A perfect matching in a $3$-uniform hypergraph on $n=3k$ vertices is subset of $\frac{n}{3}$ disjoint edges. We prove that if $H$ such every vertex belongs to at least ${n-1\choose 2} - {2n/3\choose 2}+1$ edges, then contains matching. give construction show this result the best possible.

In many graphs such as social networks, nodes have associated attributes representing their behavior. Predicting node in is an important task with applications domains like recommendation systems, privacy preservation, and targeted advertisement. Attribute values can be predicted by treating each a data point described employing classification/regression algorithms. However, there complex interdependence between pairwise interaction. For instance, of are influenced neighbors (social...

Software Defined Networking (SDN) is a network paradigm shift that facilitates comprehensive programmability to cope with emerging new technologies such as cloud computing and big data. SDN simplified centralized management enabling it operate in dynamic scenarios. Further, uses the OpenFlow protocol for communication between controller its switches. The creates vulnerabilities attacks especially Distributed Denial of Service (DDoS). DDoS are launched from compromised hosts connected In this...

SARS-CoV-2, like any other virus, continues to mutate as it spreads, according an evolutionary process. Unlike the number of currently available sequences SARS-CoV-2 in public databases such GISAID is already several million. This amount data has potential uncover dynamics a virus never before. However, million orders magnitude beyond what can be processed by traditional methods designed reconstruct virus's history, those that build phylogenetic tree. Hence, new and scalable will need...

A major challenge in computational antibody design is the accurate identification of antigen binding site, i.e., epitope. The current approaches to epitope prediction struggle because variational nature epitopes and lack availability experimental datasets. However, deep learning-based have shown great promise achieving better results for task recent years. Moreover, there now potential epitope-prediction research newly released largest-of-its-kind benchmark dataset, Antibody-specific Epitope...

Machine learning (ML) models, such as SVM, for tasks like classification and clustering of sequences, require a definition distance/similarity between pairs sequences. Several methods have been proposed to compute the similarity exact approach that counts number matches k-mers (sub-sequences length k) an approximate estimates pairwise scores. Although yield better performance, they pose high computational costs, limiting their applicability small The algorithms are proven be more scalable...

Accurate short-term load forecasting is essential for the efficient operation of power sector. Forecasting at a fine granularity such as hourly loads individual households challenging due to higher volatility and inherent stochasticity. At aggregate levels, monthly grid, uncertainties fluctuations are averaged out; hence predicting more straightforward. This paper proposes method called using Matrix Factorization (fmf) (stlf). fmf only utilizes historical data from consumers' smart meters...

Accurate short term electricity load forecasting is crucial for efficient operations of the power sector. Predicting loads at a fine granularity (e.g. households) made challenging due to large number (known or unknown) factors affecting consumption. At larger scales clusters consumers), since inherent stochasticity and fluctuations are averaged out, problem becomes substantially easier. In this work we propose method hourly) scale (households). Our use hourly consumption data certain period...

Social media platforms and online forums generate a rapid increasing amount of textual data. Businesses, government agencies, organizations seek to perform sentiment analysis on this rich text The results these analytics are used for adapting marketing strategies, customizing products, security, various other decision makings. Sentiment has been extensively studied methods have developed it with great success. These methods, however, apply texts written in specific language. This limits the...

Structural health monitoring (SHM) systems are widely used for civil infrastructure monitoring. Data acquired from the SHM play an important role in assessing structural integrity and determining further maintenance activities. Considering that sensors installed a harsh environment long-term measurements, some can malfunction produce faulty data. As large amount of measured data is often desired to be automatically processed adversely affect assessments, identifying such abnormal important....

Given a network of nodes, minimizing the spread contagion using limited budget is well-studied problem with applications in security, viral marketing, social networks, and public health. In real graphs, virus may infect node which turn infects its neighbour nodes this trigger an epidemic whole graph. The goal thus to select best k (budget constraint) that are immunized (vaccinated, screened, filtered) so as remaining graph less prone epidemic. It known is, all practical models,...

The advancement in cloud networks has enabled connectivity of both traditional networked elements and new devices from all walks life, thereby forming the Internet Things (IoT). In an IoT setting, improving scaling network components as well reducing cost is essential to sustain exponential growth. this domain, software-defined networking (SDN) revolutionizing infrastructure with a paradigm. SDN splits control/routing logic data transfer/forwarding. This splitting causes many issues SDN,...