703 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.
Shervin Malmasi · 2016 · Figshare
The prediction of an author's native language using only their second language writing -- a task called Native Language Identification (NLI) -- is usually tackled using supervised classification. This is underpinned by the presupposition…
View details →Julio Cesar Munguía Mondragón, Paula Branco, Guy-Vincent Jourdan et al. · 2025 · Applied Intelligence
Globally, cyberattacks are growing and mutating each month. Intelligent Intrusion Network Detection Systems are developed to analyze and detect anomalous traffic to face these threats. A way to address this is by using network flows, an…
View details →Tianjiao Cao, Jiahao Lyu, Weichao Zeng et al. · 2024
Scene text detection has seen the emergence of high-performing methods that excel on academic benchmarks. However, these detectors often fail to replicate such success in real-world scenarios. We uncover two key factors contributing to…
View details →Akhil Arora, Mayank Sachan, Arnab Bhattacharya · 2014
The steady growth of graph data in various applications has resulted in wide-spread research in finding significant sub-structures in a graph. In this paper, we address the problem of finding statistically significant connected subgraphs…
View details →Michael S. Vitevitch, Gavin J. D. Mullin · 2021 · Brain Sciences
Cognitive network science is an emerging approach that uses the mathematical tools of network science to map the relationships among representations stored in memory to examine how that structure might influence processing. In the present study, we used computer simulations to compare the ability of a well-known model of spoken word recognition, TRACE, to the ability of a cognitive network model with a spreading activation-like process to account for the findings from several previously published behavioral studies of language processing. In all four simulations, the TRACE model failed to retr
View details →Joshua K. Hartshorne, Lauren Skorb, Sven L. Dietz et al. · 2019 · Collabra Psychology
We report the first set of results in a multi-year project to assess the robustness – and the factors promoting robustness – of the adult statistical word segmentation literature. This includes eight total experiments replicating six different experiments. The purpose of these replications is to assess the reproducibility of reported experiments, examine the replicability of their results, and provide more accurate effect size estimates. Reproducibility was mixed, with several papers either lacking crucial details or containing errors in the description of method, making it difficult to ascert
View details →Wilhelmiina Hämäläinen · 2010 · Työväentutkimus Vuosikirja
Analyzing statistical dependencies is a fundamental problem in all empirical science. Dependencies help us understand causes and effects, create new scientific theories, and invent cures to problems. Nowadays, large amounts of data is…
View details →Robert J. Smith · 2016 · Methods in Ecology and Evolution
Summary Dissimilarity measures, which gauge compositional resemblance between sample units, tend to lose information with increasing distance along ecological gradients. This undesirable property is especially common in high‐beta‐diversity…
View details →Jundong Li, Osmar R. Zaı̈ane · 2017 · Intelligent Data Analysis
Established associative classification algorithms have shown to be very effective in handling categorical data such as text data. The learned model is a set of rules that are easy to understand and can be edited. However, they still suffer…
View details →Nima Jamalian, Marco Gillies, Frédéric Fol Leymarie et al. · 2022
Until recently, Virtual Reality (VR) applications relied on controllers to enable user interaction in virtual environments. With advances in tracking technology, HMDs are now able to track the movements of users’ hands in real-time with…
View details →Arvinder Kaur, Kamaldeep Kaur, Shilpi Jain · 2016
The objective of this paper is to study the relationship between different types of object-oriented software metrics, code smells and actual changes in software code that occur during maintenance period. It is hypothesized that code smells…
View details →Scott Grimm, Louise McNally · 2026 · Proceedings of the Amsterdam Colloquium
Syntacticians have widely assumed since [11] that there is a fundamental difference between so-called argument structure nominals (AS-nominals, also called Complex Event Nominals), e.g. destruction, and non-AS-nominals, e.g. book ([1, 5], i.a.). Grimshaw provided a list of properties characterizing AS-nominals, most notably that they have obligatory arguments (e.g. the destruction *(of Carthage) by the Romans). She and others have associated having argument structure with having event structure, but it has never been clear what having or lacking such structures amounts to semantically. In this
View details →Sun Kyong Lee, Hyunjin Park, Seoyoung C. Kim · 2024 · Behaviour and Information Technology
This study investigated the impact of task types (functional vs. social) and the gendered voices (female vs. male) of Siri, an intelligent virtual assistant (IVA), on social presence and trust perceptions toward the IVA.In an online…
View details →Rabab Ali Abumalloh, Mehrbakhsh Nilashi, Osama Halabi et al. · 2024 · Journal of Innovation & Knowledge
Recommendation agents (RAs) have proven to be effective decision-making tools for customers, as they can boost trust and loyalty when customers shop online. They can analyse large amounts of data using machine learning algorithms and…
View details →Robert Ranisch, Joschka Haltaufderheide · 2025 · Digital Society
Abstract Conversational agents are increasingly used in healthcare, with Large Language Models (LLMs) significantly enhancing their capabilities. When integrated into social robots, LLMs offer the potential for more natural interactions. However, while LLMs promise numerous benefits, they also raise critical ethical concerns, particularly regarding hallucinations and deceptive patterns. In this case study, we observed a critical pattern of deceptive behavior in commercially available LLM-based care software integrated into robots. The LLM-equipped robot falsely claimed to have medication remin
View details →Remita Austin, R. Parvathi · 2025 · Scientific Reports
The absence of reliable early treatment serves as one of the main causes of cervical cancer. Hence, it is crucial to detect cervical cancer early. The biggest challenge in diagnosing cervical cancer early is that it is asymptomatic until it develops into invasive carcinoma. In medical applications, the use of machine learning and deep learning is successful as a classifier in the preliminary identification of cancerous cells in the cervical region. In our study, we present a CNN-based method for the classification of cervical cancer cells. We present a method for accurately classifying Pap sme
View details →Catriona L. Scrivener, Tijl Grootswagers, Alexandra Woolgar · 2026 · European Journal of Neuroscience
Multivariate pattern analysis (MVPA) is a popular technique that can distinguish between condition-specific patterns of activation. Applied to neuroimaging data, MVPA decoding for inference uses above chance decoding to identify statistically robust condition-specific information in neuroimaging data, which may be missed by univariate methods. However, several analysis choices influence decoding results, and the combined effects of these choices have not been fully evaluated. In particular, an increasingly popular approach is to average data from several trials together before training an MVPA
View details →Sarah Kettley · 2026 · Edinburgh Napier Research Repository (Edinburgh Napier University)
The purpose of the research described in this thesis was to develop a design methodology for Wearable Computing concepts that could potentially embody authenticity. The Wearables community, still firmly rooted in the disciplines of engineering and ergonomics, had made clear its aspirations to the mainstream market (DeVaul et al 2001). However, at this point, there was a distinct lack of qualitative studies on user perceptions of Wearable products. A review of the market research literature revealed significant consumer demand for authenticity in goods and services, and it was this need that dr
View details →Nikunj Arora, Markku Suomalainen, Matti Pouke et al. · 2022 · IEEE Transactions on Visualization and Computer Graphics
We propose augmenting immersive telepresence by adding a virtual body, representing the user's own arm motions, as realized through a head-mounted display and a 360-degree camera. Previous research has shown the effectiveness of having a virtual body in simulated environments; however, research on whether seeing one's own virtual arms increases presence or preference for the user in an immersive telepresence setup is limited. We conducted a study where a host introduced a research lab while participants wore a head-mounted display which allowed them to be telepresent at the host's physical loc
View details →Vincent Adegoke, Daqing Chen, Ebad Banissi et al. · 2017
In this paper, several ensemble cancer survivability predictive models are presented and tested based on three variants of AdaBoost algorithm. In the models we used Random Forest, Radial Basis Function Network and Neural Network algorithms…
View details →Subrata Datta, Kalyani Mali · 2021
Traditional support-confidence framework based association rule mining approaches often generate huge number of rules including the insignificant ones. These insignificant association rules are useless in knowledge discovery. One of the…
View details →Haoze Wu · 2017
In this project, we aimed to improve the runtime of Minisat, a Conflict-Driven Clause Learning (CDCL) solver that solves the Propositional Boolean Satisfiability (SAT) problem. We first used a logistic regression model to predict the…
View details →Suhe Ji, Ke Li, Linfeng Zou · 2019 · 2019 International Joint Conference on Information, Media and Engineering (IJCIME)
Although the increased use of authentic materials in listening comprehension teaching has become general practice, it is crucial to find out whether or not the new technology-supported authentic material could be beneficial to English as a…
View details →Conor Hanrahan · 2019 · ARROW@Dublin Institute of Technology (Dublin Institute of Technology)
The presence of noise in electroencephalography (EEG) signals can significantly reduce the accuracy of the analysis of the signal. This study assesses to what extent stacked autoencoders designed using one-dimensional convolutional neural…
View details →Fabrice Djatsa · 2019 · Journal of Information Security
As the economy increases its dependence on the internet to increase efficiency and productivity in all aspects of society, close attention has been directed to solve the challenges related to internet security. Despite the large amount of…
View details →Dunigan Parker Folk, Elizabeth Dunn · 2026 · Psychological Science
Advances in AI have enabled chatbots to provide warm, personalized support. Yet little is known about the long-term consequences of AI companionship. Across a 12-month longitudinal study with more than 2,000 adults from four Western…
View details →Ramteja Sajja, Yusuf Sermet, Brian Fodale et al. · 2026 · Scientific Reports
As generative AI becomes increasingly integrated into higher education, understanding how students engage with these technologies is essential for responsible adoption. This study evaluates the Educational AI Hub, an AI-powered learning…
View details →Pertti Vakkari · 2011 · Online Information Review
Purpose This paper seeks to evaluate to what extent Google retrieved correct answers to queries inferred from factual and topical requests in a digital Ask‐a‐Librarian service. Design/methodology/approach In total, 100 factual and 100…
View details →Mohammadreza Farrokhnia, Saeed Latifi, Pantelis M. Papadopoulos et al. · 2026 · International Journal of Educational Technology in Higher Education
Abstract Providing high-quality feedback on student writing is essential yet increasingly difficult due to rising class sizes and limited instructional capacity. Generative AI (GenAI) offers a promising and scalable alternative, but its effectiveness compared to traditional teacher feedback, particularly across different prompting techniques, remains uncertain. This study employed a quantitative, randomized three-group experimental design with 70 graduate students to compare the effects of teacher feedback and GenAI feedback generated using two prompting techniques: Zero-shot and chain-of-thou
View details →Eisha Hassan, Fazila‐Tun‐Nesa Malik, Qazi Waqas Khan et al. · 2025 · IEEE Access
Document Clustering has attracted the interest of many researchers who have created several solutions to this problem by combining different techniques, models, and algorithms. While famous for its simplicity, the most commonly used algorithm, K-Means, suffers from issues such as finding the optimal value for k and random initialization of the centroids. In this paper, we propose a hybrid methodology combining K-Means++ with the metaheuristic algorithm PSO to overcome the challenges of both these algorithms. K-Means++ is a smart initialization technique that selects clusters based on probabili
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