113 research outputs found
Stochastic Database Cracking: Towards Robust Adaptive Indexing in Main-Memory Column-Stores
Modern business applications and scientific databases call for inherently
dynamic data storage environments. Such environments are characterized by two
challenging features: (a) they have little idle system time to devote on
physical design; and (b) there is little, if any, a priori workload knowledge,
while the query and data workload keeps changing dynamically. In such
environments, traditional approaches to index building and maintenance cannot
apply. Database cracking has been proposed as a solution that allows on-the-fly
physical data reorganization, as a collateral effect of query processing.
Cracking aims to continuously and automatically adapt indexes to the workload
at hand, without human intervention. Indexes are built incrementally,
adaptively, and on demand. Nevertheless, as we show, existing adaptive indexing
methods fail to deliver workload-robustness; they perform much better with
random workloads than with others. This frailty derives from the inelasticity
with which these approaches interpret each query as a hint on how data should
be stored. Current cracking schemes blindly reorganize the data within each
query's range, even if that results into successive expensive operations with
minimal indexing benefit. In this paper, we introduce stochastic cracking, a
significantly more resilient approach to adaptive indexing. Stochastic cracking
also uses each query as a hint on how to reorganize data, but not blindly so;
it gains resilience and avoids performance bottlenecks by deliberately applying
certain arbitrary choices in its decision-making. Thereby, we bring adaptive
indexing forward to a mature formulation that confers the workload-robustness
previous approaches lacked. Our extensive experimental study verifies that
stochastic cracking maintains the desired properties of original database
cracking while at the same time it performs well with diverse realistic
workloads.Comment: VLDB201
Implementasi Marker Based Tracking Augmented Reality pada Brosur Property Perumahan Berbasis Android
Salah satu bisnis yang mengalami perkembangan saat ini adalah bisnis properti. Untuk memudahkan pelanggan dalam melihat spesifikasi dan contoh properti dibutuhkan visualisasi dengan memanfaatkan teknologi Augmented Reality (AR). Penelitian ini akan mengimplementasikan teknologi AR pada brosur properti perumahan untuk visualisasi desain rumah berbasis Android dengan menggunakan Teknik Marker Based Tracking pada brosur perumahan. Pengujian aplikasi ini nantinya menggunakan kamera handphone Android dan 2 jenis marker. Kemudian menampilkan visualisasi perumahan dalam bentuk 3D agar memudahkan pengguna dalam memvisualisasikan rancangan rumah yang diinginkan. Dengan adanya aplikasi ini diharapkan akan mempermudah bagi para pengguna untuk memperoleh informasi perancangan perumahan secara lebih detail dan menarik. Hasil pengujian dengan black box testing yang dilakukan pada aplikasi sudah selesai dibangun dan didapatkan hasil bahwa aplikasi sudah dapat berjalan sesuai dengan fungsionalitas yang direncanakan. Dan berdasarkan hasil kuesioner pengujian pada aplikasi ini didapatkan hasil 94,92% dengan kategori sangat setuju yang mengindikasikan pengguna sangat setuju bahwa aplikasi ini bermanfaat dalam proses promosi penjualan dan membantu calon konsumen dalam memilih tipe desain rumah yang diinginkan
Multimedia Interaktif Pembelajaran Teknik Dasar Dan Istilah - Istilah Dalam Sepak Bola
Saat ini perkembangan olahraga di dunia saat ini semakin berkembang. Olahraga sepakbola merupakan salah satu cabang olahraga yang sangat di gemari oleh anak-anak saat ini, sepak bola di tanah air kita saat ini sudah cukup berkembang, Namun anak-anak ini juga perlu belajar untuk memahami dan menguasai teknik dasar dan istilah-istilah dari olahraga sepakbola itu sendiri.
Namun dalam bermain sepakbola, anak sekolah dasar banyak yang bermain secara asal-asalan dengan menggunakan teknik ala kadarnya. Guru olahraga di sekolah banyak yang mengajarkan pemanasan dan teknik dasar sepakbola secara asal dan tidak berpedoman pada teknik dasar yang ada. Padahal saat anak tingkat sekolah dasar merupakan saat yang tepat untuk belajar teknik dasar. Dengan demikian maka dibutuhkan sebuah media yang menarik untuk dapat membantu mengatasi masalah tersebut.
Seiring perkembangan teknologi yang makin pesat, maka untuk membantu anak sekolah dasar dalam belajar menguasai pemanasan dan teknik dasar dalam sepakbola dengan benar, dibuatlah aplikasi multimedia interaktif pembelajaran teknik dasar dan istilah-istilah dalam sepakbola untuk anak sekolah dasar. Pada aplikasi multimedia interaktif ini terdapat informasi yang lengkap dan benar tentang pemanasan, teknik, dan istilah dalam sepakbola dengan menampilkan animasi dan informasi teks agar lebih jelas dan mudah dipelajari. Multimedia interaktif teknik pembelajaran teknik dasar dan istilah-istilah dalam sepakbola untuk anak sekolah dasar dibagi menjadi 3 yaitu pemanasan, teknik, dan istilah-istilah dalam sepakbola. Pemberian animasi dan desain yang menarik, agar menjadikan aplikasi multimedia interaktif ini menarik untuk dipelajari.
Uji coba pada aplikasi multimedia interaktif pembelajaran teknik dasar dan istilah-istilah dalam sepakbola untuk anak sekolah dasar sudah dilakukan, baik oleh penyusun, maupun oleh Dosen Pembimbing dan target pemakai untuk mengevaluasi multimedia interaktif ini. Dari hasil uji coba, disimpulkan bahwa multimedia interaktif ini menarik dan dapat membantu anak sekolah dasar untuk menguasai teknik dasar dalam bermain sepakbola dengan benar
Optimizing Shipping Operations through Real-Time Monitoring and Control: A Decision Support System for Container Stripping Processes
The shipping industry plays a vital role in the global economy, with container shipping being one of the critical components. Shipping companies outline the time for customer stripping days in its contracts. The availability of the containers depends on the stripping days. The stripping days’ tardiness will hinder the availability of the containers. Therefore, it is fundamental for shipping companies to monitor both the actual condition and the contract condition of stripping days to estimate container availability and prompt customers to expedite the unloading process. However, there has yet to be a tool for monitoring the actual and the contract conditions. In this study, we used the recorded container stripping data to analyze container stripping days, tardiness, and other important parameters that indicate the performance and reliability of stripping containers. These data were post-processed and analyzed using data mining methods, and the resulting information was visualized using a dashboard to facilitate quick and effortless monitoring the dashboard in this study depicts post-processed data on container stripping days and tardiness for each port of discharge, cargo, customer, and other parameters. The dashboard was constructed using Google Data Studio. As a result, the dashboard is expected to help companies monitor, control, and analyze customers with high tardiness, allowing companies to act and ensure that the number of available containers after stripping meets demand at a given time
Case Study: First-Time Success ASIC Design Methodology Applied to a Multi-Processor System-on-Chip
Achieving first-time success is crucial in the ASIC design league considering the soaring cost, tight time-to-market window, and competitive business environment. One key factor in ensuring first-time success is a well-defined ASIC design methodology. Here we propose a novel ASIC design methodology that has been proven for the RUMPS401 (Rahman University Multi-Processor System 401) Multiprocessor System-on-Chip (MPSoC) project. The MPSoC project is initiated by Universiti Tunku Abdul Rahman (UTAR) VLSI design center. The proposed methodology includes the use of Universal Verification Methodology (UVM). The use of electronic design automation (EDA) software during each step of the design methodology is also presented. The first-time success RUMPS401 demonstrates the use of the proposed ASIC design methodology and the good of using one. Especially this project is carried on in educational environment that is even more limited in budget, resources and know-how, compared to the business and industrial counterparts. Here a novel ASIC design methodology that is tailored to first-time success MPSoC is presented
Optimizing Shipping Operations through Real-Time Monitoring and Control
The shipping industry plays a vital role in the global economy, with container shipping being one of the critical components. Shipping companies outline the time for customer stripping days in its contracts. The availability of the containers depends on the stripping days. The stripping days’ tardiness will hinder the availability of the containers. Therefore, it is fundamental for shipping companies to monitor both the actual condition and the contract condition of stripping days to estimate container availability and prompt customers to expedite the unloading process. However, there has yet to be a tool for monitoring the actual and the contract conditions. In this study, we used the recorded container stripping data to analyze container stripping days, tardiness, and other important parameters that indicate the performance and reliability of stripping containers. These data were post-processed and analyzed using data mining methods, and the resulting information was visualized using a dashboard to facilitate quick and effortless monitoring the dashboard in this study depicts post-processed data on container stripping days and tardiness for each port of discharge, cargo, customer, and other parameters. The dashboard was constructed using Google Data Studio. As a result, the dashboard is expected to help companies monitor, control, and analyze customers with high tardiness, allowing companies to act and ensure that the number of available containers after stripping meets demand at a given time
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ConvSegNet: Automated Polyp Segmentation From Colonoscopy Using Context Feature Refinement With Multiple Convolutional Kernel Sizes
Colorectal cancer occurs in the rectal of humans, and early detection has been proved to reduce its mortality rate. Colonoscopy is the standard used in detecting the presence of polyps in the rectal, and accurate segmentation of the polyps from colonoscopy images often provides helpful information for early diagnosis and treatment. Although existing deep learning models often achieve high segmentation performance when tested on the same dataset used in model training; still, their performance often degrades when applied to out-of-distribution datasets, leading to low model generalization or overfitting. This challenge is often associated with the quality of the features learnt from the input images. In this work, a novel Context Feature Refinement (CFR) module is proposed to address the challenge of low model generalization and segmentation performance. The CFR module is built to extract contextual information from the incoming feature map by using multiple parallel convolutional layers with progressively increasing kernel sizes. Using multiple parallel convolutions with different kernel sizes helped to extract more efficient multi-scale contextual information and thus enabled the network to effectively identify and segment small and fine details, as well as larger and more complex structures in the input images. Extensive experiments on three public benchmark datasets in CVC-ClinicDB, Kvasir-SEG, and BKAI-NeoPolyp showed that the proposed ConvSegNet model achieved jaccard, dice and F2 scores of 0.8650, 0.9177, and 0.9328 on CVC-ClinicDB, 0.7936, 0.8618, and 0.8855 on Kvasir-SEG, and 0.8045, 0.8747 and 0.8909 on BKAI-NeoPolyp datasets respectively. Also, an improved generalization performance was achieved by the ConvSegNet model, compared to the benchmark polyp segmentation models. Code is available at https://github.com/AOige/ConvSegNet
5-hydroxymethylcytosine marks promoters in colon that resist DNA hypermethylation in cancer
The authors would like to acknowledge the support of The University of Cambridge, Cancer Research UK (CRUK SEB-Institute Group Award A ref10182; CRUK Senior fellowship C10112/A11388 to AEKI) and Hutchison Whampoa Limited. The Human Research Tissue Bank is supported by the NIHR Cambridge Biomedical Research Centre. FF is a ULB Professor funded by grants from the F.N.R.S. and Télévie, the IUAP P7/03 programme, the ARC (AUWB-2010-2015 ULB-No 7), the WB Health program and the Fonds Gaston Ithier. Data access: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=jpwzvsowiyuamzs&acc=GSE47592Background : The discovery of cytosine hydroxymethylation (5hmC) as a mechanism that potentially controls DNA methylation changes typical of neoplasia prompted us to investigate its behaviour in colon cancer. 5hmC is globally reduced in proliferating cells such as colon tumours and the gut crypt progenitors, from which tumours can arise. Results : Here, we show that colorectal tumours and cancer cells express Ten-Eleven-Translocation (TET) transcripts at levels similar to normal tissues. Genome-wide analyses show that promoters marked by 5hmC in normal tissue, and those identified as TET2 targets in colorectal cancer cells, are resistant to methylation gain in cancer. In vitro studies of TET2 in cancer cells confirm that these promoters are resistant to methylation gain independently of sustained TET2 expression. We also find that a considerable number of the methylation gain-resistant promoters marked by 5hmC in normal colon overlap with those that are marked with poised bivalent histone modifications in embryonic stem cells. Conclusions : Together our results indicate that promoters that acquire 5hmC upon normal colon differentiation are innately resistant to neoplastic hypermethylation by mechanisms that do not require high levels of 5hmC in tumours. Our study highlights the potential of cytosine modifications as biomarkers of cancerous cell proliferation.Publisher PDFPeer reviewe
The Determinants of COVID-19 Vaccine Acceptance in Sumatra
In light of the current coronavirus disease 2019 (COVID-19) vaccination programs being implemented worldwide, this study aimed to evaluate the COVID-19 vaccine acceptance survey in Indonesia conducted by the World Health Organization (WHO), the Ministry of Health of the Republic of Indonesia, the National Immunization Technical Advisory Group (NITAG), and the United Nations Children's Fund (UNICEF), published in November 2020. It was found that Sumatra Island having lower COVID-19 vaccine acceptance rates, with Aceh Province displaying the lowest level of vaccine acceptance. Thus, a cross-sectional study was conducted, and a logistic regression analysis was used to identify the factors affecting COVID-19 vaccine acceptance. Out of 368 respondents who participated in the survey, 143 (38.9%) accepted the vaccine, and 225 (61.1%) refused it. Vaccine safety concerns constituted the most reported reason for refusal (43.6%). This study also found that province of residence and basic immunization status were determinants of COVID-19 vaccine acceptance in Sumatra. Concerns regarding vaccine safety might be the reason for the low level of vaccination in Sumatra. Increased education and encouragement from healthcare professionals and regional authority figures can alleviate public concerns and improve vaccine acceptance
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