LargeGraph

Many out-of-GPU-memory systems are recently designed to support iterative processing of large-scale graphs. However, these systems still suffer from long time to converge because of inefficient propagation of active vertices’ new states along graph paths. To efficiently support out-of-GPU-memory graph processing, this work designs a system LargeGraph . Different from existing out-of-GPU-memory systems, LargeGraph proposes a dependency-aware data-driven execution approach , which can significantly accelerate active vertices’ state propagations along graph paths with low data access cost and also high parallelism. Specifically, according to the dependencies between the vertices, it only loads and processes the graph data associated with dependency chains originated from active vertices for smaller access cost. Because most active vertices frequently use a small evolving set of paths for their new states’ propagation because of power-law property, this small set of paths are dynamically identified and maintained and efficiently handled on the GPU to accelerate most propagations for faster convergence, whereas the remaining graph data are handled over the CPU. For out-of-GPU-memory graph processing, LargeGraph outperforms four cutting-edge systems: Totem (5.19–11.62×), Graphie (3.02–9.41×), Garaph (2.75–8.36×), and Subway (2.45–4.15×).

Upaya Meningkatkan Hasil Belajar Melalui Pembelajaran Berbasis Game

Sebagai tenaga pendidik, guru dituntut untuk lebih kreatif dan inovatif dalam mengajar dan mendidik peserta didik. Penggunaan metode belajar dan media pembelajaran tentunya akan sangat mempengaruhi hasil akhir dari pelajaran yang akan dipelajari. Penggunaan media pembelajaran harus sesuai dengan pelajaran yang akan dipelajari. Penggunaan yang tepat oleh guru dapat menanamkan pemahaman konsep materi yang baik kepada siswa. Media pembelajaran juga dapat membantu guru agar tujuan pembelajaran dapat tercapai.Riana (2008:196) mengemukakan sebuah media yang efektif dan efisien serta menyenangkan tentu menjadi dambaan dan kebutuhan untuk pembelajaran, untuk mendapatkan media tersebut diperlukan beberapa prinsip yang perlu diperhatikan dalam pemilihan media. Dalam memilih media pembelajaran dipertimbangkan berbagai hal yang dirumuskan dalam satu kata ACTION, yaitu akronim dari; Access, Cost, Technology, Interactivity, Organization, dan Novelty.Salah satu bentuk dari media pembelajaran adalah game. Menurut Santoso (2019) Game adalah media bagi anak-anak untuk bisa mendapatkan pembelajaran yang memuat perkembangan kognitif, sosial, emosional, dan fisik. Game yang dikembangkan untuk pembelajaran atau biasa disebut game edukasi merupakan media belajar yang dapat memicu aktivitas siswa untuk mempelajari suatu materi pembelajaran dan dapat menumbuhkan pemahamaman tentang suatu dengan cara yang lebih menyenangkan.

A Systematic Review of Cost-Effectiveness Analyses of Novel Agents in the Treatment of Multiple Myeloma

Background: Novel therapies for multiple myeloma (MM) promise to improve outcomes but are also associated with substantial increasing costs. Evidence regarding cost-effectiveness of novel treatments is necessary, but a comprehensive up-to-date overview of the cost-effectiveness evidence of novel treatments is currently lacking. Methods: We searched Embase, Medline via Ovid, Web of Science and EconLIT ProQuest to identify all cost-effectiveness evaluations of novel pharmacological treatment of MM reporting cost per quality-adjusted life year (QALY) and cost per life year (LY) gained since 2005. Quality and completeness of reporting was assessed using the Consolidated Health Economic Evaluation Reporting Standards. Results: We identified 13 economic evaluations, comprising 32 comparisons. Our results show that novel agents generate additional LYs (range: 0.311–3.85) and QALYs (range: 0.1–2.85) compared to backbone regimens and 0.02 to 1.10 LYs and 0.01 to 0.91 QALYs for comparisons between regimens containing two novel agents. Lifetime healthcare costs ranged from USD 60,413 to 1,434,937 per patient. The cost-effectiveness ratios per QALY gained ranged from dominating to USD 1,369,062 for novel agents compared with backbone therapies and from dominating to USD 618,018 for comparisons between novel agents. Conclusions: Cost-effectiveness ratios of novel agents were generally above current willingness-to-pay thresholds. To ensure access, cost-effectiveness should be improved or cost-effectiveness ratios above current thresholds should be accepted.

Quality Assessment in Emergency Telehealth

Telemedicine is a modality for care delivery. The medicine is the same, but the manner in which it is delivered differs. As a result, quality should be assessed based on the care rendered for the given condition as well as in accordance with the National Quality Forum (NQF) Telemedicine framework, which has four domains—access, cost/financial, experience, and effectiveness. This framework for quality provides a foundation for developing objective measures to assess emergency telehealth. Among NQF Committee’s findings was that the use of various telehealth modalities improved access to health care services. The NQF also recommended measuring whether sufficient information was obtained during a telemedicine encounter to make clinical decisions regarding intervening or not intervening. It found that obtaining the appropriate actionable information was more important than measuring diagnostic accuracy.

Penerapan Metode Association Rule Mining untuk Asosiasi Ulasan Terhadap Aspek Tempat Wisata Jawa Timur Park 3

<p class="Abstrak">Google Review pada salah satu fitur Google Maps dapat menjadi salah satu media untuk mengukur tingkat kepuasan pengunjung Jawa Timur Park 3 (Jatim Park 3). Akan tetapi jumlah ulasan yang mencapai ribuan dan belum tersedianya media pengelola data ulasan dapat mempersulit manajemen Jatim Park 3 dalam mengeksplorasi dan menganalisis masukan pengunjung secara mendetail. Penelitian ini memanfaatkan teknik <em>Association Rule Mining </em>(ARM) dalam mengelola data ulasan sehingga dapat menemukan hubungan kata yang sering muncul pada ulasan. Teknik ini paling populer untuk menemukan hubungan tersembunyi antar variabel. Algoritma yang digunakan dalam mengimplementasikannya adalah algoritma Apriori karena dianggap paling efisien. Pada penelitian ini menggunakan data ulasan sebanyak 1067 ulasan dalam Bahasa Indonesia dari bulan Januari sampai bulan April tahun 2019. Berdasarkan wawancara, data tersebut digolongkan menjadi 8 aspek berdasarkan kata kunci yang sudah ditentukan sebelumnya. Aspek tersebut antara lain akses jalan, biaya, kebersihan, kepuasan, keramaian, pelayanan, keamanan, dan teknologi. Pengujian dilakukan untuk mengetahui pengaruh <em>minimum support</em> dan <em>minimum confidence</em> terhadap <em>rule</em> yang terbentuk. Keseluruhan aspek mampu menghasilkan asosiasi kata dengan algoritma Apriori. Selain itu, Keseluruhan <em>rule</em> yang terbentuk menghasilkan rata-rata <em>lift ratio</em> di atas 1 dimana rule dengan nilai lift ratio diatas 1 tersebut merupakan rule yang unik diantara rule-rule lain yang terebentuk dari asosiasi tersebut. Pada penelitian ini, rule yang terbentuk divisualisasikan untuk menampilkan keterkaitan antara kata kunci dengan aspek pada data ulasan pengunjung Jatim Park 3. Penelitian ini mencoba menggali informasi mengenai pemetaan layanan mana saja yang mendapatkan perhatian pengunjung di Jatim Park 3.</p><p class="Abstrak" align="center"> </p><p class="Judul2"><strong><em>Abstract</em></strong></p><p class="Judul2"> <em>Google Review, which is one of the features of Google Maps can be a medium to measure the satisfaction rate visitors of Jawa Timur Park 3 (Jatim Park 3). the number of reviews that reached thousands and media of review data manager is not available yet complicate the management of Jatim Park to explore and analyze visitor feedback in detail. The Association Rule Mining (ARM) technique is a text mining method that can support the knowledge discovery process in large document collections. ARM is able to link keywords to comments to find words that appear frequently. This technique is most popular for finding hidden relationships between variables. The algorithm used in this study is apriori algorithm because it is the most efficient. In this study, there are 1067 reviews of the visitors in Indonesian from January to April 2019 as the data. The data is classified into 8 aspects based on predetermined keywords. These aspects include road access, cost, cleanliness, satisfaction, hustle, service, security, and technology. Testing was conducted to determine the minimum support and minimum confidence impact of the established rules. The whole aspects is capable of generating word associations with an Apriori algorithm. In addition, the overall rules that are formed produce an average lift ratio above 1 where the rule with that value is a unique rule among other rules formed from the association. In this study, the rules that are formed are visualized to show the relationship between keywords and aspects of visitor reviews of Jatim Park 3. This research tries to dig up information about mapping which services get the attention of visitors in Jatim Park 3.</em></p>

HARNAS: Human Activity Recognition Based on Automatic Neural Architecture Search Using Evolutionary Algorithms

Human activity recognition (HAR) based on wearable sensors is a promising research direction. The resources of handheld terminals and wearable devices limit the performance of recognition and require lightweight architectures. With the development of deep learning, the neural architecture search (NAS) has emerged in an attempt to minimize human intervention. We propose an approach for using NAS to search for models suitable for HAR tasks, namely, HARNAS. The multi-objective search algorithm NSGA-II is used as the search strategy of HARNAS. To make a trade-off between the performance and computation speed of a model, the F1 score and the number of floating-point operations (FLOPs) are selected, resulting in a bi-objective problem. However, the computation speed of a model not only depends on the complexity, but is also related to the memory access cost (MAC). Therefore, we expand the bi-objective search to a tri-objective strategy. We use the Opportunity dataset as the basis for most experiments and also evaluate the portability of the model on the UniMiB-SHAR dataset. The experimental results show that HARNAS designed without manual adjustments can achieve better performance than the best model tweaked by humans. HARNAS obtained an F1 score of 92.16% and parameters of 0.32 MB on the Opportunity dataset.

The Extensive Margin of Exporting Products: A Firm-Level Analysis

To quantify trade frictions, we examine multiproduct exporters. We build a flexible general-equilibrium model and estimate market entry costs using Brazilian firm-product-destination data under rich demand and market access cost shocks. Our estimates show that additional products farther from a firm’s core competency come at higher production costs, but there are substantive economies of scope in market access costs. Market access costs differ across destinations, falling more rapidly in scope at nearby regions and at destinations with fewer nontariff barriers. We evaluate a counterfactual scenario that harmonizes market access costs across destinations and find global welfare gains similar to eliminating all current tariffs. (JEL D22, F12, F13, F14, O14, O19)

Perceptions of Cervical Cancer Screening in Rural Guatemala

Cervical cancer (CC) is the second most common cause of cancer-related mortality in the developing world. Globally, the incidence of CC is 13.1 per 100,000, with the highest incidence of CC seen in sub-Saharan Africa, Melanesia, Latin America and the Caribbean, Southcentral Asia, and Southeast Asia. Little data exist regarding perceptions of screening in Guatemala and how this may affect the likelihood that women seek care. This study aimed to assess the attitudes, perceptions, and beliefs of CC screening in women of Rural Guatemala. A cross-sectional mixed method analysis was administered using a survey given to 169 women in San Pedro La Laguna in Sololá, Guatemala. Results showed that none of the indigenous-language-speaking patients and only half of the bilingual patients had knowledge of human papillomavirus; 97% of women indicated that they believed regular Pap smears are important; only 46.4% of women screened had received a Pap smear at some point in their lives, which is slightly above the national average (39.3%). This is due to barriers to access, cost of treatment, and knowledge of CC. Results of this study display a positive perception of CC screening by indigenous women, indicating that efforts should be made to move toward the implementation of low-cost CC screening methods.

Open Science in Kenya: Where Are We?

According to the United Nations Educational, Scientific, and Cultural Organization (UNESCO), Open Science is the movement to make scientific research and data accessible to all. It has great potential for advancing science. At its core, it includes (but is not limited to) open access, open data, and open research. Some of the associated advantages are promoting collaboration, sharing and reproducibility in research, and preventing the reinvention of the wheel, thus saving resources. As research becomes more globalized and its output grows exponentially, especially in data, the need for open scientific research practices is more evident — the future of modern science. This has resulted in a concerted global interest in open science uptake. Even so, barriers still exist. The formal training curriculum in most, if not all, universities in Kenya does not equip students with the knowledge and tools to subsequently practice open science in their research. Therefore, to work openly and collaboratively, there is a need for awareness and training in the use of open science tools. These have been neglected, especially in most developing countries, and remain barriers to the cause. Moreover, there is scanty research on the state of affairs regarding the practice and/or adoption of open science. Thus, we developed, through the OpenScienceKE framework, a model to narrow the gap. A sensitize-train-hack-collaborate model was applied in Nairobi, the economic and administrative capital of Kenya. Using the model, we sensitized through seminars, trained on the use of tools through workshops, applied the skills learned in training through hackathons to collaboratively answer the question on the state of open science in Kenya. While the former parts of the model had 20–50 participants, the latter part mainly involved participants with a bioinformatics background, leveraging their advanced computational skills. This model resulted in an open resource that researchers can use to publish as open access cost-effectively. Moreover, we observed a growing interest in open science practices in Kenya through literature search and data mining and that lack of awareness and skills may still hinder the adoption and practice of open science. Furthermore, at the time of the analyses, we surprisingly found that out of the 20,069 papers downloaded from BioRXiv, only 18 had Kenyan authors, a majority of which are international (16) collaborations. This may suggest poor uptake of the use of preprints among Kenyan researchers. The findings in this study highlight the state of open science in Kenya and challenges facing its adoption and practice while bringing forth possible areas for primary consideration in the campaign toward open science. It also proposes a model (sensitize-train-hack-collaborate model) that may be adopted by researchers, funders and other proponents of open science to address some of the challenges faced in promoting its adoption in Kenya.

Westdrive X LoopAR: An Open-Access Virtual Reality Project in Unity for Evaluating User Interaction Methods during Takeover Requests

With the further development of highly automated vehicles, drivers will engage in non-related tasks while being driven. Still, drivers have to take over control when requested by the car. Here, the question arises, how potentially distracted drivers get back into the control-loop quickly and safely when the car requests a takeover. To investigate effective human–machine interactions, a mobile, versatile, and cost-efficient setup is needed. Here, we describe a virtual reality toolkit for the Unity 3D game engine containing all the necessary code and assets to enable fast adaptations to various human–machine interaction experiments, including closely monitoring the subject. The presented project contains all the needed functionalities for realistic traffic behavior, cars, pedestrians, and a large, open-source, scriptable, and modular VR environment. It covers roughly 25 km2, a package of 125 animated pedestrians, and numerous vehicles, including motorbikes, trucks, and cars. It also contains all the needed nature assets to make it both highly dynamic and realistic. The presented repository contains a C++ library made for LoopAR that enables force feedback for gaming steering wheels as a fully supported component. It also includes all necessary scripts for eye-tracking in the used devices. All the main functions are integrated into the graphical user interface of the Unity® editor or are available as prefab variants to ease the use of the embedded functionalities. This project’s primary purpose is to serve as an open-access, cost-efficient toolkit that enables interested researchers to conduct realistic virtual reality research studies without costly and immobile simulators. To ensure the accessibility and usability of the mentioned toolkit, we performed a user experience report, also included in this paper.