Loop Closure Detection via Locality Preserving Matching With Global Consensus

A critical component of visual simultaneous localization and mapping is loop closure detection(LCD),an operation judging whether a robot has come to a pre-visited area.Concretely,given a query image(i.e.,the latest view observed by the robot),it proceeds by first exploring images with similar semantic information,followed by solving the relative relationship between candidate pairs in the 3D space.In this work,a novel appearance-based LCD system is proposed.Specifically,candidate frame selection is conducted via the combination of Superfeatures and aggregated selective match kernel(ASMK).We incorporate an incremental strategy into the vanilla ASMK to make it applied in the LCD task.It is demonstrated that this setting is memory-wise efficient and can achieve remarkable performance.To dig up consistent geometry between image pairs during loop closure verification,we propose a simple yet surprisingly effective feature matching algorithm,termed locality preserving matching with global consensus(LPM-GC).The major objective of LPM-GC is to retain the local neighborhood information of true feature correspondences between candidate pairs,where a global constraint is further designed to effectively remove false correspondences in challenging sceneries,e.g.,containing numerous repetitive structures.Meanwhile,we derive a closed-form solution that enables our approach to provide reliable correspondences within only a few milliseconds.The performance of the proposed approach has been experimentally evaluated on ten publicly available and challenging datasets.Results show that our method can achieve better performance over the state-of-the-art in both feature matching and LCD tasks.We have released our code of LPM-GC at https://github.com/jiayi-ma/LPM-GC.

Locality Preserving Discriminant Projection for Speaker Verification

In this paper, a manifold subspace learning algorithm based on locality preserving discriminant projection (LPDP) is used for speaker verification. LPDP can overcome the deficiency of the total variability factor analysis and locality preserving projection (LPP). LPDP can effectively use the speaker label information of speech data. Through optimization, LPDP can maintain the inherent manifold local structure of the speech data samples of the same speaker by reducing the distance between them. At the same time, LPDP can enhance the discriminability of the embedding space by expanding the distance between the speech data samples of different speakers. The proposed method is compared with LPP and total variability factor analysis on the NIST SRE 2010 telephone-telephone core condition. The experimental results indicate that the proposed LPDP can overcome the deficiency of LPP and total variability factor analysis and can further improve the system performance.

Face recognition using illuminant locality preserving projections

A novel supervised manifold learning method was proposed to realize high accuracy face recognition under varying illuminant conditions. The proposed method, named illuminant locality preserving projections （ILPP）, exploited illuminant directions to alleviate the effect of illumination variations on face recognition. The face images were first projected into low dimensional subspace, Then the ILPP translated the face images along specific direction to reduce lighting variations in the face. The ILPP reduced the distance between face images of the same class, while increase the dis tance between face images of different classes. This proposed method was derived from the locality preserving projections （LPP） methods, and was designed to handle face images with various illumi nations. It preserved the face image＇ s local structure in low dimensional subspace. The ILPP meth od was compared with LPP and discriminant locality preserving projections （DLPP）, based on the YaleB face database. Experimental results showed the effectiveness of the proposed algorithm on the face recognition with various illuminations.

A supervised multimanifold method with locality preserving for face recognition using single sample per person

Although real-world experiences show that preparing one image per person is more convenient, most of the appearance-based face recognition methods degrade or fail to work if there is only a single sample per person(SSPP). In this work, we introduce a novel supervised learning method called supervised locality preserving multimanifold(SLPMM) for face recognition with SSPP. In SLPMM, two graphs: within-manifold graph and between-manifold graph are made to represent the information inside every manifold and the information among different manifolds, respectively. SLPMM simultaneously maximizes the between-manifold scatter and minimizes the within-manifold scatter which leads to discriminant space by adopting locality preserving projection(LPP) concept. Experimental results on two widely used face databases FERET and AR face database are presented to prove the efficacy of the proposed approach.

An Efficient Grid Service Discovery Mechanism Based on the Locality Principle

With the explosion of services in grid environment, it＇s necessary to develop a mechanism which has the ability of discovering suitable grid services efficiently. This paper attempts to establish a layered resource management model based on the locality principle which classifies services into different domains and virtual organizations （VOs） according to their shared purposes. We propose an ontologybased search method applying the ontology theory for characterizing semantic information. In addition, we extend the UD- D1 in querying, storing, and so on. Simulation experiments have shown that our mechanism achieves higher performance in precision, recall and query response time.

Fault Diagnosis Model Based on Feature Compression with Orthogonal Locality Preserving Projection

Based on feature compression with orthogonal locality preserving projection（OLPP）,a novel fault diagnosis model is proposed in this paper to achieve automation and high-precision of fault diagnosis of rotating machinery.With this model,the original vibration signals of training and test samples are first decomposed through the empirical mode decomposition（EMD）,and Shannon entropy is constructed to achieve high-dimensional eigenvectors.In order to replace the traditional feature extraction way which does the selection manually,OLPP is introduced to automatically compress the high-dimensional eigenvectors of training and test samples into the low-dimensional eigenvectors which have better discrimination.After that,the low-dimensional eigenvectors of training samples are input into Morlet wavelet support vector machine（MWSVM） and a trained MWSVM is obtained.Finally,the low-dimensional eigenvectors of test samples are input into the trained MWSVM to carry out fault diagnosis.To evaluate our proposed model,the experiment of fault diagnosis of deep groove ball bearings is made,and the experiment results indicate that the recognition accuracy rate of the proposed diagnosis model for outer race crack、inner race crack and ball crack is more than 90%.Compared to the existing approaches,the proposed diagnosis model combines the strengths of EMD in fault feature extraction,OLPP in feature compression and MWSVM in pattern recognition,and realizes the automation and high-precision of fault diagnosis.

Regional difference and dynamic mechanism of locality of the Chinese farming-pastoral ecotone based on geotagged photos from Panoramio

Cross-regional locality research reflects the influences of natural environment and the human activities due to the abundant land types and the multiple landscape combinations in related regions. The Chinese farming-pastoral ecotone is a typical large-scale region but few studies were conducted. This research contributed to the understanding of cross-regional locality of the Chinese farming-pastoral ecotone from different scales, including national, sectional, and provincial administrative units by utilizing geotagged photos（GTPs） obtained from the Panoramio website. The major results were as follows：（1） the locality elements of the Chinese farming-pastoral ecotone included 52 free nodes classified into 8 types of scene attributes;（2） there were huge differences between locality elements of different regions, and there was a negative correlation between the similarity degree of elements of different provinces and their spatial distances;（3） the Chinese farming-pastoral ecotone could be divided into the northern, central and southern sections, whose localities had differences in element constitution, association structure and the strength of elements, system stability and the anti-interference capability; and（4） the evolution of the localities of the northern and central sections was mainly influenced by human activities, while the locality of southern section retained more natural features. On a theoretical level, this research aimed to establish the research methodology of locality from the perspective of open data on the web with strong operability and replicability. On a practical level, this research could enrich the structuring recognition of the locality of the Chinese farming-pastoral ecotone and the comprehension of its dynamic mechanism. The results provide a reference for locality differentiation protection and the development of a cross-regional scale.

Performance Study of Locality and Its Impact on Peer-to-Peer Systems

This paper presents the measurement study of locality-aware Peer-to-Peer solutions on Internet Autonomous System (AS) topology by reducing AS hop count and increase nearby source nodes in P2P applications. We evaluate the performance of topology-aware BT system called TopBT with BitTorrent (BT) by constructing AS graph and measure the hops between nodes to observe the impact of quality of service in P2P applications.

Comprehensiveness and Locality: Website Marketing of World City Governments in the Era of Globalisation

In the era of the Internet and globalisation, more and more international academics focus their attention on how city governments compete for talent, capital, and technology through website marketing to promote their economy and global status. However, 1) present research generally overlooks the importance of different types of elements in different marketing themes, 2) the combinations of marketing themes are still unknown, and 3) the presumption that the emphasised elements and specific combination of marketing themes on official websites differentiates cities requires more cases to be understood. In light of this background, this study collects homepage elements of 49 Alpha world cities' official websites and quantitatively analyses the frequency of different types of elements, the marketing content themes, and the dissimilarity of content of Chinese Alpha world cities. The results indicate that comprehensiveness and locality appear in the process of city marketing throughout official city websites. Overall, we make the following conclusions. 1) The importance of different kinds of elements significantly differs between 49 Alpha world cities. 2) Based on various combinations of elements, the marketing contents of Alpha world cities through official websites can be categorised into six themes of history and culture, government and information, construction and environment, government and living, construction and living, and general compound. 3) The marketing elements of five Chinese Alpha world cities, including Hong Kong, Beijing, Shanghai, Taipei and Guangzhou, are different than the other 44 Alpha world cities, and Chinese cities prefer to advertise their history and culture but rarely market citizens' activities. Moreover, Chinese cities' marketing mostly targets natives while the other 44 Alpha cities target external groups, and the locality of world cities' website marketing is reinforced especially on a native language edition website. This study ultimately finds that the Chinese edition websites of five Chinese cities place more focus on introducing local historical buildings, administrative services, and internal business information than the English edition websites do.

Early Jurassic Coleopterans from the Mintaja Insect Locality,Western Australia

Beetles （Coleoptera） are the most common insects recovered from the Lower Jurassic Mintaja insect locality of Western Australia, with over half of the fossils recorded from this site being isolated coleopteran elytra. A range of partial beetle bodies and other isolated beetle sclerites have also been recovered from the locality; much of this material is taxonomically unidenitifiable due to its disarticulation and poor preservation. A number of the Mintaja coleopterans are assigned to the archostematan family Ommatidae, including Zygadenia westraliensis （Riek, 1968） comb. nov, previously placed in the morphogenus Mesothoris, and an unnamed species of Tetraphalerus. Also recorded is a new species of elaterid, Lithomerus wunda sp. nov., along with other fragments likely attributable to the same family. The remaining material is assigned into morphospecies, separated primarily on preserved body parts - specifically, there are three morphospecies based on partially articulated coleopteran bodies, two morphospecies based on isolated head capsules, three morphospecies based on isolated thoracic sclerites, three morphospecies based on isolated abdominal sclerites, and 13 morphospecies based on isolated elytra. Overall, the ecology of these fossils is difficult to interpret due to poor preservation, although some of the beetles were likely aquatic, and the Ommatidae and Elateridae were both likely xylophilous. There is a strong similarity between the Mintaja coleopterans and those from the Late Triassic Denmark Hill locality of Queensland, though many of these similarities are based on morphotaxa and may be superficial in nature. Of the species that have been assigned to named taxa, all are generally typical of the Late Mesozoic worldwide, with Zygadenia, Tetraphalerus and Lithomerus all long-ranging, cosmopolitan genera.

Importance of genetic data from type specimens:The questionable type locality of southern white-cheeked gibbon,Nomascus siki(Delacour,1951)

DEAR EDITOR,Many historical descriptions of new species have included vague or inaccurate information about the type locality.This can lead to confusion in the study of the species and their geographic distributions,thereby hindering conservation efforts.One such example is the southern white-cheeked gibbon(Nomascus siki(Delacour,1951)).The type locality is given as Thua Luu in central Vietnam,which is located within the range of another crested gibbon species(N.annamensis)and more than 200 km south of the known range of N.siki.To investigate the problematic type locality of N.siki,we sequenced the mitochondrial genome of the holotype and compared its cytochrome b gene sequence to those of other georeferenced crested gibbon samples.

Factors Influencing Hepatitis C Viral Infections in the Population of Algamosi Locality, Gezira State, Central Sudan

Hepatitis C (HCV) remains a global health challenge and is transmitted via contact with contaminated blood and body fluids. This study aimed To find the factors influencing hepatitis c viral infections and to identify its prevalence among populations of the Algamosi area, Gezira state central Sudan. This cross-sectional community-based study was conducted. A total of 492 participants were randomly selected from among 4 villages and were interviewed to find out the factors that lead to transmission of infection and tested for markers of hepatitis C infection. ELISA confirmed all the positive card tests. The results showed that the individuals within the age groups > 45 and 31 - 45 years are more affected by HCV the percentage was 3.37% and 0.6% respectively, while the age groups of 15 - 30 and p < 0.05). Among the possible cause (1.4%) had a previous history of tattooing and were significantly reactive for anti-HCV (X2 = 14.588 and p value = 0.001) The study concluded that the prevalence of hepatitis C viruses was only detected in three areas. This study explored many possible causes associated with viral hepatitis, tattooing is the common cause of hepatitis C virus. Based on the finding the study recommends, the crucial intervention program to screen most of the Algamosi population who have been not screened for HCV, proper treatment for HCV, and the health education program is strongly recommended to create awareness among the general population.

An Online Malicious Spam Email Detection System Using Resource Allocating Network with Locality Sensitive Hashing

In this paper, we propose a new online system that can quickly detect malicious spam emails and adapt to the changes in the email contents and the Uniform Resource Locator (URL) links leading to malicious websites by updating the system daily. We introduce an autonomous function for a server to generate training examples, in which double-bounce emails are automatically collected and their class labels are given by a crawler-type software to analyze the website maliciousness called SPIKE. In general, since spammers use botnets to spread numerous malicious emails within a short time, such distributed spam emails often have the same or similar contents. Therefore, it is not necessary for all spam emails to be learned. To adapt to new malicious campaigns quickly, only new types of spam emails should be selected for learning and this can be realized by introducing an active learning scheme into a classifier model. For this purpose, we adopt Resource Allocating Network with Locality Sensitive Hashing (RAN-LSH) as a classifier model with a data selection function. In RAN-LSH, the same or similar spam emails that have already been learned are quickly searched for a hash table in Locally Sensitive Hashing (LSH), in which the matched similar emails located in “well-learned” are discarded without being used as training data. To analyze email contents, we adopt the Bag of Words (BoW) approach and generate feature vectors whose attributes are transformed based on the normalized term frequency-inverse document frequency (TF-IDF). We use a data set of double-bounce spam emails collected at National Institute of Information and Communications Technology (NICT) in Japan from March 1st, 2013 until May 10th, 2013 to evaluate the performance of the proposed system. The results confirm that the proposed spam email detection system has capability of detecting with high detection rate.

A Comparative Study of Locality Preserving Projection and Principle Component Analysis on Classification Performance Using Logistic Regression

There are a variety of classification techniques such as neural network, decision tree, support vector machine and logistic regression. The problem of dimensionality is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity, however, we need to use dimensionality reduction methods. These methods include principal component analysis (PCA) and locality preserving projection (LPP). In many real-world classification problems, the local structure is more important than the global structure and dimensionality reduction techniques ignore the local structure and preserve the global structure. The objectives is to compare PCA and LPP in terms of accuracy, to develop appropriate representations of complex data by reducing the dimensions of the data and to explain the importance of using LPP with logistic regression. The results of this paper find that the proposed LPP approach provides a better representation and high accuracy than the PCA approach.

On the notions of normality, locality, and operational stability in ADRC

Treating plant dynamics as an ideal integrator chain disturbed by the total disturbance is the hallmark of active disturbance rejection control(ADRC).To interpret its effectiveness and success,to explain why so many vastly different dynamic systems can be treated in this manner,and to answer why a detailed,accurate,and global mathematical model is unnecessary,is the target of this paper.Driven by a motivating example,the notions of normality and locality are introduced.Normality shows that,in ADRC,the plant is normalized to an integrator chain,which is called local nominal model and locally describes the plant’s frequency response in the neighborhood of the expected gain crossover frequency.Locality interprets why ADRC can design the controller only with the local information of the plant.With normality and locality,ADRC can be effective and robust,and obtain operational stability discussed by T.S.Tsien.Then viewing proportional-integral-derivative(PID)control as a low-frequency approximation of second-order linear ADRC,the above results are extended to PID control.A controller design framework is proposed to obtain the controller in three steps:(1)choose an integrator chain as the local nominal model of the plant;(2)select a controller family corresponding to the local nominal model;and(3)tune the controller to guarantee the gain crossover frequency specification.The second-order linear ADRC and the PID control are two special cases of the framework.

How Locality Generates Modernity: Reflections on Qiao Ye's Baoshui Village

Novel writings in China in 2023 display a tendency toward locality which exhibits two characteristics:One is the“sense of hometown,”and the other is the“integration of locality with modernity.”Qiao Ye's novel Baoshui Village is a representative work that achieves“modernity”through“locality”How contemporary novels portray the changing countryside,and how they handle and grasp the relationship and proportion between change and constancy;how to find the right way to integrate the geographical,ethnic,and modern aspects of a novel;how locality generates modernity;and how modernity can accommodate and activate locality are not only theoretical questions that need to be deeply explored but also issues of writing that need continuous exploration in practice.In this sense,Baoshui Village is worth cherishing.

A Study on the Transmission Dynamics of the Omicron Variant of COVID-19 Using Nonlinear Mathematical Models

This research examines the transmission dynamics of the Omicron variant of COVID-19 using SEIQIcRVW and SQIRV models,considering the delay in converting susceptible individuals into infected ones.The significant delays eventually resulted in the pandemic’s containment.To ensure the safety of the host population,this concept integrates quarantine and the COVID-19 vaccine.We investigate the stability of the proposed models.The fundamental reproduction number influences stability conditions.According to our findings,asymptomatic cases considerably impact the prevalence of Omicron infection in the community.The real data of the Omicron variant from Chennai,Tamil Nadu,India,is used to validate the outputs.

Multi-Material Topology Optimization for Spatial-Varying Porous Structures

This paper aims to propose a topology optimization method on generating porous structures comprising multiple materials.The mathematical optimization formulation is established under the constraints of individual volume fraction of constituent phase or total mass,as well as the local volume fraction of all phases.The original optimization problem with numerous constraints is converted into a box-constrained optimization problem by incorporating all constraints to the augmented Lagrangian function,avoiding the parameter dependence in the conventional aggregation process.Furthermore,the local volume percentage can be precisely satisfied.The effects including the globalmass bound,the influence radius and local volume percentage on final designs are exploited through numerical examples.The numerical results also reveal that porous structures keep a balance between the bulk design and periodic design in terms of the resulting compliance.All results,including those for irregular structures andmultiple volume fraction constraints,demonstrate that the proposedmethod can provide an efficient solution for multiple material infill structures.

Construction of a Computational Scheme for the Fuzzy HIV/AIDS Epidemic Model with a Nonlinear Saturated Incidence Rate

This work aimed to construct an epidemic model with fuzzy parameters.Since the classical epidemic model doesnot elaborate on the successful interaction of susceptible and infective people,the constructed fuzzy epidemicmodel discusses the more detailed versions of the interactions between infective and susceptible people.Thenext-generation matrix approach is employed to find the reproduction number of a deterministic model.Thesensitivity analysis and local stability analysis of the systemare also provided.For solving the fuzzy epidemic model,a numerical scheme is constructed which consists of three time levels.The numerical scheme has an advantage overthe existing forward Euler scheme for determining the conditions of getting the positive solution.The establishedscheme also has an advantage over existing non-standard finite difference methods in terms of order of accuracy.The stability of the scheme for the considered fuzzy model is also provided.From the plotted results,it can beobserved that susceptible people decay by rising interaction parameters.