Interaction Path Research Articles

Modeling and Simulation Research of Interactive Public Opinion Evolution under Multi-Agent Interventions

To study the interactive impact and multi-agent intervention effect caused by multiple public opinion events, a SI3R interactive public opinion communication model is proposed in this paper. Based on interactive public opinion evolution and influence paths of multi-agent interventions, the dynamic equation under multi-agent intervention is formulated; the equilibrium points of the model are calculated and the stability of the model is validated; and the assignment functions are constructed. Further, real data of the case study are obtained and set as initial model simulation parameters, the multi-agent intervention and control measures are numerically simulated and the effects of comprehensive public opinion control are obtained and put forward to suggestions for public opinion management. Simulation results show that the model can simulate the interactive propagation and evolution trend of multiple public opinion events, and imitate the intervention effect of each agent. Compared with the traditional transmission and infection model, it provides an assignment method combined with actual events. Taking the interaction of multiple public opinion events and the effect of multi-agent intervention into account, a new perspective for the formulation of public opinion supervision and control strategies can be provided.

Reconstructing distant interactions of multiple paths between perceptible nodes in dark networks.

Quantitative research of interdisciplinary fields, including biological and social systems, has attracted great attention in recent years. Complex networks are popular and important tools for the investigations. Explosively increasing data are created by practical networks, from which useful information about dynamic networks can be extracted. From data to network structure, i.e., network reconstruction, is a crucial task. There are many difficulties in fulfilling network reconstruction, including data shortage (existence of hidden nodes) and time delay for signal propagation between adjacent nodes. In this paper a deep network reconstruction method is proposed, which can work in the conditions that even only two nodes (say A and B) are perceptible and all other network nodes are hidden. With a well-designed stochastic driving on node A, this method can reconstruct multiple interaction paths from A to B based on measured data. The distance, effective intensity, and transmission time delay of each path can be inferred accurately.

A Review of Social Media Website Users’ Interaction Paths with Governmental Accounts during the COVID-19 Pandemic

This study aims to describe and analyze the paths of social media website users’ interaction with the content of government accounts during the COVID-19 pandemic. The objectives of the study are to describe the roles of government accounts as a tool to support the concept of health communication among users of social media websites and analyze the targeted and untargeted roles that have emerged in this context, describe the roles of government accounts as a tool of government communication and analyze how government institutions employed them during the COVID-19 pandemic, and describe the roles of social media websites as a tool to address the problems and challenges created by the social spacing procedures and solutions provided by these websites to deal with these challenges. This study surveys a sample of previous studies conducted on the roles of government accounts on social media websites during the COVID-19 pandemic. The tools of this study are both analytical and comparative as they analyze and compare the results of previous studies on the interaction paths of internet users. The results indicate that social media websites have been considered a pivotal tool for building a renewable and interactive system. This coincides with developments in the communication environment in which the individual is present within the social pattern, and its depth of impact has been demonstrated, particularly after the repercussions of the spread of the COVID-19 pandemic.

Fostering the diversity of exploratory testing in web applications

SummaryExploratory testing (ET) is a software testing approach that complements automated testing by leveraging business expertise. It has gained momentum over the last decades as it appeals testers to exploit their business knowledge to stress the system under test (SUT). Exploratory tests, unlike automated tests, are defined and executed on‐the‐fly by testers. However, testers who perform exploratory tests may be biased by their experience and, incidentally, miss anomalies or unusual interactions proposed by the SUT. This is even more complex in the context of web applications, which typically expose a huge number of interaction paths to their users. As testers of these applications cannot remember all the sequences of interactions they performed, they may fail to deeply explore the application scope. This article, therefore, introduces a new approach to assist testers in widely exploring any web application. In particular, our approach monitors the online interactions performed by the testers to suggest in real‐time the probabilities of performing next interactions. Looking at these probabilities, we claim that the testers who favour interactions that have a low probability (because they were rarely performed), will increase the diversity of their explorations. Our approach defines a prediction model, based on ‐grams, that encodes the history of past interactions and that supports the estimation of the probabilities. Integrated within a web browser extension, it automatically and transparently injects feedback within the application itself. We conduct a controlled experiment and a qualitative study to assess our approach. Results show that it prevents testers to be trapped in already tested loops, and succeeds to assist them in performing deeper explorations of the SUT.

Abstract 2723: Model-based cancer therapy selection by linking tumor vulnerabilities to drug mechanism

Abstract Selection of the treatments most likely to combat a patient’s tumor is a central aim of precision oncology. We are currently developing a functional precision oncology program at the University of Utah and Huntsman Cancer Institute that combines the multi-omic characterization of a patient's tumor with the functional screening of relevant drug candidates in patient-derived organoid tumor models to identify which drugs are uniquely capable of combating the patient’s cancer. Here we present our model-based approach for utilizing the multi-omic tumor data to computationally predict the patient’s response to each drug. In this approach, we first identify the genomic and transcriptomic vulnerabilities of the tumor as genes harboring somatic DNA mutations or copy number changes (from paired tumor/normal WGS/WES DNA sequencing data), as well as genes whose expression levels have been significantly altered in the tumor (based on bulk or single-cell RNA sequencing data). Second, using targeting information from drug-gene interaction databases (DGIdb) we compile a list of genes targeted by each drug relevant in the patient’s treatment. Third, we utilize gene interaction database knowledge (KEGG) to construct a gene interaction graph to link each drug’s gene targets with all of the tumor’s vulnerability genes. We then identify all gene interaction paths connecting specific drug target genes with specific vulnerability genes; and score each path and combine all path-specific scores for the target-vulnerability gene pair. Subsequently, we further combine all pairwise scores across all drug target genes and all tumor vulnerability genes and determine the statistical significance of the resulting score by sampling the background distribution of such scores across random drugs, target genes, and vulnerability genes. We have applied our algorithm to predict drug response in advanced breast cancer patients as well as using publicly available tumor cell line data (GDSC2). We have found a high level of concordance between our computational prediction and organoid/cell line screening results, clearly separating sensitive and non-sensitive models. Using Bayesian probability, we compare the drug-specific score distributions of sensitive and non-sensitive models and are able to identify sensitive cell lines/patients with high accuracy. By encapsulating available information on direct gene-gene interactions, the drug’s direct gene targets and the collected omic vulnerabilities of the tumor, our model is not only capable of predicting sensitivity to both targeted and chemotherapy agents, but can also provide a mechanistic understanding for the targeting of the tumor. Our approach will be validated and fine-tuned on a large cohort of breast and brain cancer patients as well as patient PDX models, interrogating gene-target interactions to identify novel relevant target genes/pathways. Citation Format: Szabolcs Tarapcsak, Yi Qiao, Xiaomeng Huang, Tony Di Sera, Matthew H. Bailey, Bryan E. Welm, Alana L. Welm, Gabor T. Marth. Model-based cancer therapy selection by linking tumor vulnerabilities to drug mechanism [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2723.

Mid-infrared supercontinuum-based Fourier transform spectroscopy for plasma analysis

Broadband mid-infrared (MIR) spectroscopy is a well-established and valuable diagnostic technique for reactive plasmas. Plasmas are complex systems and consist of numerous (reactive) types of molecules; it is challenging to measure and control reaction specificity with a good sensitivity. Here, we demonstrate the first use of a novel MIR supercontinuum (SC) source for quantitative plasma spectroscopy. The SC source has a wide spectral coverage of 1300–2700 cm−1 (wavelength range 3.7–7.7 μm), thus enabling broadband multispecies detection. The high spatial coherence of the MIR SC source provides long interaction path lengths, thereby increasing the sensitivity for molecular species. The combination of such a SC source with a custom-built FTIR spectrometer (0.1 cm−1 spectral resolution) allows detection of various gases with high spectral resolution. We demonstrate its potential in plasma applications by accurate identification and quantification of a variety of reaction products (e.g. nitrogen oxides and carbon oxides) under low-pressure conditions, including the molecular species with overlapping absorbance features (e.g. acetone, acetaldehyde, formaldehyde, etc.).

Managerial Ability and Investors Protect: Test of Stimulating Decision-Making Functions by Devil's Advocate Theory

The efforts of the developers of capital market laws and regulations over the past years have been aimed at increasing the level of information transparency to create more symmetry between companies and shareholders so that they can be more attractive to investors to invest in the stock market. But given the interplay of individual characteristics of corporate decision-makers with the interests of shareholders and investors, it seems that focusing on behavioral functions in the area of promoting managerial ability can more effectively lead to increased protection of shareholder interests. The purpose of this study is to investigate the effect of management ability on the protection of investors based on the development of the theory of the devil's advocate. Therefore, the present study, using the structural equation modeling approach and partial least squares analysis (PLS), while fitting the model's desirability, examined the impact of management ability on protecting investors. In this study, in order to measure the in-field variable, ie protection of shareholders' interests, a researcher-made questionnaire was created through meta-analysis with the participation of 15 research experts. Then the criterion of Demirjan et al (2013) was used to measure managerial ability as an exogenous variable in partial least squares analysis. The researcher-made questionnaire was sent to 142 CEOs of companies listed on the Tehran Stock Exchange, and finally, after many follow-ups, 105 questionnaires were completed and returned and used as a final sample for analysis. After ensuring the acceptable fit of the measurement and structural models of the research, according to the theory of the devil's advocate, the results showed that the ability of management has a positive and significant effect on protecting the investors. Managerial ability, as one of the specialized decision-making capacities, puts the company on the path of effective interaction with stakeholders and provides the ground for investors to Protect in companies' priorities to gain their trust.

Poly(lactic acid)/Poly(butylene succinate) (PLA/PBS) Layered Composite Gas Barrier Membranes by Anisotropic Janus Nanosheets Compartibilizers.

Poly(lactic acid) (PLA), one of the most promising biodegradable polymer products, has achieved wide applications for its relatively good mechanical properties and moderate degradability. Here we report an environment-friendly filler, the organic-inorganic composite Janus nanosheets (PLA/PBS JNs), which can jam at the interface of the PLA/PBS blend with a low threshold as the compatibilizer and can simultaneously toughen the composites and improve the gas barrier performance due to better interfacial interaction and tortuous path effect. With 0.3 wt % of PLA/PBS JNs added, the tensile strength and elongation at break of the PLA/PBS blend can be improved by 37% and 224%, respectively. After a further hot-pressing process, the barrier performance of the PLA/PBS composite membranes can be significantly enhanced since PLA, PLA/PBS JNs, and PBS are arranged in a nearly lamellar structure with oxygen permeability of 0.63 × 10-15 cm3 cm·cm-2 s-1 Pa-1 with only 0.5 wt % of PLA/PBS JNs.

Magnetic state in the quasi-two-dimensional organic conductor λ−(BEST)2FeCl4 and the path of π−d interaction

Studies of the quasi-two-dimensional organic conductors $\ensuremath{\lambda}\text{\ensuremath{-}}{(D)}_{2}M{\mathrm{Cl}}_{4}$ [$D=\text{donor molecules}$, $M=\mathrm{Ga},\mathrm{Fe}$] have shown that $\ensuremath{\lambda}\text{\ensuremath{-}}{(\mathrm{BETS})}_{2}{\mathrm{GaCl}}_{4}$ [BETS = bis(ethylenedithio)tetraselenafulvalene] undergoes an unconventional superconducting transition and $\ensuremath{\lambda}\text{\ensuremath{-}}{(\mathrm{BETS})}_{2}{\mathrm{FeCl}}_{4}$ undergoes a field-induced superconducting transition. In $\ensuremath{\lambda}$-type salts, the interactions between donor molecules and ${\mathrm{FeCl}}_{4}^{\ensuremath{-}}$ ($\ensuremath{\pi}\text{\ensuremath{-}}d$ interactions) are important. To investigate $\ensuremath{\pi}\text{\ensuremath{-}}d$ interaction, a pair of magnetic $M=\mathrm{Fe}$ and nonmagnetic $M=\mathrm{Ga}$ salts which have the same ground state in the donor layer is desired. However, no such pair has been found, and few experimental studies have considered $\ensuremath{\pi}\text{\ensuremath{-}}d$ interaction paths. $\ensuremath{\lambda}\text{\ensuremath{-}}{(\mathrm{BEST})}_{2}M{\mathrm{Cl}}_{4}$ [BEST = bis(ethylenediseleno)tetrathiafulvalene] are obtained for both anions, and $M=\mathrm{Ga}$ salt shows an antiferromagnetic transition, but the ground state has not been analyzed in $M=\mathrm{Fe}$ salt. We perform x-ray diffraction, magnetic susceptibility measurement, and M\"ossbauer spectroscopy in $\ensuremath{\lambda}\text{\ensuremath{-}}{(\mathrm{BEST})}_{2}{\mathrm{FeCl}}_{4}$. We find that a magnetic transition is observed at around 26 K. The $\ensuremath{\lambda}\text{\ensuremath{-}}{(\mathrm{BEST})}_{2}M{\mathrm{Cl}}_{4}$ system is a system in which both ${\mathrm{FeCl}}_{4}^{\ensuremath{-}}$ and ${\mathrm{GaCl}}_{4}^{\ensuremath{-}}$ salts show antiferromagnetic transitions. In addition, the ethylene motions observed at room temperature are ordered around 108 K, resulting in the establishment of the $\ensuremath{\pi}\text{\ensuremath{-}}d$ interaction path between chalcogens and the anion, and low-field magnetization suggests that the $\ensuremath{\pi}\text{\ensuremath{-}}d$ interaction in $\ensuremath{\lambda}\text{\ensuremath{-}}{(\mathrm{BEST})}_{2}{\mathrm{FeCl}}_{4}$ is smaller than that in $\ensuremath{\lambda}\text{\ensuremath{-}}{(\mathrm{BETS})}_{2}{\mathrm{FeCl}}_{4}$. Our results show that the inner chalcogen of donor molecules is important as the path of the interaction.

Scattering enhanced photoacoustic gas sensor based on acetate membrane

AbstractIn this paper, a scattering enhanced photoacoustic spectroscopy (SEPAS) technique is introduced for trace gas detection. An acetate membrane is mounted at the inner wall of a miniaturized photoacoustic (PA) cell to improve the light‐gas interaction path. It has been found out from theoretical simulations that the light rays in the PA cell with the acetate material are obviously denser, leading to a large enhancement of the PA signal. A SEPAS system, mainly consisting of a PA sensor, a near‐infrared distributed feedback laser source, and a high‐speed demodulator has been developed for CH4 detection. The experimental results have successfully proved that the SEPAS technique based on the porous acetate material can achieve at least three times enhancement on the PA signal, compared with the PA cell without the acetate membrane. The minimum detection limit is calculated to be 57.5 parts per billion with an averaging time of 100 s.

Influence of soil properties on cadmium accumulation in vegetables: Thresholds, prediction and pathway models based on big data

Soil properties, such as soil pH, soil organic matter (SOM), cation exchange capacity (CEC), are the most important factors affecting cadmium (Cd) accumulation in vegetables. In this study, we conducted big data mining of 31,342 soil and vegetable samples to examine the influence of soil properties (soil pH, SOM, CEC, Zn and Mn content) on the accumulation of Cd in root, solanaceous, and leafy vegetables in Hunan Province, China. Specifically, the Cd accumulation capability was in the following order: leafy vegetables > root vegetables > solanaceous vegetables. The soil property thresholds for safety production in vegetables were determined by establishing nonlinear models between Cd bioaccumulation factor (BCF) and the individual soil property, and were 6.5 (pH), 30.0 g/kg (SOM), 13.0 cmol/kg (CEC), 100–140 mg/kg (Zn), and 300–400 mg/kg (Mn). When soil property values were higher than the thresholds, Cd accumulation in vegetables tended to be stable. Prediction models showed that pH and soil Zn were the leading factors influencing Cd accumulation in root vegetables, explaining 87% of the variance; pH, SOM, soil Zn and Mn explained 68% of the variance in solanaceous vegetables; pH and SOM were the main contributors in leafy vegetables, explaining 65% of the variance. Further, variance partitioning analysis (VPA) revealed that the interaction effect of the corresponding key soil properties contributed mostly to BCF. Meanwhile, partial least squares (PLS) path modeling was employed to analyze the path and the interactive effects of soil properties on Cd BCF. pH and SOM were found to be the biggest two players affecting BCF in PLS-models, and the most substantial interactive influence paths of soil properties on BCF were different among the three types of vegetables.

Design and implementation of an autonomous service robot based on cyber physical modeling systems

An autonomous robot is designed and implemented to support the service works. Many technologies were adapted, namely human-robot interaction order system, path planning and mapping in indoor, Robot Operating System (ROS), and Cyber Physical System (CPS). Many subsystems are developed and constructed based on ROS to implement a human-interaction action in completing service robot tasks. A human-robot interaction order system is designed for the convenient human servicing purpose. Therefore, the customer quickly finds the commodity information through the internet. This system recommends the commodity according to the content of the database. In addition, the customer makes an order by touch screen interface, and then it sends a command to control the robot to deliver the commodity. In the second subsystem, it includes path planning and mapping generation. The well-known simultaneous localization and mapping (SLAM) concept with a Rao-Blackwellized particle filter (RBPF) addresses the appropriated maps after completing the exploration of the indoor environment. In order to reach better robustness and agility, the hybrid path planning algorithm includes a global A* algorithm and local dynamic window approach (DWA) to navigation. In the third subsystem, the Gazebo makes the perfect construction of CPS design. Finally, the simulation and implementation of dual-arm robot navigation with the interactive order situation to efficiently support servicing actions of the robot and finish the required tasks.

An RPG Game Design for English Learning using ADDIE Methods

Technology makes easier to study English language easier by social media, websites, books, or even seminars. RPG game is a type of game that tell the story and information by virtual and interactive path. Most students that struggling learning English have faced complexity and difficulty in learning them. This study aims to create a RPG game that can help learning English. The method used for this study is ADDIE (Analysis, Design, Development, Implement, Evaluate) method and the software required for this study are Unity and Visual Studio 2019. ADDIE method is a learning model that instructional designers and training developers have used to create methods of learning effectiveness learning, this learning model is an acronym for a five-step process which are: Analysis, Design, Development, Implementation, and evaluation. And therefore the software used to develop the game are Unity. The result of this research is a RPG game that can be used for learning English. With this RPG game, it is hoped that the game can help with students who struggle learning English.

Interaction paths analysis and stability-enhancing methods for LCC-HVDC system with weak receiving-end grid

The stability problem becomes more prominent when line-commuted converter based high voltage direct current (LCC-HVDC) system is connected to weak receiving AC network. Although the impacts of controller parameters on the stability of LCC-HVDC system have been well studied, the interaction mechanism between LCC and weak AC network has not been totally understood and revealed. As a result, the proposal of corresponding solutions is restricted. To remedy such insufficiency, firstly, the sketchy interaction paths between LCC and AC network are extracted and analyzed in this paper based on the motion equation model. The results reveal that the phase interaction path provides negative damping and is the main contributor to the instability. Moreover, since the extinction angle (EA) is the critical node in phase path, the impacts of two coefficients of EA on the system stability are analyzed, namely phase tracking error (PTE)-EA coefficient kδγ and firing angle order (FAO)-EA coefficient kαoγ. The theoretical analysis shows that increasing kδγ or decreasing kαoγ will strengthen the system damping. Next, the comprehensive physical explanations for the above discoveries are presented. Then, two methods that have the same effects on modifying these coefficients are proposed to enhanced the system stability. Finally, the effectiveness of these two methods is verified by the simulations in PSCAD/EMTDC.

Facial Skincare Journey

Consumer journey analysis led to efficient marketing implementation. A journey represents a path of steps and interaction between consumer and service units at each touchpoint. Dissatisfaction in the touchpoint, causes a negative effect to retain a customer. Previous studies always constructed the journey maps relied on the narrative approach. According to use Google, consumers always face massive websites to access, which is a pain point in the journey. Improving consumer buying, led to the research aims: identifying consumer needs, and reducing SEO pain-point using content relevance indexing. The data (social media posts from the Thai beauty communities in the year 2020) is analyzed and has found that there are two need types: curative and preventive. The study can segment the 150 websites into four groups which reduce the search space. Moreover, the significant words from the wrapping technique can use to create keywords in the homepage introduction that are matching the products to consumer needs.

Ecological Security Evaluation for Marine Ranching Based on the PLTS/ANP Method: A Case Study of Rongcheng

The evaluation index system of ecological security of marine ranching (MRES) is based on the assumption that there is independence among evaluation indexes in the existing studies, which ignores the complex interactive paths of marine ranching as an artificial ecosystem. In this study, the MRES evaluation network model that includes interdependent relationships is established based on the Driver-Pressure-State-Impact-Response model and the analytic network process method. Then, the probabilistic linguistic term sets and analytic network process methods are used to calculate the weights of the evaluation indexes of MRES. The overall evaluation value and the contribution rate of clusters are consequently defined and analyzed to reflect the performance of MRES. Finally, a case study is carried out for evaluating the MRES of marine ranches in Rongcheng by means of the proposed method. The conclusions are summarized as follows: (1) The weights of clusters are ranked as Responses > Impact > Driver > State > Pressure, and “scientific management of fishery resources” is the most important index; (2) the MRES performance of marine ranches in the city of Rongcheng is at the medium security grade on the whole, and all 11 samples are driven by the response.

Big I Notation to Estimate the Interaction Complexity of Interaction Concepts

ABSTRACT Efficiency of use is an important quality criterion of usability ISO9241-110-2019. Since design for efficiency often requires functional support, an early consideration of efficiency in the design process is critical. It is desirable to have a technique at hand, which can be applied to the earliest design artifacts (i.e. interaction concepts), and its application only takes a few minutes. Available techniques (e.g., KLM, FLM, modeling techniques, and summative usability tests) require either detailed user interface designs or significant more time for its application. This paper proposes the big I notation (with the capital letter i). It is based on the big O notation. The big I notation estimates the growth of interaction steps for the longest interaction path executed once. It can be applied to interaction concepts. The formal definition of the big I notation is introduced, and examples are shown to demonstrate its use and benefits.

模拟计算平行样对流域生物信息流估算的影响

PDF HTML阅读 XML下载 导出引用 引用提醒 模拟计算平行样对流域生物信息流估算的影响 DOI: 10.5846/stxb202104271109 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 农业农村部财政专项"长江渔业资源与环境调查"(CJDC-2017-14);中国水产科学研究院中央级公益性科研院所基本科研业务费专项(2020JBF01,2020TD08) Simulating the impacts of parallel samples on the estimations of upstream-to-downstream watershed biological information flow Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:流域生物信息流是流域生态学研究中的重要内容,是流域生态系统中的物质输移和能量输移过程的信息标记,是用eDNA技术调查评估河流水体中物种组成空间特征的基础。估算流域生物信息流是流域生态系统过程研究和eDNA技术调查评估河流水体中物种组成空间特征的关键。在有限的调查采样中,平行样的数量如何影响流域生物信息流的估算,尚待解答。基于随机抽样调查的基本原理,提出假设--采样数量不影响流域生物信息流估算结果的准确度,但会影响其精密度,然后通过问题简化转化和模拟计算,对该假设进行了检验。模拟计算结果显示,随着样点生物信息检出度(平行样数量)的增大,流域生物信息流估算结果会从偏小逐渐靠近流域生物信息流实际值,同时其99.9%置信区间也逐渐集中于流域生物信息流实际值。即样点生物信息检出度(平行样数量)对流域生物信息流估算的准确度和精密度均有影响。在实际调查研究过程中,建议先在所研究区域对平行样数量和样点生物信息检出度的关系进行预评估,然后基于流域生物信息流估算可信度目标在正式实施方案中经济有效地设置平行样,基于多平行样调查结果估算流域生物信息流,再根据各样点生物信息检出状况对流域生物信息流估算结果进行后验评估。 Abstract:Watershed biological information flow (WBIF) is defined as the path, processes and control of biological information transport, exchange, interaction and feedback among different spaces and systems along with watershed ecosystem processes, and could be partly described as the land-to-river and upstream-to-downstream bioinformation transportation (including organisms, nucleic acids, peptides and other biomarkers), which is driven by the hydrologic processes of watershed systems. The WBIF labels the transport of organic matter and energy. The WBIF integrates the ecological processes of environmental DNA (eDNA), including the origin, state, transport, and fate of eDNA, and makes it possible that the species composition in river system is monitored and assessed using eDNA. The WBIF estimation is the key for watershed ecosystem processes studying and riverine biodiversity monitoring. However, in practice, the parallel samples in each sampling site always are limited. And how parallel samples would impact WBIF estimation is unknown. Based on the principles of stochastic sampling survey, we hypothesized that parallel samples would not impact the accuracy of the WBIF estimation, but affect the precision of the WBIF estimation. Then, we transformed this hypothesis into a set of formulas and tested it with a series of analog computation. Results showed that the number of parallel samples (efficiency of detection) affected both the accuracy and precision of the WBIF estimation. The optimal WBIF estimation was less than the actual WBIF in any condition. Along with the increase of parallel samples (efficiency of detection), the optimal WBIF estimation gradually neared to the actual WBIF, the range of WBIF estimation gradually focused on the actual WBIF. In other words, more parallel samples (higher efficiency of detection) led higher accuracy and precision of the WBIF estimation. In addition, the actual WBIF affected both the accuracy and precision of the WBIF estimation too. Larger actual WBIF led higher accuracy and precision of the WBIF estimation. The relative relationship between the number of biological information types in upstream and downstream samples affected both the accuracy and precision of the WBIF estimation too. The accuracy and precision of WBIF estimation would be higher when the number of biological information types in upstream samples was more than those in downstream samples. So, we suggest that in the work of watershed ecosystem processes studying and riverine biodiversity monitoring, the relationship between parallel sample number and detection efficiency should be assessed, the suitable parallel sample number should be estimated based on the reliability target of WBIF estimation, the sampling program should be designed with suitable parallel samples, the WBIF should be estimated based on all parallel samples of each sampling site, at last the estimated results of WBIF should be re-evaluated according to the posterior probability of WBIF in different conditions. The current work provided the framework and methodology reference for the post-evaluation. 参考文献 相似文献 引证文献

Shed Light on the Path of Human-Machine Interaction in Autonomous Vehicles: Where Did We Come from, Where We are Going?

Shed Light on the Path of Human-Machine Interaction in Autonomous Vehicles: Where Did We Come from, Where We are Going?

Enhancing outdoor campus design by utilizing space syntax theory for social interaction locations

Education is mainly the process of facilitating learning which includes teaching, training, and other methods. To accomplish education, learning space whether indoor or outdoor must be suitable to empower students to reach that goal. Universities must integrate more outdoor space to encourage social interaction. Social interaction in university campuses can boost the sense of belonging and enhance wellbeing. In this study, the social spaces of a governmental University campus in the Delta area (Egypt) are investigated. Students are asked if they spent time between and after lectures/practical work together and where they spent it. They are also asked in a form of questionnaire to evaluate both the sensory and physical features of the space and to list their priorities. This is followed by an analysis of integration and choice based on the space syntax theory of outdoor spaces and routes. This study points out to the importance of students’ participation in providing suitable social interaction locations, paths, and routes in campuses that meet their needs. Space syntax theory is then applied to optimize decision-making. The research aims at providing responsive spaces in existing campuses and for guiding the design of new ones in future projects.