693 real negative results, null findings, and replication failures in Computer Science · Negative / Null Result Report. Search the index →
WASTE indexes published research — it does not host or republish full papers. Each entry is a metadata record compiled from open scholarly databases; the abstract is shown in full only where the paper is openly licensed, otherwise a short excerpt under fair use. Classifications are automated and approximate.
Troels F. Rønnow, Zhihui Wang, Joshua Job et al. · 2014 · Science
The development of small-scale quantum devices raises the question of how to fairly assess and detect quantum speedup. Here, we show how to define and measure quantum speedup and how to avoid pitfalls that might mask or fake such a…
View details →Youngjoon Choi, Miju Choi, Munhyang Oh et al. · 2019 · Journal of Hospitality Marketing & Management
Hotel industry started to adopt service robots, which are considered a future workforce. However, no attempt was conducted to examine the dimensionality of service quality of service robots. This paper aims to understand the influence of…
View details →Jafar Tanha, Yousef Abdi, Negin Samadi et al. · 2020 · Journal Of Big Data
Abstract Since canonical machine learning algorithms assume that the dataset has equal number of samples in each class, binary classification became a very challenging task to discriminate the minority class samples efficiently in imbalanced datasets. For this reason, researchers have been paid attention and have proposed many methods to deal with this problem, which can be broadly categorized into data level and algorithm level. Besides, multi-class imbalanced learning is much harder than binary one and is still an open problem. Boosting algorithms are a class of ensemble learning methods in
View details →Petra Valíčková, Tomáš Havránek, Roman Horváth · 2014 · Journal of Economic Surveys
Abstract We analyze 1334 estimates from 67 studies that examine the effect of financial development on economic growth. Taken together, the studies imply a positive and statistically significant effect, but the individual estimates vary…
View details →Frederick M. Howard, James M. Dolezal, Sara Kochanny et al. · 2021 · Nature Communications
The Cancer Genome Atlas (TCGA) is one of the largest biorepositories of digital histology. Deep learning (DL) models have been trained on TCGA to predict numerous features directly from histology, including survival, gene expression patterns, and driver mutations. However, we demonstrate that these features vary substantially across tissue submitting sites in TCGA for over 3,000 patients with six cancer subtypes. Additionally, we show that histologic image differences between submitting sites can easily be identified with DL. Site detection remains possible despite commonly used color normaliz
View details →Indah Lestari · 2015 · Formatif Jurnal Ilmiah Pendidikan MIPA
<p>The purpose of this research was to the determinate the effect of study time on <br />mathematics learning outcomes. To determinate the effect of interest in earning the mathematics learning outcomes. To determinate the…
View details →James R. Lewis · 2018 · International Journal of Human-Computer Interaction
The primary purpose of this research was to investigate the relationship between two widely used questionnaires designed to measure perceived usability: the Computer System Usability Questionnaire (CSUQ) and the System Usability Scale…
View details →Christian Conrad, Anessa Custovic, Éric Ghysels · 2018 · Journal of risk and financial management
We use the GARCH-MIDAS model to extract the long- and short-term volatility components of cryptocurrencies. As potential drivers of Bitcoin volatility, we consider measures of volatility and risk in the US stock market as well as a measure of global economic activity. We find that S&P 500 realized volatility has a negative and highly significant effect on long-term Bitcoin volatility. The finding is atypical for volatility co-movements across financial markets. Moreover, we find that the S&P 500 volatility risk premium has a significantly positive effect on long-term Bitcoin volatility
View details →Marco Gui, Gianluca Argentin · 2011 · New Media & Society
This article outlines the main results and methodological challenges of a large-scale survey on actual digital skills. A test covering three main dimensions of digital literacy (theoretical, operational and evaluation skills) was…
View details →Geoffrey Gorisse, Olivier Christmann, Étienne Armand Amato et al. · 2017 · Frontiers in Robotics and AI
Current design of virtual reality (VR) applications relies essentially on the transposition of users' viewpoint in first-person perspective (1PP). Within this context, our research aims to compare the impact and the potentialities enabled via the integration of the third-person perspective (3PP) in immersive virtual environments (IVE). Our empirical study is conducted in order to assess the sense of presence, the sense of embodiment and performance of users confronted with a series of tasks presenting a case of potential use for the video game industry. Our results do not reveal significant di
View details →Deanna D. Caputo, Shari Lawrence Pfleeger, Jesse D. Freeman et al. · 2013 · IEEE Security & Privacy
To explore the effectiveness of embedded training, researchers conducted a large-scale experiment that tracked workers' reactions to a series of carefully crafted spear phishing emails and a variety of immediate training and awareness…
View details →Anita Nanda, Bibhuti Bhusan Mohapatra, Abikesh Prasada Kumar Mahapatra et al. · 2021 · International Journal of Statistics and Applied Mathematics
Examining a huge amount of data is a typical issue in any research process. However, different statistical processes and techniques play essential role to derive a meaningful conclusion from the presented enormous data. Control of type I…
View details →Godfrey Tan, John V. Guttag · 2026 · arXiv (Cornell University)
The performance seen by individual clients on a wireless local area network (WLAN) is heavily influenced by the manner in which wireless channel capacity is allocated. The popular MAC protocol DCF (Distributed Coordination Function) used…
View details →Hélder Sebastião, Pedro Godinho · 2021 · Financial Innovation
This study examines the predictability of three major cryptocurrencies-bitcoin, ethereum, and litecoin-and the profitability of trading strategies devised upon machine learning techniques (e.g., linear models, random forests, and support vector machines). The models are validated in a period characterized by unprecedented turmoil and tested in a period of bear markets, allowing the assessment of whether the predictions are good even when the market direction changes between the validation and test periods. The classification and regression methods use attributes from trading and network activi
View details →Michel E. Vandenberghe, Marietta Scott, Paul W. Scorer et al. · 2017 · Scientific Reports
Tissue biomarker scoring by pathologists is central to defining the appropriate therapy for patients with cancer. Yet, inter-pathologist variability in the interpretation of ambiguous cases can affect diagnostic accuracy. Modern artificial intelligence methods such as deep learning have the potential to supplement pathologist expertise to ensure constant diagnostic accuracy. We developed a computational approach based on deep learning that automatically scores HER2, a biomarker that defines patient eligibility for anti-HER2 targeted therapies in breast cancer. In a cohort of 71 breast tumour r
View details →Fazle Karim, Somshubra Majumdar, Houshang Darabi · 2019 · IEEE Access
Long short-term memory fully convolutional neural networks (LSTM-FCNs) and Attention LSTM-FCN (ALSTM-FCN) have shown to achieve the state-of-the-art performance on the task of classifying time series signals on the old University of…
View details →Gang Wang, Christo Wilson, Xiaohan Zhao et al. · 2012
Popular Internet services in recent years have shown that remarkable things can be achieved by harnessing the power of the masses using crowd-sourcing systems. However, crowd-sourcing systems can also pose a real challenge to existing…
View details →Ala Al‐Fuqaha, Abdallah Khreishah, Mohsen Guizani et al. · 2015 · IEEE Communications Magazine
Several divergent application protocols have been proposed for Internet of Things (IoT) solutions including CoAP, REST, XMPP, AMQP, MQTT, DDS, and others. Each protocol focuses on a specific aspect of IoT communications. The lack of a…
View details →Gintare Karolina Dziugaite, Daniel M. Roy, Zoubin Ghahramani · 2015 · arXiv (Cornell University)
We consider training a deep neural network to generate samples from an unknown distribution given i.i.d. data. We frame learning as an optimization minimizing a two-sample test statistic---informally speaking, a good generator network…
View details →Guido Makransky, Gustav Bøg Petersen, Sara Klingenberg · 2020 · British Journal of Educational Technology
Abstract Science‐related competencies are demanded in many fields, but attracting more students to scientific educations remains a challenge. This paper uses two studies to investigate the value of using Immersive Virtual Reality (IVR)…
View details →Elie Bouri, Luis A. Gil‐Alana, Rangan Gupta et al. · 2018 · International Journal of Finance & Economics
Abstract Motivated by the emergence of Bitcoin as a speculative financial investment, the purpose of this paper is to examine the persistence in the level and volatility of Bitcoin price, accounting for the impact of structural breaks.…
View details →Lee D. Walsh, G. Lorimer Moseley, Janet L. Taylor et al. · 2011 · The Journal of Physiology
The sense of body ownership, knowledge that parts of our body ‘belong’ to us, is presumably developed using sensory information. Cutaneous signals seem ideal for this and can modify the sense of ownership. For example, an illusion of…
View details →Moritz Beller, Georgios Gousios, Annibale Panichella et al. · 2015
The research community in Software Engineering and Software Testing in particular builds many of its contributions on a set of mutually shared expectations. Despite the fact that they form the basis of many publications as well as…
View details →Sunbok Lee, Jae Young Chung · 2019 · Applied Sciences
A dropout early warning system enables schools to preemptively identify students who are at risk of dropping out of school, to promptly react to them, and eventually to help potential dropout students to continue their learning for a better future. However, the inherent class imbalance between dropout and non-dropout students could pose difficulty in building accurate predictive modeling for a dropout early warning system. The present study aimed to improve the performance of a dropout early warning system: (a) by addressing the class imbalance issue using the synthetic minority oversampling t
View details →Peter E. Clark, Oren Etzioni, Tushar Khot et al. · 2016 · Proceedings of the AAAI Conference on Artificial Intelligence
What capabilities are required for an AI system to pass standard 4th Grade Science Tests? Previous work has examined the use of Markov Logic Networks (MLNs) to represent the requisite background knowledge and interpret test questions, but…
View details →Mary McGlohon, Natalie Glance, Zach Reiter · 2010 · Proceedings of the International AAAI Conference on Web and Social Media
Given a set of reviews of products or merchants from a wide range of authors and several reviews websites, how can we measure the true quality of the product or merchant? How do we remove the bias of individual authors or sources? How do…
View details →Ramlawati Ramlawati, Eva Trisnawati, Nurfatwa Andriani Yasin et al. · 2020 · Management Science Letters
The purpose of this study was to determine the alternative external influence and job stress on employee satisfaction and to determine the effects of the alternative external influence, job satisfaction job stress on Turnover Intention on employees of PT Bank Mandiri Regional X South Sulawesi. Respondents in this study were 100 people. The analysis model used to determine the effect between variables was a structural model with the Partial Least Square (PLS) approach. The results show that external alternatives had a significant effect on job satisfaction, stress had no significant effect on j
View details →Abu Saleh Musa Miah, Jungpil Shin, Md. Al Mehedi Hasan et al. · 2022 · Applied Sciences
Sign language recognition is one of the most challenging applications in machine learning and human-computer interaction. Many researchers have developed classification models for different sign languages such as English, Arabic, Japanese, and Bengali; however, no significant research has been done on the general-shape performance for different datasets. Most research work has achieved satisfactory performance with a small dataset. These models may fail to replicate the same performance for evaluating different and larger datasets. In this context, this paper proposes a novel method for recogn
View details →Manamba Epaphra, Ales H. Mwakalasya · 2017 · Modern Economy
This paper analyzes the effect of foreign direct investment (FDI) on agricultural sector in Tanzania. The paper also examines the declining contribution of agriculture to real GDP growth despite the fact that the sector employs more than 70 percent of the total labour force. Annual time series data spanning from 1990 to 2015 are used to test the significance of the relationship between FDI inflow and agriculture value added-to-GDP ratio on one hand and FDI inflows and economic growth on the other hand. Also, the relationship between agriculture value added and economic growth rate is empirical
View details →Başak Alper, Tobias Höllerer, JoAnn Kuchera-Morin et al. · 2011 · IEEE Transactions on Visualization and Computer Graphics
In this paper we present a new technique and prototype graph visualization system, stereoscopic highlighting, to help answer accessibility and adjacency queries when interacting with a node-link diagram. Our technique utilizes stereoscopic…
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