A Shared Natural Neighbors Based-Hierarchical Clustering Algorithm for Discovering Arbitrary-Shaped Clusters

In clustering algorithms,the selection of neighbors significantly affects the quality of the final clustering results.While various neighbor relationships exist,such as K-nearest neighbors,natural neighbors,and shared neighbors,most neighbor relationships can only handle single structural relationships,and the identification accuracy is low for datasets with multiple structures.In life,people’s first instinct for complex things is to divide them into multiple parts to complete.Partitioning the dataset into more sub-graphs is a good idea approach to identifying complex structures.Taking inspiration from this,we propose a novel neighbor method:Shared Natural Neighbors(SNaN).To demonstrate the superiority of this neighbor method,we propose a shared natural neighbors-based hierarchical clustering algorithm for discovering arbitrary-shaped clusters(HC-SNaN).Our algorithm excels in identifying both spherical clusters and manifold clusters.Tested on synthetic datasets and real-world datasets,HC-SNaN demonstrates significant advantages over existing clustering algorithms,particularly when dealing with datasets containing arbitrary shapes.

Active learning accelerated Monte-Carlo simulation based on the modified K-nearest neighbors algorithm and its application to reliability estimations

This paper proposes an active learning accelerated Monte-Carlo simulation method based on the modified K-nearest neighbors algorithm.The core idea of the proposed method is to judge whether or not the output of a random input point can be postulated through a classifier implemented through the modified K-nearest neighbors algorithm.Compared to other active learning methods resorting to experimental designs,the proposed method is characterized by employing Monte-Carlo simulation for sampling inputs and saving a large portion of the actual evaluations of outputs through an accurate classification,which is applicable for most structural reliability estimation problems.Moreover,the validity,efficiency,and accuracy of the proposed method are demonstrated numerically.In addition,the optimal value of K that maximizes the computational efficiency is studied.Finally,the proposed method is applied to the reliability estimation of the carbon fiber reinforced silicon carbide composite specimens subjected to random displacements,which further validates its practicability.

Cultural Adaptation in Tim Winton's "Neighbors"

As the most productive and prestigious writer in contemporary Australian literature,Tim Winton is noted not only for his novels but also for his short stories.Neighbors is a case in point.The short story describes the daily trivial incidents in the multi-cultural background according to the line of a newly-weds moving to a new neighborhood.The young couple gradually understood and communicated with their neighbors and eventually achieved cultural adaptation.

China and Its Neighbors

After the September 11 events, America timely took the opportunity of antiterrorism to spread its offensive to Central Asia. In so doing, its intention to push for its policy of "managing " Eurasia has become prominent. Undoubtedly, America’s series of measures ignited changes of the situation in China’s surrounding regions, bringing many negative

From Culture Shock to Cultural Assimilations in Tim Winton's Neighbors

Cultural assimilation consists of three stages:frustration and unease,acceptance mixed with interval uncertainty,assimilation.As a prestigious Western Australian,Tim Winton is famous for his novels and short stories.Based on one of his popular short stories Neighbors,this essay aims to point out that a willingness to change and the powerful influence of the surroundings are both critical when one tries to get merged into a new culture.

An Adaptive Steganographic Algorithm for Point Geometry Based on Nearest Neighbors Search

In this study, we extend our previous adaptive steganographic algorithm to support point geometry. For the purpose of the vertex decimation process presented in the previous work, the neighboring information between points is necessary. Therefore, a nearest neighbors search scheme, considering the local complexity of the processing point, is used to determinate the neighbors for each point in a point geometry. With the constructed virtual connectivity, the secret message can be embedded successfully after the vertex decimation and data embedding processes. The experimental results show that the proposed algorithm can preserve the advantages of previous work, including higher estimation accuracy, high embedding capacity, acceptable model distortion, and robustness against similarity transformation attacks. Most importantly, this work is the first 3D steganographic algorithm for point geometry with adaptation.

Neighbors

Jiro Ninomiya name to the United States ,from Japan .at the tum of the century and bought a few acres of land just northeast,of SanFrrincisco. There,next to a palm tree,

Configurations of the Penrose Tiling beyond Nearest Neighbors

Starting from the eight vertex types in the Penrose tiling, we investigate the configurations beyond the nearest neighbors. The detailed structure of configurations and their concentrations in the whole pattern are obtained. It is found that the number of configuration types increases greatly when the observed clusters are becoming larger, which indicates that it is difficult to generate a perfect Penrose tiling according to the local matching rules.

A NEW DAY FOR OLD NEIGHBORS

The draft of the Foreign Investment Law was a hot topic of this year’s Two Sessions held in March.The newly-adopted law is an innovation in the legal system on foreign investment and serves as the basic law on foreign investment as China continues to open up in the new era.Thai enterprises were among the first foreign companies to enter China after the introduction of the reform and opening-up policy.On the sidelines of the Two Sessions,China Report ASEAN conducted an exclusive interview with Vithit Powattanasuk,Consul-General of Royal Thai Consulate-General in Chengdu.

Doubts Over Neighbors' Export Gear Up

Recently, a circular has been is- sued by the Ministry of Com merce to notify the domestictextile exporters not to be engaged in il- legal transit trade. If those practices are founded, there will be severe punishment.

An Analysis of“Outsiders”Identity in Isaac Bashevis Singer's Neighbors

Singer is a Polish — born Jewish author in Yiddish, awarded the Nobel Prize in Literature in 1978. Although Singer is exposed to the English culture of United States for more than 50 years, he always insists on the mother tongue Yiddish creation.The way in which he writes with the dying language fully expresses his"outsiders"identity in the exotic culture. This thesis aims to analyze the"outsiders"identity revealed in Neighbors from the perspective of Singer's strict adherence to Yiddish and Jews as victims of the history.

Close Neighbors Plus Relatives──An unforgettable Trip to the Philippines

At the invitation of the.Asian Center of the Philip-pine University,a five-mem-berCAFIU delegation visited the Philippines.The host high-ly regarded our visit,gave us a W arm and courteous recep-tion.Mr.Estrada.

The k Nearest Neighbors Estimator of the M-Regression in Functional Statistics

It is well known that the nonparametric estimation of the regression function is highly sensitive to the presence of even a small proportion of outliers in the data.To solve the problem of typical observations when the covariates of the nonparametric component are functional,the robust estimates for the regression parameter and regression operator are introduced.The main propose of the paper is to consider data-driven methods of selecting the number of neighbors in order to make the proposed processes fully automatic.We use thek Nearest Neighbors procedure(kNN)to construct the kernel estimator of the proposed robust model.Under some regularity conditions,we state consistency results for kNN functional estimators,which are uniform in the number of neighbors(UINN).Furthermore,a simulation study and an empirical application to a real data analysis of octane gasoline predictions are carried out to illustrate the higher predictive performances and the usefulness of the kNN approach.

Intrusion Detection Algorithm Based on Density,Cluster Centers,and Nearest Neighbors

Intrusion detection aims to detect intrusion behavior and serves as a complement to firewalls.It can detect attack types of malicious network communications and computer usage that cannot be detected by idiomatic firewalls.Many intrusion detection methods are processed through machine learning.Previous literature has shown that the performance of an intrusion detection method based on hybrid learning or integration approach is superior to that of single learning technology.However,almost no studies focus on how additional representative and concise features can be extracted to process effective intrusion detection among massive and complicated data.In this paper,a new hybrid learning method is proposed on the basis of features such as density,cluster centers,and nearest neighbors(DCNN).In this algorithm,data is represented by the local density of each sample point and the sum of distances from each sample point to cluster centers and to its nearest neighbor.k-NN classifier is adopted to classify the new feature vectors.Our experiment shows that DCNN,which combines K-means,clustering-based density,and k-NN classifier,is effective in intrusion detection.

China and US Strategic Choices and China’s Relations with Its Neighbors

Strategic competition between China and the United States has gradually intensified while the relationship between China and neighboring countries has stabilized.The implementation of an " America First"policy along with a decline in US strategic credibility is prompting China's neighbors to adopt a more cooperative stance toward China.China's positive response to those gestures and its continued strategic reassurance improve China's strategic credibility.Allaying their security concerns lays a foundation for continuous improvement of China's neighboring security environment.It is imperative for China to grasp this opportunity to resolve disputes with its neighbors to ease its rise dilemma.

China's Relations with Neighbors

China has a large number of neighboring countries, and its relations with them together with the situation of the neighborhood mean special and important interests for China. Given that, China has put its relations with neighboring countries in the first place in its foreign relations, and has put forward the basic concepts of developing relations with the neighboring countries, such as good neighborliness.

RecBERT:Semantic recommendation engine with large language model enhanced query segmentation for k-nearest neighbors ranking retrieval

The increasing amount of user traffic on Internet discussion forums has led to a huge amount of unstructured natural language data in the form of user comments.Most modern recommendation systems rely on manual tagging,relying on administrators to label the features of a class,or story,which a user comment corresponds to.Another common approach is to use pre-trained word embeddings to compare class descriptions for textual similarity,then use a distance metric such as cosine similarity or Euclidean distance to find top k neighbors.However,neither approach is able to fully utilize this user-generated unstructured natural language data,reducing the scope of these recommendation systems.This paper studies the application of domain adaptation on a transformer for the set of user comments to be indexed,and the use of simple contrastive learning for the sentence transformer fine-tuning process to generate meaningful semantic embeddings for the various user comments that apply to each class.In order to match a query containing content from multiple user comments belonging to the same class,the construction of a subquery channel for computing class-level similarity is proposed.This channel uses query segmentation of the aggregate query into subqueries,performing k-nearest neighbors(KNN)search on each individual subquery.RecBERT achieves state-of-the-art performance,outperforming other state-of-the-art models in accuracy,precision,recall,and F1 score for classifying comments between four and eight classes,respectively.RecBERT outperforms the most precise state-of-the-art model(distilRoBERTa)in precision by 6.97%for matching comments between eight classes.

Attention,neighbors:Methyl salicylate mediates plant airborne defense

Plants have evolved to generate and release a wide array of volatile organic compounds(VOCs)when challenged by environmental stimuli such as biotic and abiotic stresses,which facilitate their reproduction,defense responses,and plant-plant communication(Karban,2021).Once emitted,some VOCs can elicit defense signaling in neighboring plants by interacting with specific receptor(s),a phenomenon referred to as airborne defense(AD)(Loreto and D’Auria,2022).

Root overlap and allocation of above- and belowground growth of European beech in pure and mixed stands of Douglas fir and Norway spruce

Site conditions and species identity have a combined effect on fine root growth of trees in pure and mixed stands.However,mechanisms that may contribute to this effect are rarely studied,even though they are essential to assess the potential of species to cope with climate change.This study examined fine root overlap and the linkage between fine root and stem growth of European beech(Fagus sylvatica)growing in pure and mixed stands with Douglas fir(Pseudotsuga menziesii)or Norway spruce(Picea abies)at two different study sites in northwestern Germany.The study sites represented substantially different soil and climate conditions.At each site,three stands,and at each stand,three pairs of trees were studied.In the pure beech stand,the pairs consisted of two beech trees,while in the mixed stands each pair was composed of a beech tree and a conifer.Between each pair,three evenly spaced soil cores were taken monthly throughout the growing season.In the pure beech stands,microsatellite markers were used to assign the fine roots to individual trees.Changes in stem diameter of beech were quantified and then upscaled to aboveground wood productivity with automatic high-resolution circumference dendrometers.We found that fine root overlap between neighboring trees varied independently of the distance between the paired trees or the stand types(pure versus mixed stands),indicating that there was no territorial competition.Aboveground wood productivity(wood NPP)and fine root productivity(root NPP)showed similar unimodal seasonal patterns,peaking in June.However,this pattern was more distinct for root NPP,and root NPP started earlier and lasted longer than wood NPP.The influence of site conditions on the variation in wood and root NPP of beech was stronger than that of stand type.Wood NPP was,as expected,higher at the richer site than at the poorer site.In contrast,root NPP was higher at the poorer than at the richer site.We concluded that beech can respond to limited resources not only above-but also belowground and that the negative relationship between above-and belowground growth across the study sites suggests an‘optimal partitioning’of growth under stress.

Outsmarting Android Malware with Cutting-Edge Feature Engineering and Machine Learning Techniques

The growing usage of Android smartphones has led to a significant rise in incidents of Android malware andprivacy breaches.This escalating security concern necessitates the development of advanced technologies capableof automatically detecting andmitigatingmalicious activities in Android applications(apps).Such technologies arecrucial for safeguarding user data and maintaining the integrity of mobile devices in an increasingly digital world.Current methods employed to detect sensitive data leaks in Android apps are hampered by two major limitationsthey require substantial computational resources and are prone to a high frequency of false positives.This meansthat while attempting to identify security breaches,these methods often consume considerable processing powerand mistakenly flag benign activities as malicious,leading to inefficiencies and reduced reliability in malwaredetection.The proposed approach includes a data preprocessing step that removes duplicate samples,managesunbalanced datasets,corrects inconsistencies,and imputes missing values to ensure data accuracy.The Minimaxmethod is then used to normalize numerical data,followed by feature vector extraction using the Gain ratio andChi-squared test to identify and extract the most significant characteristics using an appropriate prediction model.This study focuses on extracting a subset of attributes best suited for the task and recommending a predictivemodel based on domain expert opinion.The proposed method is evaluated using Drebin and TUANDROMDdatasets containing 15,036 and 4,464 benign and malicious samples,respectively.The empirical result shows thatthe RandomForest(RF)and Support VectorMachine(SVC)classifiers achieved impressive accuracy rates of 98.9%and 98.8%,respectively,in detecting unknown Androidmalware.A sensitivity analysis experiment was also carriedout on all three ML-based classifiers based on MAE,MSE,R2,and sensitivity parameters,resulting in a flawlessperformance for both datasets.This approach has substantial potential for real-world applications and can serve asa valuable tool for preventing the spread of Androidmalware and enhancing mobile device security.