Vehicle Interaction Behavior Prediction with Self-Attention

The structured road is a scene with high interaction between vehicles, but due to the high uncertainty of behavior, the prediction of vehicle interaction behavior is still a challenge. This prediction is significant for controlling the ego-vehicle. We propose an interaction behavior prediction model based on vehicle cluster (VC) by self-attention (VC-Attention) to improve the prediction performance. Firstly, a five-vehicle based cluster structure is designed to extract the interactive features between ego-vehicle and target vehicle, such as Deceleration Rate to Avoid a Crash (DRAC) and the lane gap. In addition, the proposed model utilizes the sliding window algorithm to extract VC behavior information. Then the temporal characteristics of the three interactive features mentioned above will be caught by two layers of self-attention encoder with six heads respectively. Finally, target vehicle’s future behavior will be predicted by a sub-network consists of a fully connected layer and SoftMax module. The experimental results show that this method has achieved accuracy, precision, recall, and F1 score of more than 92% and time to event of 2.9 s on a Next Generation Simulation (NGSIM) dataset. It accurately predicts the interactive behaviors in class-imbalance prediction and adapts to various driving scenarios.

The COVID-19 Pandemic and Intergenerational Support: Results Based on the Health and Retirement Study COVID-19 Module

This study examined relationships between COVID-19 exposure and intergenerational support patterns. The data was from the 2020 Health and Retirement Study (HRS) COVID-19 Module (N=3266). The latent class analysis (LCA) was used to identify the types of intergenerational support based on respondents’ reports on whether they provided and received financial and instrumental support from either coresident children or non-coresident children. Two classes were identified, namely, the high interaction group and the low interaction group. Logistic regression showed that respondents who had COVID-19 and had increased spending as a result of COVID-19 were more likely to be in the high interaction group. Other types of COVID-19 exposure, i.e., knowing someone being diagnosed or knowing someone who died from COVID-19 were not significant.

Integration of MatLab and R with high-level languages using C# and Microsoft Visual Studio as an example

The paper discusses the technology of integration (providing a single interface of interaction) of different software systems working in a single environment. The levels of integration are indicated, the composition of subtasks (subsystems), which can be solved efficiently using various computing environments, are highlighted. The expediency of joint use of MatLab and R systems with high-level programming languages C ++ and C # is shown due to the limited or lack of tools for creating a convenient graphical user interface for mathematical systems, as well as the weak adaptability of programming languages for mathematical or statistical data processing and solving modeling problems. The aim of the article is to justify the most appropriate technology for integrating MatLab and R with highlevel programming languages to ensure high interaction efficiency and a user-friendly interface for complex mathematical or statistical data processing problems. The analysis of the possibilities and ways of solving the organization of interaction of MatLab and R systems with high-level languages carried out on the example of C # and the Microsoft Visual Studio environment. The possibilities of interaction of the R system and the MatLab system with highlevel programming languages, respectively, are considered. An example of software implementation of the integration of R and MatLab with a C# application is given. The capabilities of the developed program as a whole and the functionality of each of the subsystems used (R, MatLab and applications in C #) are indicated. The most preferable variant of integration of the considered systems - with the use of .NetFramework platform - is singled out. The advantages of using the Common Language Runtime for the implementation of the considered option of integrating R, MatLab and C # applications are noted.

Cost-effective Detection of Drive-by-Download Attacks with Hybrid Client Honeypots

<p>With the increasing connectivity of and reliance on computers and networks, important aspects of computer systems are under a constant threat. In particular, drive-by-download attacks have emerged as a new threat to the integrity of computer systems. Drive-by-download attacks are clientside attacks that originate fromweb servers that are visited byweb browsers. As a vulnerable web browser retrieves a malicious web page, the malicious web server can push malware to a user's machine that can be executed without their notice or consent. The detection of malicious web pages that exist on the Internet is prohibitively expensive. It is estimated that approximately 150 million malicious web pages that launch drive-by-download attacks exist today. Socalled high-interaction client honeypots are devices that are able to detect these malicious web pages, but they are slow and known to miss attacks. Detection ofmaliciousweb pages in these quantitieswith client honeypots would cost millions of US dollars. Therefore, we have designed a more scalable system called a hybrid client honeypot. It consists of lightweight client honeypots, the so-called low-interaction client honeypots, and traditional high-interaction client honeypots. The lightweight low-interaction client honeypots inspect web pages at high speed and forward only likely malicious web pages to the high-interaction client honeypot for a final classification. For the comparison of client honeypots and evaluation of the hybrid client honeypot system, we have chosen a cost-based evaluation method: the true positive cost curve (TPCC). It allows us to evaluate client honeypots against their primary purpose of identification of malicious web pages. We show that costs of identifying malicious web pages with the developed hybrid client honeypot systems are reduced by a factor of nine compared to traditional high-interaction client honeypots. The five main contributions of our work are: High-Interaction Client Honeypot The first main contribution of our work is the design and implementation of a high-interaction client honeypot Capture-HPC. It is an open-source, publicly available client honeypot research platform, which allows researchers and security professionals to conduct research on malicious web pages and client honeypots. Based on our client honeypot implementation and analysis of existing client honeypots, we developed a component model of client honeypots. This model allows researchers to agree on the object of study, allows for focus of specific areas within the object of study, and provides a framework for communication of research around client honeypots. True Positive Cost Curve As mentioned above, we have chosen a cost-based evaluationmethod to compare and evaluate client honeypots against their primary purpose of identification ofmaliciousweb pages: the true positive cost curve. It takes into account the unique characteristics of client honeypots, speed, detection accuracy, and resource cost and provides a simple, cost-based mechanism to evaluate and compare client honeypots in an operating environment. As such, the TPCC provides a foundation for improving client honeypot technology. The TPCC is the second main contribution of our work. Mitigation of Risks to the Experimental Design with HAZOP - Mitigation of risks to internal and external validity on the experimental design using hazard and operability (HAZOP) study is the third main contribution. This methodology addresses risks to intent (internal validity) as well as generalizability of results beyond the experimental setting (external validity) in a systematic and thorough manner. Low-Interaction Client Honeypots - Malicious web pages are usually part of a malware distribution network that consists of several servers that are involved as part of the drive-by-download attack. Development and evaluation of classification methods that assess whether a web page is part of a malware distribution network is the fourth main contribution. Hybrid Client Honeypot System - The fifth main contribution is the hybrid client honeypot system. It incorporates the mentioned classification methods in the form of a low-interaction client honeypot and a high-interaction client honeypot into a hybrid client honeypot systemthat is capable of identifying malicious web pages in a cost effective way on a large scale. The hybrid client honeypot system outperforms a high-interaction client honeypot with identical resources and identical false positive rate.</p>

Cost-effective Detection of Drive-by-Download Attacks with Hybrid Client Honeypots

<p>With the increasing connectivity of and reliance on computers and networks, important aspects of computer systems are under a constant threat. In particular, drive-by-download attacks have emerged as a new threat to the integrity of computer systems. Drive-by-download attacks are clientside attacks that originate fromweb servers that are visited byweb browsers. As a vulnerable web browser retrieves a malicious web page, the malicious web server can push malware to a user's machine that can be executed without their notice or consent. The detection of malicious web pages that exist on the Internet is prohibitively expensive. It is estimated that approximately 150 million malicious web pages that launch drive-by-download attacks exist today. Socalled high-interaction client honeypots are devices that are able to detect these malicious web pages, but they are slow and known to miss attacks. Detection ofmaliciousweb pages in these quantitieswith client honeypots would cost millions of US dollars. Therefore, we have designed a more scalable system called a hybrid client honeypot. It consists of lightweight client honeypots, the so-called low-interaction client honeypots, and traditional high-interaction client honeypots. The lightweight low-interaction client honeypots inspect web pages at high speed and forward only likely malicious web pages to the high-interaction client honeypot for a final classification. For the comparison of client honeypots and evaluation of the hybrid client honeypot system, we have chosen a cost-based evaluation method: the true positive cost curve (TPCC). It allows us to evaluate client honeypots against their primary purpose of identification of malicious web pages. We show that costs of identifying malicious web pages with the developed hybrid client honeypot systems are reduced by a factor of nine compared to traditional high-interaction client honeypots. The five main contributions of our work are: High-Interaction Client Honeypot The first main contribution of our work is the design and implementation of a high-interaction client honeypot Capture-HPC. It is an open-source, publicly available client honeypot research platform, which allows researchers and security professionals to conduct research on malicious web pages and client honeypots. Based on our client honeypot implementation and analysis of existing client honeypots, we developed a component model of client honeypots. This model allows researchers to agree on the object of study, allows for focus of specific areas within the object of study, and provides a framework for communication of research around client honeypots. True Positive Cost Curve As mentioned above, we have chosen a cost-based evaluationmethod to compare and evaluate client honeypots against their primary purpose of identification ofmaliciousweb pages: the true positive cost curve. It takes into account the unique characteristics of client honeypots, speed, detection accuracy, and resource cost and provides a simple, cost-based mechanism to evaluate and compare client honeypots in an operating environment. As such, the TPCC provides a foundation for improving client honeypot technology. The TPCC is the second main contribution of our work. Mitigation of Risks to the Experimental Design with HAZOP - Mitigation of risks to internal and external validity on the experimental design using hazard and operability (HAZOP) study is the third main contribution. This methodology addresses risks to intent (internal validity) as well as generalizability of results beyond the experimental setting (external validity) in a systematic and thorough manner. Low-Interaction Client Honeypots - Malicious web pages are usually part of a malware distribution network that consists of several servers that are involved as part of the drive-by-download attack. Development and evaluation of classification methods that assess whether a web page is part of a malware distribution network is the fourth main contribution. Hybrid Client Honeypot System - The fifth main contribution is the hybrid client honeypot system. It incorporates the mentioned classification methods in the form of a low-interaction client honeypot and a high-interaction client honeypot into a hybrid client honeypot systemthat is capable of identifying malicious web pages in a cost effective way on a large scale. The hybrid client honeypot system outperforms a high-interaction client honeypot with identical resources and identical false positive rate.</p>

High interaction valency ensures cohesion and persistence of a microtubule +TIP body at the plus-end of a single specialized microtubule in yeast

Microtubule plus-end tracking proteins (+TIPs) control microtubule specialization and are as such essential notably during eukaryotic cell division. Here, we investigated interactions and functions of the budding yeast Kar9 network consisting of the core +TIPs components Kar9 (functional homologue of APC, MACF, and SLAIN), Bim1 (orthologue of EB1), and Bik1 (orthologue of CLIP-170). Our data indicate that a redundant, multivalent web of interactions links the three +TIPs together to form a "Kar9 body" at the tip of a single cytoplasmic microtubule. They further suggest that this body is a liquid-like condensate, allowing it to persist on both growing and shrinking microtubule tips, and functions as a mechanical coupling device between microtubules and actin cables during mitosis. Our study underlines the power of dissecting the web of low-affinity interactions driving liquid-liquid phase separation of proteins in order to demonstrate the importance and establish the functional roles of condensation processes in vivo.

Effect of Interaction Intensity on Alignment and EFL Learners’ Oral Production in the Reading-Speaking Integrated Continuation Task

This study aims to uncover the relationship between interaction and alignment in a reading-speaking integrated continuation task, especially focusing on whether an increase in interaction intensity can lead to stronger alignment and further generate positive effects on L2 learning. To this end, 31 participants were asked to perform reading-speaking integrated continuation tasks under three different conditions featuring low, medium and high interaction intensity respectively. The results showed that 1) alignment existed in the reading-speaking integrated continuation task; 2) increasing interaction intensity generated stronger alignment at both linguistic and situational levels; 3) growing interaction intensity contributed to more coherent and accurate L2 oral production. These findings not only proved the workings of mind-body-world alignment, but also testified that increasing interaction intensity could bring about a stronger alignment effect (Wang, 2010), which then contributed to better L2 oral performance. These findings confirm again the role of interaction in L2 learning and suggest that alignment could possibly be a mediating factor that links interaction and L2 development. Pedagogical implications for teaching and learning L2 speaking are discussed.

Effect of Surfactant on the Formation of Chitosan/ε-Polycaprolactone Blend Films for Food Packaging Applications

The objective of this study was to develop and characterize chitosan-ε-polycaprolactone (CHI/PCL) polymer blends with Tween 80 as a compatibilizer for application in packaging. The blends were produced by casting, with up to 10% (w/w) PCL in the CHI matrix. These blends were characterized in terms of their microstructure, chemical interactions, mechanical and thermal properties, solubility and water vapor permeability (WVP). The micrographs showed microsphere-like structures from the PCL in the continuous phase of CHI. Fourier transform infrared spectroscopy (FTIR) indicated a high interaction between CHI amino groups and PCL carbonyls, resulting in blends with greater ductility than the pure CHI film, thus providing greater flexibility. In the crystallinity analyses, the presence of PCL favored an increase in crystalline regions, limiting the passage of light. Given the results, blends are an alternative for application in multilayer systems and can be considered for use as a biodegradable fraction in food packaging.

The Effect of Economic Constraints on Direct Real Estate Market

The objective of this research to investigate the interactions between the direct real estate markets with the financial stock market changes. To accomplish this objective data was collected of different official secondary sources. The collected data entered to SPSS and E-views for analysis. The results of this research showed that there is high interaction between the real estate market performance in Jordan and stock exchange market