiveness of Explicit Form-Focused Instruction in Teaching the Schwa /ə/ (영어 약모음 /ə/ 교수에 있어서 명시적 Form-Focused Instruction의 효과 연구)

  • Lee, Yunhyun
    • The Journal of the Korea Contents Association
    • /
    • v.20 no.8
    • /
    • pp.101-113
    • /
    • 2020
  • This study aimed to explore how effective explicit form-focused instruction (FFI) is in teaching the schwa vowel /ə/ to EFL students in a classroom setting. The participants were 25 female high school students, who were divided into the experimental group (n=13) and the control group (n=12). One female American also participated in the study for a speech sample as a reference. The treatment, which involves shadowing model pronunciation by the researcher and a free text-to-speech software and the researcher's feedback in a private session, was given to the control group over a month and a half. The speech samples, for which the participants read the 14 polysyllabic stimulus words followed by the sentences containing the words, were collected before and after the treatment. The paired-samples t test and non-parametric Wilcoxon signed-rank test were used for analysis. The results showed that the participants of the experimental group in the post-test reduced the duration of the schwa by around 40 percent compared to the pre-test. However, little effect was found in approximating the participants' distribution patterns of /ə/ measured by the F1/F2 formant frequencies to the reference point, which was 539 Hz (F1) by 1797 Hz (F2). The findings of this study suggest that explicit FFI with multiple repetitions and corrective feedback is partly effective in teaching pronunciation.