ML and DL-based Phishing Website Detection:The Effects of Varied Size Datasets and Informative Feature Selection Techniques

Onemust interact with a specific webpage or website in order to use the Internet for communication,teamwork,and other productive activities.However,because phishing websites look benign and not all website visitors have the same knowledge and skills to inspect the trustworthiness of visited websites,they are tricked into disclosing sensitive information and making them vulnerable to malicious software attacks like ransomware.It is impossible to stop attackers fromcreating phishingwebsites,which is one of the core challenges in combating them.However,this threat can be alleviated by detecting a specific website as phishing and alerting online users to take the necessary precautions before handing over sensitive information.In this study,five machine learning(ML)and DL algorithms—cat-boost(CATB),gradient boost(GB),random forest(RF),multilayer perceptron(MLP),and deep neural network(DNN)—were tested with three different reputable datasets and two useful feature selection techniques,to assess the scalability and consistency of each classifier’s performance on varied dataset sizes.The experimental findings reveal that the CATB classifier achieved the best accuracy across all datasets(DS-1,DS-2,and DS-3)with respective values of 97.9%,95.73%,and 98.83%.The GB classifier achieved the second-best accuracy across all datasets(DS-1,DS-2,and DS-3)with respective values of 97.16%,95.18%,and 98.58%.MLP achieved the best computational time across all datasets(DS-1,DS-2,and DS-3)with respective values of 2,7,and 3 seconds despite scoring the lowest accuracy across all datasets.

Public Speaking的技巧与策略(8)——如何进行Informative Presentation

演讲和面对面谈话非常相似。如果我们想教授某一种技能,如演示性演讲,我们必须首先让听众知道我们想让他们了解什么,做什么。如果是劝说式演讲或辩论,我们必须在劝服听众相信我们的观点前使他们了解所要讨论的题目。这种告知听众的做法要求我们清晰简洁地提出我们的主题,然后用具体的细节、例证来支持主题或在辩论中提出具体明确的参考材料。

Old nest material functions as an informative cue in making nest-site selection decisions in the European Kestrel(Falco tinnunculus)

Background:For secondary cavity-nesting bird species that do not add lining materials to nests,the presence of old nest material or organic remains that have accumulated within nest cavities from previous breeding events may be a cue of nest-site quality.These materials potentially contain information about past breeding success in con-and heterospecifics and may improve the thermal insulation of eggs during incubation.However,few studies have addressed whether the presence of old nest materials serves as a cue for cavity-nesting raptors when choosing specific nest sites.Methods:We conducted a 9-year nest box experiment to test whether old nest materials from con-and heterospecifics serve as informative cues to the European Kestrel(Falco tinnunculus)when making nest selection decisions,as this species uses nest boxes without adding nesting material.Results:The presence of old nest materials and entrance size best discriminated nest boxes occupied by European Kestrels from unoccupied boxes.Nest boxes containing conspecific organic remains,artificial dry leaf and branch material,and material left behind by Great Tits(Parus major)were reused at higher rates,especially those containing conspecific nest material,than nest boxes containing true or simulated nest materials from predators.In 2010,no single nest box was occupied by the same banded individual that occupied the box in the previous year(10 females and 2 males were banded in 2009).Conclusions:European Kestrels preferred nest boxes containing old nest material over empty boxes,which is consistent with previous findings that they exploit con-and heterospecific cues when deciding where to settle and breed,as old nest or organic material provides substrate for incubating females.Kestrels may be able to assess the predation risks associated with a specific nest site based on experience or the presence of prey remains.The repeated use of nest boxes across breeding seasons by kestrels cannot be entirely ascribed to philopatry.This study provides evidence that old nest materials are potentially used as informative cues when making nest-site selection decisions in European Kestrels.

The Fourier Notation of the Geomagnetic Signals Informative Parameters

The paper discusses the quantitative definition of the s/n (signal to noise ratio) by means of new computational parameters derived (and computed) by the Fourier analysis. The theme is of great relevance when the geomagnetic observed field has high transient noise and high energy content (i.e.geomagnetic signal interfered by human activity magnetic band) and when the signal analysis action is oriented to the detection of magnetic sources characterized by quasi-punctiform size, low energy level and kinetic mechanical status (i.e.uw armed terrorist). The paper shows the results obtained introducing two new informative spectral parameters: the informative capability “C” and the enhanced informative capability “eC”. These parameters are depending on the comparison of the energy of the target signal with total field energy and they are characteristics of each elementary signal. C classifies the energy of the spectrum in two metrological bands: elementary signal informative energy EI (band or single signal) and passive energy EP. This metrological classification of the energy overtakes the concept of noise: each signal is part of the noise band when it is not under observation and becomes out of the band when it is under observation (numerical observation→computation). C (and eC) allows to compute the value of the “visibility” of the informative signals in a high energy geomagnetic field (or spectrum). C is a fundamental parameter for the evaluation of the effectiveness of singularity magnetic metrology in the passive detection of small magnetic sources in high noised magnetic field.

Informative Property of the Data Set in a Single-input Single-output (SISO) Closed-loop System with a Switching Controller

Closed-loop identification is important and necessary to various model-based advanced process control strategies, whose performance depends greatly on the informative property of the data set. Switching control is an important method in process control. Therefore, this paper studies the informative property of a data set in a single-input single-output (SISO) closed-loop system with a switching controller. It is proved that this data set is informative if the controller switches among at least two modes (i.e., feedback laws). Our result does not require any assumption on the way of switch and removes the constraints on the switching manner required in some classical literature. Finally, simulation case studies based on a continuous stirred-tank reactor (CSTR) process are given to validate the results.

Using Informative Score for Instance Selection Strategy in Semi-Supervised Sentiment Classification

Sentiment classification is a useful tool to classify reviews about sentiments and attitudes towards a product or service.Existing studies heavily rely on sentiment classification methods that require fully annotated inputs.However,there is limited labelled text available,making the acquirement process of the fully annotated input costly and labour-intensive.Lately,semi-supervised methods emerge as they require only partially labelled input but perform comparably to supervised methods.Nevertheless,some works reported that the performance of the semi-supervised model degraded after adding unlabelled instances into training.Literature also shows that not all unlabelled instances are equally useful;thus identifying the informative unlabelled instances is beneficial in training a semi-supervised model.To achieve this,an informative score is proposed and incorporated into semisupervised sentiment classification.The evaluation is performed on a semisupervised method without an informative score and with an informative score.By using the informative score in the instance selection strategy to identify informative unlabelled instances,semi-supervised models perform better compared to models that do not incorporate informative scores into their training.Although the performance of semi-supervised models incorporated with an informative score is not able to surpass the supervised models,the results are still found promising as the differences in performance are subtle with a small difference of 2%to 5%,but the number of labelled instances used is greatly reduced from100%to 40%.The best finding of the proposed instance selection strategy is achieved when incorporating an informative score with a baseline confidence score at a 0.5:0.5 ratio using only 40%labelled data.

Semiparametric Estimator of Mean Conditional Residual Life Function under Informative Random Censoring from Both Sides

In this paper we study estimator of mean residual life function in fixed design regression model when life times are subjected to informative random censoring from both sides. We prove an asymptotic normality of estimators.

Quality Requirements for Multimedia Interactive Informative Systems

Multimedia Interactive Informative Systems (MIIS) are software applications resulting from the convergence of multiples technologies such as audiovisual, computing and communication. They aim to transmit information to a large, diverse and dispersed public. As with other mass media, the fulfillment of MIIS goals depends largely on the quality of communication between the system and end users. Therefore, those systems should be developed in order to ensure that this quality requirement is satisfied. If MIIS are constructed according to usual software engineering practices, the analysis discipline of the development process includes requirements identification and specification;however, these techniques are focused on functional requirements, and they do not give much importance to non-functional requirements. In this paper, we propose a development process based on the production of videogames which has two different phases: preproduction and production. The first phase, corresponding to requirements identification, derives into the concept of system. In order to translate this concept into a specification, we propose the use of new communicational attributes and a MIIS metamodel. The establishment of MIIS non-functional specification is the result of analyzing class diagrams through quality attributes. In order to evaluate if the specifications are responding to communicational attributes, a functional prototype is built and evaluated with end users. The proposed methodology is applied to a real case study.

On the Informative Function of Language in the Poems and Couplets in Benzhu Temples in Dali,Yunnan

In Dali Bai Autonomous Prefecture,Yunnan Province,there exists a quite special and interesting cultural phenomenon of the Bai ethnic group,which is the belief in Benzhu.There are a lot of poems and couplets in Benzhu temples.The poems are carved on the walls and tablets.The couplets,being on both sides of the doors,are carved on planks or written on red paper.Lan guage used in the poems and couplets plays the informative function.

Intertextile Beijing Features More Informative programme of seminars and trend forums add value to fair

Intertextile Beijing Apparel Fabrics,will be held from 29-31 March 2009 at the China International Exhibition Centre,will showcase the latest textiles from around the world on 48,000 sqm of exhibition space.The event has confirmed 1100 exhibitors from 14 countries and regions including

Weighted-averaging-based classification of laser-induced breakdown spectroscopy measurements using most informative spectral lines

In this study,efficient spectral line selection and wcightcd-avcraging-bascd processing schemes are proposed for the classification of laser-induced breakdown spectroscopy(UBS)measurements.For fast on-line classification,a set of representative spectral lines arc selected ami processed relying on the information metric,instead of the time consuming full spectrum based analysis.I he most informative spectral line sets arc investigated by the joint mutual information estimation(MIR)evaluated with the Gaussian kernel density,where dominant intensity peaks associated with the concentrated components arc not necessarily most valuable for classification.In order to further distinguish the characteristic patterns of die LIBS measured spectrum,two-dimensional spectral images are synthesized through column-wise concatenation of the peaks along with their neighbors.For fast classification while preserv ing die effect of distinctive peak patterns,column-wise Gaussian weighted averaging is applied to die synthesized images,yielding a favorable trade off between classification performance and computational complexity.To explore the applicability of the proposed schemes,two applications of alloy classification and skin cancer detection arc investigated with the multi-class and binary support vector machines classifiers,respectively.Ihc MIE measures associated with selected spectral lines in bodi applications show a strong correlation to the actual classification or detection accuracy,which enables to find out meaningful combinations of spectral lines.In addition,the peak patterns of the selected lines and their Gaussian weighted averaging with nciehbors of the selected peaks efficiently distineuish different classes of LIBS measured spectrum.

Research of Impact of Geografical Latitute and Residual Ionospheric Noises on Informativeness of Measuring of Zenith Wet Delay of GPS Signals

It is noted that necessity of further increase of accuracy of GPS positioning systems requires de-velopment of more perfect methods to compensate information losses occurred due to residual ionospheric delay by using optimization procedures. According to the conditions of formulated optimization task, the signal/noise ratio in measurements of zenith wet delay depends on the second order ionospheric errors, geographic latitude and day of year. At the same time if we assume that the number of measurements at the fixed geographic site is proportional to geographic latitude and if we accept existence of only two antiphase scenarios for variation of residual ionospheric delay on latitude normed by their specific constant, there should be optimum functional dependence of precipitated water on latitude upon which the quantity of measuring information reaches the maximum. The mathematical grounding of solution of formulated optimization task is given.

Employee Stock Ownership Plans and Stock-price Informativeness

This study examines the impact of employee stock ownership plans(ESOPs)on stock-price informativeness in Chinese stock markets.Its findings indicate that firms implementing ESOPs experienced an average 11.89 percent increase in stock-price informativeness.The plans improved stock-price informativeness through increased external attention and supervision.An event study shows that ESOPs gave rise to an announcement effect,driven by anticipated performance improvements and the novelty associated with ESOPs.A mechanism analysis demonstrates that the implementation of ESOPs attracted market attention,and the increased market supervision resulting from this mitigated the moral hazards of management associated with ESOPs.Plans with more positive signals exerted a greater influence.Notably,ESOPs that prioritized management incentives gained more recognition in the market.As the incentive effects of ESOPs were weaker than those of equity incentive plans and the ESOPs lost novelty over time,the annual announcement effect diminished gradually.These findings underscore the necessity of strengthening ESOP incentives for continued optimization of priceefficiency.

Analysis of Panel Count Data with Time-dependent Covariates and Informative Observation Process

Panel count data occur in many clinical and observational studies and in some situations the observation process is informative. In this article, we propose a new joint model for the analysis of panel count data with time-dependent covariates and possibly in the presence of informative observation process via two latent variables. For the inference on the proposed model, a class of estimating equations is developed and the resulting estimators are shown to be consistent and asymptotically normal. In addition, a lack-of-fit test is provided for assessing the adequacy of the model. The finite-sample behavior of the proposed methods is examined through Monte Carlo simulation studies which suggest that the proposed approach works well for practical situations. Also an illustrative example is provided.

A DSRPCL-SVM Approach to Informative Gene Analysis

Microarray data based tumor diagnosis is a very interesting topic in bioinformatics. One of the key problems is the discovery and analysis of informative genes of a tumor. Although there are many elaborate approaches to this problem, it is still difficult to select a reasonable set of informative genes for tumor diagnosis only with microarray data. In this paper, we classify the genes expressed through microarray data into a number of clusters via the distance sensitive rival penalized competitive learning （DSRPCL） algorithm and then detect the informative gene cluster or set with the help of support vector machine （SVM）. Moreover, the critical or powerful informative genes can be found through further classifications and detections on the obtained informative gene clusters. It is well demonstrated by experiments on the colon, leukemia, and breast cancer datasets that our proposed DSRPCL-SVM approach leads to a reasonable selection of informative genes for tumor diagnosis.

High-throughput development of genome-wide locus-specific informative SSR markers in wheat

Dear Editor,Although simple sequence repeat（SSR）markers are not new,they are still useful and often used markers in molecular mapping and marker-assisted breeding,particularly in developing countries.However,locus-specific SSR markers could be more useful and informative in wheat breeding and genetic studies.In the present study,221,911 locus-specific SSR markers were designed.Verification of polymorphisms showed that the proportion of polymorphic markers increases with an increase in SSR size.

Ultrasound-guided prostate percutaneous intervention robot system and calibration by informative particle swarm optimization

Applying a robot system in ultrasound-guided percutaneous intervention is an effective approach for prostate cancer diagnosis and treatment.The limited space for robot manipulation restricts structure volume and motion.In this paper,an 8-degree-of-freedom robot system is proposed for ultrasound probe manipulation,needle positioning,and needle insertion.A novel parallel structure is employed in the robot system for space saving,structural rigidity,and collision avoidance.The particle swarm optimization method based on informative value is proposed for kinematic parameter identification to calibrate the parallel structure accurately.The method identifies parameters in the modified kinematic model stepwise according to parameter discernibility.Verification experiments prove that the robot system can realize motions needed in targeting.By applying the calibration method,a reasonable,reliable forward kinematic model is built,and the average errors can be limited to 0.963 and 1.846 mm for insertion point and target point,respectively.

Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models

This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and AB-RBFN.Additionally,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and validation.The models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to roads.These factors were instrumental in predicting the output variable,which was the probability of landslide occurrence.Statistical analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other models.The AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of 0.926.These results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.

Structural Modal Parameter Recognition and Related Damage Identification Methods under Environmental Excitations: A Review

Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.

“The Insider’s Guide to Beijing rates as one of the best,new,imaginative and informative guidebooks in a long time”—South China Morning Post

Immersion Guides,Beijing’s leading English-language publisher of guidebooks for Beijing and beyond,is proud to present the 2008 edition of the Insider’s Guide to Beijing (November 2007,ISBN: 978-7-5085-1172-6,90 yuan).This is not the run-of-the-mill guide- book written by travelers who spend a few harried days getting to know their destination.Combining the knowledge of 40 long-term residents, this is the guidebook that knows Beijing inside and out.Now in its fourth edition,this'Beijing Bible'(Beijing Today) is the most compre- hensive resource available for both travelers and residents. Fully updated annually to keep pace with the rate of change in Beijing,the Insider’s Guide provides readers with practical informa-