A Study on the Explainability of Thyroid Cancer Prediction:SHAP Values and Association-Rule Based Feature Integration Framework

In the era of advanced machine learning techniques,the development of accurate predictive models for complex medical conditions,such as thyroid cancer,has shown remarkable progress.Accurate predictivemodels for thyroid cancer enhance early detection,improve resource allocation,and reduce overtreatment.However,the widespread adoption of these models in clinical practice demands predictive performance along with interpretability and transparency.This paper proposes a novel association-rule based feature-integratedmachine learning model which shows better classification and prediction accuracy than present state-of-the-artmodels.Our study also focuses on the application of SHapley Additive exPlanations(SHAP)values as a powerful tool for explaining thyroid cancer prediction models.In the proposed method,the association-rule based feature integration framework identifies frequently occurring attribute combinations in the dataset.The original dataset is used in trainingmachine learning models,and further used in generating SHAP values fromthesemodels.In the next phase,the dataset is integrated with the dominant feature sets identified through association-rule based analysis.This new integrated dataset is used in re-training the machine learning models.The new SHAP values generated from these models help in validating the contributions of feature sets in predicting malignancy.The conventional machine learning models lack interpretability,which can hinder their integration into clinical decision-making systems.In this study,the SHAP values are introduced along with association-rule based feature integration as a comprehensive framework for understanding the contributions of feature sets inmodelling the predictions.The study discusses the importance of reliable predictive models for early diagnosis of thyroid cancer,and a validation framework of explainability.The proposed model shows an accuracy of 93.48%.Performance metrics such as precision,recall,F1-score,and the area under the receiver operating characteristic(AUROC)are also higher than the baseline models.The results of the proposed model help us identify the dominant feature sets that impact thyroid cancer classification and prediction.The features{calcification}and{shape}consistently emerged as the top-ranked features associated with thyroid malignancy,in both association-rule based interestingnessmetric values and SHAPmethods.The paper highlights the potential of the rule-based integrated models with SHAP in bridging the gap between the machine learning predictions and the interpretability of this prediction which is required for real-world medical applications.

Amine-grafted on lanthanide metal-organic frameworks:Three solid base catalysts for Knoevenagel condensation reaction

A post-synthetic modification strategy has been used to prepare three solid base catalysts, including Er（btc）（ED）075（H2O）0.25 （2, btc = 1,3,5-benzenetricarboxylates, ED = 1,2-ethanediamine）, Er（btc）（PP）0.55（H20）0.45 （3, PP = piperazine）, and Er（btc）（DABCO）0.15（H2O）0.85 （4, DABCO = 1,4- diazabicyclo[2.2.2]octane）, by grafting three different diamines onto the coordinatively unsaturated Er（III） ions into the channels of the desolvated lanthanide metal-organic framework （Er（otc））. The resulting metal-organic frameworks were characterized by elemental analysis, thermogravimetric analysis, powder X-ray diffraction, and N2 adsorption. Based on its higher loading ratio of the diamine, as well as its greater stability and porosity, catalyst 2 exhibited higher catalytic activity and reusability than catalysts 3 and 4- for the Knoevenagel condensation reaction. The catalytic mechanism of 2 has also been investigated using size-selective catalysis tests.

Market based framework for multiple AUVs cooperation

A“Market” based framework for multiple AUVs team is introduced in this paper.It is a distributed meta-level task allocation framwork. The formulation and the basic concepts of the “Market” such as “goods” and “price” are discussed first, then the basic algorithm of the “auction”. The loosely coupled v-MDTSP tasks are considered as an example of the task allocation mission. A multiple AUV team controller and a detailed algorithm are developed for such applications. The simulation results show that the controller has the advantages such as robustness and low complexity and it can achieve better optimization results than the classical central controller (such as GA) in some tasks. And the comparison of two different local solvers also implies that we should get the reasonable task allocation even not using the high quality algorithm, which can considerably decrease the cooperation computation.

A thiophene-containing covalent triazine-based framework with ultramicropore for CO2 capture

In this work, a 2D covalent triazine-based framework was prepared by using 1,3-dicyanobenzo[c]thiophene（DCBT） as monomer to effectively capture CO. The resulting CTF-DCBT was characterized by FT-IR, XPS, PXRD, elemental analysis, SEM, TEM, and Nadsorption-desorption.The results indicate that CTF-DCBT is partially crystalline and has ultramicropore（6.5 A?） as well as high heteroatom contents（11.24 wt% and 12.61 wt% for N and S, respectively）. In addition, the BET surface area and total pore volume of CTF-DCBT are 500 m/g and 0.26 cm/g, respectively. CTF-DCBT possesses excellent thermal stability（450 °C） and chemical stability towards boiling water, 4 M HCl, and 1 M Na OH.The COadsorption capacity of CTF-DCBT is 37.8 cm/g at 1 bar and 25 °C. After six adsorption-desorption cycles, there is no obvious loss of COuptake observed. Due to the ultramicropore and high heteroatom contents, CTF-DCBT has high isosteric heats of adsorption for COand high selectivities of COover Nand CH. At 25 °C, the CO/Nand CO/CHselectivities are 112.5 and 10.3, respectively, which are higher than those of most POFs. Breakthrough curves indicate that CTF-DCBT could effectively separate CO/Nand CO/CHmixtures.

Carbon-based derivatives from metal-organic frameworks as cathode hosts for Li–S batteries

Lithium-sulfur batteries(Li–S batteries) are promising candidates for the next generation high-energy rechargeable Li batteries due to their high theoretical specific capacity(1672 m Ahg-1) and energy density(2500 Wh kg-1). The commercialization of Li–S batteries is impeded by several key challenges at cathode side, e.g. the insulating nature of sulfur and discharged products(Li2S 2 and Li2S), the solubility of long-chain polysulfides and volume variation of sulfur cathode upon cycling. Recently, the carbonbased derivatives from metal-organic frameworks(MOFs) has emerged talent in their utilization as cathode hosts for Li–S batteries. They are not only highly conductive and porous to enable the acceleration of Li +/e-transfer and accommodation of volumetric expansion of sulfur cathode during cycling, but also enriched by controllable chemical active sites to enable the adsorption of polysulfides and promotion of their conversion reaction kinetics. In this review, based on the types of MOFs(e.g. ZIF-8, ZIF-67, Prussian blue, Al-MOF, MOF-5, Cu-MOF, Ni-MOF), the synthetic methods, formation process and morphology, structural superiority of MOFs-derived carbon frameworks along with their electrochemical performance as cathode host in Li–S batteries are summarized and discussed.

A new image watermarking framework based on levels-directions decomposition in contourlet representation

With the development of digital information technologies,robust watermarking framework is taken into real consideration as a challenging issue in the area of image processing,due to the large applicabilities and its utilities in a number of academic and real environments.There are a wide range of solutions to provide image watermarking frameworks,while each one of them is attempted to address an efficient and applicable idea.In reality,the traditional techniques do not have sufficient merit to realize an accurate application.Due to the fact that the main idea behind the approach is organized based on contourlet representation,the only state-of-the-art materials that are investigated along with an integration of the aforementioned contourlet representation in line with watermarking framework are concentrated to be able to propose the novel and skilled technique.In a word,the main process of the proposed robust watermarking framework is organized to deal with both new embedding and de-embedding processes in the area of contourlet transform to generate watermarked image and the corresponding extracted logo image with high accuracy.In fact,the motivation of the approach is that the suggested complexity can be of novelty,which consists of the contourlet representation,the embedding and the corresponding de-embedding modules and the performance monitoring including an analysis of the watermarked image as well as the extracted logo image.There is also a scrambling module that is working in association with levels-directions decomposition in contourlet embedding mechanism,while a decision maker system is designed to deal with the appropriate number of sub-bands to be embedded in the presence of a series of simulated attacks.The required performance is tangibly considered through an integration of the peak signal-to-noise ratio and the structural similarity indices that are related to watermarked image.And the bit error rate and the normal correlation are considered that are related to the extracted logo analysis,as well.Subsequently,the outcomes are fully analyzed to be competitive with respect to the potential techniques in the image colour models including hue or tint in terms of their shade,saturation or amount of gray and their brightness via value or luminance and also hue,saturation and intensity representations,as long as the performance of the whole of channels are concentrated to be presented.The performance monitoring outcomes indicate that the proposed framework is of significance to be verified.

Synthesis, Structure and Electrocatalytic Activity of Perfluorinated Covalent Triazine-based Framework

Using the bottom-up method, we synthesized a series of perfluorinated covalent triazine-based frameworks(FCTFs) with porous structures for catalysis oxygen reduction reaction(ORR). The evolved FCTFs by high-temperature carbonization show an apparent variation in electrocatalytic activity toward the ORR dependent on the type of F. The samples synthesized at 900 ℃(FCTF-900) exhibits advantages in terms of high activity, high durability, and methanol-tolerant as an efficient electrocatalyst for ORR, manifests a comparable or even better activity as compared with the commercial Pt/C catalysts not only in alkaline media but also in acidic and neutral electrolyte.

A Conceptual and Computational Framework for Aspect-Based Collaborative Filtering Recommender Systems

Many datasets in E-commerce have rich information about items and users who purchase or rate them. This information can enable advanced machine learning algorithms to extract and assign user sentiments to various aspects of the items thus leading to more sophisticated and justifiable recommendations. However, most Collaborative Filtering (CF) techniques rely mainly on the overall preferences of users toward items only. And there is lack of conceptual and computational framework that enables an understandable aspect-based AI approach to recommending items to users. In this paper, we propose concepts and computational tools that can sharpen the logic of recommendations and that rely on users’ sentiments along various aspects of items. These concepts include: The sentiment of a user towards a specific aspect of a specific item, the emphasis that a given user places on a specific aspect in general, the popularity and controversy of an aspect among groups of users, clusters of users emphasizing a given aspect, clusters of items that are popular among a group of users and so forth. The framework introduced in this study is developed in terms of user emphasis, aspect popularity, aspect controversy, and users and items similarity. Towards this end, we introduce the Aspect-Based Collaborative Filtering Toolbox (ABCFT), where the tools are all developed based on the three-index sentiment tensor with the indices being the user, item, and aspect. The toolbox computes solutions to the questions alluded to above. We illustrate the methodology using a hotel review dataset having around 6000 users, 400 hotels and 6 aspects.

Testability Estimation of Framework Based Applications

Quality of software systems is highly demanded in today’s scenario. Highly testable system enhances the reliability also. More than 50% of test effort-time and cost are used to produce a highly testable system. Thus, design-for-testability is needed to reduce the test effort. In order to enhance the quality, productivity and reduced cost of the software organizations are promoting to produce the reuse-oriented products. Incorporating reuse technology in both aspects-software development process and test process may payoff many folds. Keeping this view, our study focus the testability of the object-oriented framework based software systems and identify that flexibility at the variable points of the object-oriented framework, chosen for framework instantiation, greatly affects the testability of object-oriented framework based software at each level of testing. In the current paper, we propose a testability model considering the flexible aspect of the variable point to estimate testability in the early phase, requirement analysis phase, of development process of the framework based software. The proposed model helps to improve the testability of the software before the implementation starts thus reducing the overall development cost.

Using a Task-based Teaching Framework in Lesson Designing

Task-basedteachingandlearningis becoming more and more popularin China now,andthe aimof taskis to create a real purpose for language use and provide a natural context for language study· This article introduces what a task-based teaching frameworkis and the three phases of pre-task, while-task and post-task,combined withsomethoughts about howwe shouldconvertthosetasksinto actual classroomactivities while using the task-based teaching framework in designing the lessons and howthe teacher and students participate inthe lessons·

Optimization of RDF link traversal based query execution

Aiming at the problem that only some types of SPARQL （ simple protocal and resource description framework query language） queries can be answered by using the current resource description framework link traversal based query execution （RDF-LTE） approach, this paper discusses how the execution order of the triple pattern affects the query results and cost based on concrete SPARQL queries, and analyzes two properties of the web of linked data, missing backward links and missing contingency solution. Then three heuristic principles for logic query plan optimization, namely, the filtered basic graph pattern （FBGP） principle, the triple pattern chain principle and the seed URIs principle, are proposed. The three principles contribute to decrease the intermediate solutions and increase the types of queries that can be answered. The effectiveness and feasibility of the proposed approach is evaluated. The experimental results show that more query results can be returned with less cost, thus enabling users to develop the full potential of the web of linked data.

A Triple Nexus Water-Energy-Housing (WEH) Framework Modelling towards Improved Decision-Making in Humanitarian Operations

Given the challenges facing most humanitarian operations worldwide, a change of approach is needed to ensure greater sustainability of humanitarian settlements right from the planning stage. Some studies attribute unsustainability to inadequate provision of basic resources and highlight the apparent bottlenecks that prevent access to the meaningful data needed to plan and remedy problems. Most operations have relied on an “ad hoc ism” approach, employing parallel and disconnected data processing methods, resulting in a wide range of data being collected without subsequent prioritization to optimize interconnections that could enhance performance. There have been little efforts to study the trade-offs potentially at stake. This work proposes a new framework enabling all subsystems to operate in a single system and focusing on data processing perspective. To achieve this, this paper proposes a Triple Nexus Framework as an attempt to integrate water, energy, and housing sector data derived from a specific sub-system within the overall system in the application of Model-Based Systems Engineering. Understanding the synergies between water, energy, and housing, Systems Engineering characterizes the triple nexus framework and identifies opportunities for improved decision-making in processing operational data from these sectors. Two scenarios illustrate how an integrated platform could be a gateway to access meaningful operational data in the system and a starting point for modeling integrated human settlement systems. Upon execution, the model is tested for nexus megadata processing, and the optimization simulation yielded 67% satisfactory results, demonstrating that an integrated system could improve sustainability, and that capacity building in service delivery is more than beneficial.

Two Generic Frameworks of Multiple Viewpoints Oriented Requirements Method and Their Comparison

Traditional requirements method has some problems when it is used for large distributed systems. Multiple viewpoints oriented requirements method (MVORM) is a new method for resolving these problems. This paper develops two generic formal frameworks of MVORM, framework based on refinement relation (FBRR) and framework based on implementation relation (FBIR). They are generic, because no assumptions are made about the development process or the formal description languages to be used. Three kinds of specification relations and three kinds of specification transformations are discussed over FBIR and FBRR. This paper also compares the equivalence between FBIR and FBRR. We point out that an equivalent FBIR can be found for any FBRR, but reverse transformation is not always possible. We think FBIR is better than FBRR on most cases.

A Certifiable Framework for Health Monitoring and Management

The scope of this paper is to provide an E2 Eperspective of health monitoring and management(HMM)and structural health mornitoring(SHM)as an integrated system element of an integrated system health monitoring and management(ISHM)system.The paper will address two main topics:(1)The importance of a diagnostics and prognostic requirements specification to develop an innovative health monitoring and management system;(2)The certification of a health monitoring and management system aiming at a maintenance credit as an integral part of the maintenance strategies.The development of a maintenance program which is based on combinations of different types of strategies(preventive,condition-based maintenance(CBM)and corrective maintenance…)for different subsystems or components and structures of complex systems like an aircraft to achieve the most optimized solution in terms of availability,cost and safety/certification is a real challenge.The maintenance strategy must satisfy the technical-risk and cost feasibility of the maintenance program.

Density-based trajectory outlier detection algorithm

With the development of global position system（GPS）,wireless technology and location aware services,it is possible to collect a large quantity of trajectory data.In the field of data mining for moving objects,the problem of anomaly detection is a hot topic.Based on the development of anomalous trajectory detection of moving objects,this paper introduces the classical trajectory outlier detection（TRAOD） algorithm,and then proposes a density-based trajectory outlier detection（DBTOD） algorithm,which compensates the disadvantages of the TRAOD algorithm that it is unable to detect anomalous defects when the trajectory is local and dense.The results of employing the proposed algorithm to Elk1993 and Deer1995 datasets are also presented,which show the effectiveness of the algorithm.

Testability Models for Object-Oriented Frameworks

Frameworks are time-tested highly reusable architectural skeleton structures. They are designed ‘abstract’ and ‘inco- mplete’ and are designed with predefined points of variability, known as hot spots, to be customized later at the time of framework reuse. Frameworks are reusable entities thus demand stricter and rigorous testing in comparison to one- time use application. The overall cost of framework development may be reduced by designing frameworks with high testability. This paper aims at discussing a few metric models for testability analysis of object-oriented frameworks in an attempt to having quantitative data on testability to be used to plan and monitor framework testing activities so that the framework testing effort and hence the overall framework development effort may be brought down.

大数据驱动的产品创新商务智能——基于SSP框架的分析

人工智能改变产品创新主体,引发产品创新战略与流程变革。本文依据大数据合作资产理论,从企业与用户互动的适应性创新视角,通过逻辑推演分析提出大数据驱动的产品创新商务智能主体—战略—流程框架,以探讨人工智能影响制造产品创新的新机制。研究表明:首先,人与人工智能双向卷入形成要素组合与知识积累的双向反馈式增强机制,促使创新主体发生结构性改变,形成产品创新战略与流程变革的新基础。其次,企业人工智能认知战略与竞争战略、组织文化、商业模式和生态系统的匹配,共同影响人工智能在创新流程中的一体化应用。最后,模糊前端的全流程扩散、需求—解决方案对的非线性迭代和智能制造的生成式自测构成大数据驱动的产品创新流程的新特征。研究表明,主体—战略—流程框架适合分析大数据驱动的产品创新商务智能的新机制,可为人工智能与产品创新的关系研究提供新视角。

基于Robot Framework的5G基站自动化测试系统的设计研究

设计了一种基于Robot Framework框架的5G基站自动化测试系统,结合Robot Framework框架特点介绍了自动化测试系统的总体架构,详细阐述了自动化测试系统的测试流程及被测系统、测试工具等相关测试库的设计方案。通过分析终端附着测试的自动化流程,对比手工测试与自动化测试的效率,验证了5G基站自动化测试系统设计的可行性和先进性,具有重要的工程使用价值。

基于成果导向教育理念的人工智能开发框架应用课程教学改革与实践

基于成果导向教育理念,对人工智能开发应用课程进行教学改革与实践,阐述了依据专业预期学习成果设计课程教学目标,再分解细化为课程预期学习成果和课程单元预期学习成果,制定课程教学设计方案,最后进行课程教学评价。在实施教学实践后,取得较好的教学效果。

数字平台生态系统治理——理论逻辑、行动框架与模式划分

数字平台生态系统的持续发展取决于其平台架构设计和治理规则的有效匹配。基于平台的治理规则和治理架构之间的动态镜像关系,从理论逻辑、行动框架和模式划分等方面对数字平台生态系统治理进行分析,结果发现:首先,数字平台生态系统治理是平台所有者基于治理架构设计创建规则来管理平台参与者的一系列活动组合。在治理过程中,治理主体主要面临着决策权集中与分散的平衡、平台边界开放与封闭的取舍两个关键问题;其次,治理主体、治理目标、治理架构和治理规则是数字平台生态系统治理的四个基本要素,四者相互作用共同组成实现数字平台生态系统可持续性的行动框架;最后,基于平台决策权分散还是集中,以及平台边界是封闭还是开放两个维度,数字平台生态系统治理可以划分为专断型治理、引导型治理、合约型治理和自由型治理四类模式。