Attribute Reduction of Hybrid Decision Information Systems Based on Fuzzy Conditional Information Entropy

The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal values.In order to address the aforementioned issues,this paper delves into the study of attribute reduction withinHDISs.First of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute values.The newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute values.Then,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute values.Furthermore,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy attributes.It effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information systems.Finally,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is presented.The experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction algorithms.The comprehensive analysis of these research results clearly indicates that our algorithm is highly effective in managing the intricate uncertainties inherent in hybrid data.

Boron-doped high-entropy oxide toward high-rate and long-cycle layered cathodes for wide-temperature sodium-ion batteries

03-type layered metal oxides hold great promise for sodium-ion batteries cathodes owing to their energy density advantage.However,the severe irreversible phase transition and sluggish Na^(+)diffusion kinetics pose significant challenges to achieve high-performance layered cathodes.Herein,a boron-doped03-type high entropy oxide Na(Fe_(0.2)Co_(0.15)Cu_(0.05)Ni_(0.2)Mn_(0.2)Ti_(0.2))B_(0.02)O_(2)(NFCCNMT-B_(0.02))is designed and the covalent B-O bonds with high entropy configuration ensure a robust layered structure.The obtained cathode NFCCNMT-B_(0.02)exhibits impressive cycling performance(capacity retention of 95%and 82%after100 cycles and 300 cycles at 1 and 10 C,respectively)and outstanding rate capability(capacity of 83 mAh g^(-1)at 10 C).Furthermore,the NFCCNMT-B_(0.02)demonstrates a superior wide-temperature performance,maintaining the same capacity level(113,4 mAh g^(-1)@-20℃,121 mAh g^(-1)@25℃,and 119 mAh g^(-1)@60℃)and superior cycle stability(90%capacity retention after 100 cycles at 1 C at-20℃).The high-entropy configuration design with boron doping strategy contributes to the excellent sodium-ion storage performance.The high-entropy configuration design effectively suppresses irreversible phase transitions accompanied by small volume changes(ΔV=0.65 A3).B ions doping expands the Na layer distance and enlarges the P3 phase region,thereby enhancing Na^(+)diffusion kinetics.This work offers valuable insights into design of high-performance layered cathodes for sodium-ion batteries operating across a wide temperature.

Microstructure and Properties of AlCoCrFeNiTi High-Entropy Alloy Coatings Prepared by Laser Cladding

21-4N(5Cr21Mn9Ni4N)is extensively employed in the production of engine valves,operating under severe conditions.Apart from withstanding high-temperature gas corrosion,it must also endure the impact of cylinder explosion pressure.The predominant failure mode of 21-4N valves is abrasive wear.Surface coatings serve as an effective approach to prevent such failures.In this investigation,Laser cladding technology was utilized to fabricate AlCoCrFeNiTi high entropy alloy coatings onto the surfaces of 21-4N valves.According to the findings,the cladding zone has a normal dendritic microstructure,a good substrate-to-cladding layer interaction,and no obvious flaws.In terms of hardness,the cladding demonstrates an average hardness of 620 HV.The hardness has increased by 140%compared to the substrate.The average hardness of the cladding remains at approximately 520 HV even at elevated temperatures.Regarding frictional wear performance,between 400℃and 800℃,the cladding layer exhibits an average friction coefficient of 0.4,with the primary wear mechanisms being abrasive wear,adhesive wear,and a minor degree of plastic deformation.

Characterization of Small-Scale Farmers and Assessment of Their Access to Crop Production Information in Selected Counties of Kenya

Small-scale farming accounts for 78% of total agricultural production in Kenya and contributes to 23.5% of the country’s GDP. Their crop production activities are mostly rainfed subsistence with any surplus being sold to bring in some income. Timely decisions on farm practices such as farm preparation and planting are critical determinants of the seasonal outcomes. In Kenya, most small-scale farmers have no reliable source of information that would help them make timely and accurate decisions. County governments have extension officers who are mandated with giving farmers advisory services to farmers but they are not able to reach most farmers due to facilitation constraints. The mode and format of sharing information is also critical since it’s important to ensure that it’s timely, well-understood and usable. This study sought to assess access to geospatial derived and other crop production information by farmers in four selected counties of Kenya. Specific objectives were to determine the profile of small-scale farmers in terms of age, education and farm size;to determine the type of information that is made available to them by County and Sub-County extension officers including the format and mode of provision;and to determine if the information provided was useful in terms of accuracy, timeliness and adequacy. The results indicated that over 80% of the farmers were over 35 years of age and over 56% were male. Majority had attained primary education (34%) or secondary education (29%) and most farmers in all the counties grew maize (71%). Notably, fellow farmers were a source of information (71%) with the frequency of sharing information being mostly seasonal (37%) and when information was available (43%). Over 66% of interviewed farmers indicating that they faced challenges while using provided information. The results from the study are insightful and helpful in determining effective ways of providing farmers with useful information to ensure maximum benefits.

Entropy of deterministic trajectory via trajectories ensemble

We present a formulation of the single-trajectory entropy using the trajectories ensemble. The single-trajectory entropy is affected by its surrounding trajectories via the distribution function. The single-trajectory entropies are studied in two typical potentials, i.e., harmonic potential and double-well potential, and in viscous environment by interacting trajectory method. The results of the trajectory methods are in agreement well with the numerical methods(Monte Carlo simulation and difference equation). The single-trajectory entropies increasing(decreasing) could be caused by absorption(emission) heat from(to) the thermal environment. Also, some interesting trajectories, which correspond to the rare evens in the processes, are demonstrated.

ESTIMATION OF AVERAGE DIFFERENTIAL ENTROPY FOR A STATIONARY ERGODIC SPACE-TIME RANDOM FIELD ON A BOUNDED AREA

In this paper,we mainly discuss a discrete estimation of the average differential entropy for a continuous time-stationary ergodic space-time random field.By estimating the probability value of a time-stationary random field in a small range,we give an entropy estimation and obtain the average entropy estimation formula in a certain bounded space region.It can be proven that the estimation of the average differential entropy converges to the theoretical value with a probability of 1.In addition,we also conducted numerical experiments for different parameters to verify the convergence result obtained in the theoretical proofs.

Chemical Scissors Tailored Nano‑Tellurium with High‑Entropy Morphology for Efficient Foam‑Hydrogel‑Based Solar Photothermal Evaporators

The development of tellurium(Te)-based semiconductor nanomaterials for efficient light-to-heat conversion may offer an effective means of harvesting sunlight to address global energy concerns.However,the nanosized Te(nano-Te)materials reported to date suffer from a series of drawbacks,including limited light absorption and a lack of surface structures.Herein,we report the preparation of nano-Te by electrochemical exfoliation using an electrolyzable room-temperature ionic liquid.Anions,cations,and their corresponding electrolytic products acting as chemical scissors can precisely intercalate and functionalize bulk Te.The resulting nano-Te has high morphological entropy,rich surface functional groups,and broad light absorption.We also constructed foam hydrogels based on poly(vinyl alcohol)/nano-Te,which achieved an evaporation rate and energy efficiency of 4.11 kg m^(−2)h^(−1)and 128%,respectively,under 1 sun irradiation.Furthermore,the evaporation rate was maintained in the range 2.5-3.0 kg m^(−2)h^(−1)outdoors under 0.5-1.0 sun,providing highly efficient evaporation under low light conditions.

Properties of Self-recoverable Mechanoluminescence Phosphor Ca_(5)Ga_(6)O_(14)∶Eu^(3+) and Its Information Encryption Application

A novel self-recoverable mechanoluminescent phosphor Ca_(5)Ga_(6)O_(14)∶Eu^(3+) was developed by the high-tem-perature solid-state reaction method,and its luminescence properties were investigated.Ca_(5)Ga_(6)O_(14)∶Eu^(3+)can produce red mechanoluminescence,and importantly,it shows good repeatability.The mechanoluminescence of Ca_(5)Ga_(6)O_(14)∶Eu^(3+) results from the piezoelectric field generated inside the material under stress,rather than the charge carriers stored in the traps,which can be confirmed by the multiple cycles of mechanoluminescence tests and heat treatment tests.The mechanoluminescence color can be turned from red to green by co-doping varied concentrations of Tb^(3+),which may be meaningful for encrypted letter writing.The encryption scheme for secure communication was devised by harnessing mechanoluminescence patterns in diverse shapes and ASCII codes,which shows good encryption performance.The results suggest that the mechanoluminescence phosphor Ca_(5)Ga_(6)O_(14)∶Eu^(3+),Tb^(3+)may be applied to the optical information encryption.

A critical review on solid-state welding of high entropy alloys-processing,microstructural characteristics and mechanical properties of joints

The high entropy alloys(HEAs)are the newly developed high-performance materials that have gained significant importance in defence,nuclear and aerospace sector due to their superior mechanical properties,heat resistance,high temperature strength and corrosion resistance.These alloys are manufactured by the equal mixing or larger proportions of five or more alloying elements.HEAs exhibit superior mechanical performance compared to traditional engineering alloys because of the extensive alloying composition and higher entropy of mixing.Solid state welding(SSW)techniques such as friction stir welding(FSW),rotary friction welding(RFW),diffusion bonding(DB)and explosive welding(EW)have been efficiently deployed for improving the microstructural integrity and mechanical properties of welded HEA joints.The HEA interlayers revealed greater potential in supressing the formation of deleterious intermetallic phases and maximizing the mechanical properties of HEAs joints.The similar and dissimilar joining of HEAs has been manifested to be viable for HEA systems which further expands their industrial applications.Thus,the main objective of this review paper is to present a critical review of current state of research,challenges and opportunities and main directions in SSW of HEAs mainly CoCrFeNiMn and Al_xCoCrFeNi alloys.The state of the art of problems,progress and future outlook in SSW of HEAs are critically reviewed by considering the formation of phases,microstructural evolution and mechanical properties of HEAs joints.

Using Cross Entropy as a Performance Metric for Quantifying Uncertainty in DNN Image Classifiers: An Application to Classification of Lung Cancer on CT Images

Cross entropy is a measure in machine learning and deep learning that assesses the difference between predicted and actual probability distributions. In this study, we propose cross entropy as a performance evaluation metric for image classifier models and apply it to the CT image classification of lung cancer. A convolutional neural network is employed as the deep neural network (DNN) image classifier, with the residual network (ResNet) 50 chosen as the DNN archi-tecture. The image data used comprise a lung CT image set. Two classification models are built from datasets with varying amounts of data, and lung cancer is categorized into four classes using 10-fold cross-validation. Furthermore, we employ t-distributed stochastic neighbor embedding to visually explain the data distribution after classification. Experimental results demonstrate that cross en-tropy is a highly useful metric for evaluating the reliability of image classifier models. It is noted that for a more comprehensive evaluation of model perfor-mance, combining with other evaluation metrics is considered essential. .

The Impact of Health Information Technology on Hospital Performance: A Systematic Integrative Literature Review

Objective: To review, categorise, and synthesise findings from literature on health information technology (HIT) functionalities, HIT use, and the impact of HIT on hospital performance. Materials and Methods: We conducted a systematic integrative literature review based on a compre-hensive database search. To organise, categorise and synthesise the ex-isting literature, we adopted the affordance actualization theory. To align the literature with our research framework, we used four categories: 1) the functionalities of HIT and how these functionalities are measured;2) use and immediate outcomes of HIT functionalities;3) different perfor-mance indicators and how HIT functionalities affect them;and 4) what hospital characteristics influence the outcome of hospital performance. Results: Fifty-two studies were included. We identified four types of HIT. Only ten studies (19.2%) define the use of HIT by explicitly meas-uring the use rate of HIT. We identified five dimensions of hospital per-formance indicators. Every dimension showed mixed results;however, in general, HIT has a positive impact on mortality and patient readmis-sions. We found several hospital characteristics that may affect the rela-tionship between HIT and hospital-level outcomes. Discussion: Further efforts should focus on embedded research on HIT functionalities, use and effects of HIT implementations with more performance indicators and adjusted for hospital characteristics. Conclusion: The proposed framework could help hospitals and researchers make decisions regard-ing the functionalities, use and effects of HIT implementation in hospi-tals. Given our research outcomes, we suggest future research opportuni-ties to improve understanding of how HIT affects hospital performance. .

Efficient slope reliability analysis under soil spatial variability using maximum entropy distribution with fractional moments

Spatial variability of soil properties imposes a challenge for practical analysis and design in geotechnical engineering.The latter is particularly true for slope stability assessment,where the effects of uncertainty are synthesized in the so-called probability of failure.This probability quantifies the reliability of a slope and its numerical calculation is usually quite involved from a numerical viewpoint.In view of this issue,this paper proposes an approach for failure probability assessment based on Latinized partially stratified sampling and maximum entropy distribution with fractional moments.The spatial variability of geotechnical properties is represented by means of random fields and the Karhunen-Loève expansion.Then,failure probabilities are estimated employing maximum entropy distribution with fractional moments.The application of the proposed approach is examined with two examples:a case study of an undrained slope and a case study of a slope with cross-correlated random fields of strength parameters under a drained slope.The results show that the proposed approach has excellent accuracy and high efficiency,and it can be applied straightforwardly to similar geotechnical engineering problems.

The Value of Modern Information Technology in Nursing Emergencies

In first aid, traditional information interchange has numerous shortcomings. For example, delayed information and disorganized departmental communication cause patients to miss out on critical rescue time. Information technology is becoming more and more mature, and as a result, its use across numerous industries is now standard. China is still in the early stages of developing its integration of emergency medical services with modern information technology;despite our progress, there are still numerous obstacles and constraints to overcome. Our goal is to integrate information technology into every aspect of emergency patient care, offering robust assistance for both patient rescue and the efforts of medical personnel. Information may be communicated in a fast, multiple, and effective manner by utilizing modern information technology. This study aims to examine the current state of this field’s development, current issues, and the field’s future course of development.

Review on uncertainty analysis and information fusion diagnosis of aircraft control system

In the aircraft control system,sensor networks are used to sample the attitude and environmental data.As a result of the external and internal factors(e.g.,environmental and task complexity,inaccurate sensing and complex structure),the aircraft control system contains several uncertainties,such as imprecision,incompleteness,redundancy and randomness.The information fusion technology is usually used to solve the uncertainty issue,thus improving the sampled data reliability,which can further effectively increase the performance of the fault diagnosis decision-making in the aircraft control system.In this work,we first analyze the uncertainties in the aircraft control system,and also compare different uncertainty quantitative methods.Since the information fusion can eliminate the effects of the uncertainties,it is widely used in the fault diagnosis.Thus,this paper summarizes the recent work in this aera.Furthermore,we analyze the application of information fusion methods in the fault diagnosis of the aircraft control system.Finally,this work identifies existing problems in the use of information fusion for diagnosis and outlines future trends.

Heterogeneous information fusion recognition method based on belief rule structure

To solve the problem that the existing situation awareness research focuses on multi-sensor data fusion,but the expert knowledge is not fully utilized,a heterogeneous informa-tion fusion recognition method based on belief rule structure is proposed.By defining the continuous probabilistic hesitation fuzzy linguistic term sets(CPHFLTS)and establishing CPHFLTS distance measure,the belief rule base of the relationship between feature space and category space is constructed through information integration,and the evidence reasoning of the input samples is carried out.The experimental results show that the proposed method can make full use of sensor data and expert knowledge for recognition.Compared with the other methods,the proposed method has a higher correct recognition rate under different noise levels.

Reflections and Improvements on China’s Asset-Backed Securities Information Disclosure System

Asset-backed securities are developed through complex processes such as asset restructuring and credit enhancement.Therefore,the information asymmetry between issuers and investors is greater compared to traditional securities,which imposes higher requirements on information disclosure for asset-backed securities.Asset-backed securities have characteristics such as diversified disclosers,differentiated disclosure content,and specialized risk factors.China has already formulated a series of rules and regulations regarding information disclosure of asset-backed securities.It is imperative to develop specialized laws and regulations for asset-backed securities,encompass original equity holders and credit enhancement agencies as information disclosers,incorporate information such as underlying asset details,cash flow projections,and credit ratings and enhancements into the disclosure content,and improve the legal liability rules to effectively address false disclosures.

Database Search Behaviors: Insight from a Survey of Information Retrieval Practices

This study examines the database search behaviors of individuals, focusing on gender differences and the impact of planning habits on information retrieval. Data were collected from a survey of 198 respondents, categorized by their discipline, schooling background, internet usage, and information retrieval preferences. Key findings indicate that females are more likely to plan their searches in advance and prefer structured methods of information retrieval, such as using library portals and leading university websites. Males, however, tend to use web search engines and self-archiving methods more frequently. This analysis provides valuable insights for educational institutions and libraries to optimize their resources and services based on user behavior patterns.

RAIENet:End-to-End Multitasking Road All Information Extractor

Road lanes and markings are the bases for autonomous driving environment perception.In this paper,we propose an end-to-end multi-task network,Road All Information Extractor named RAIENet,which aims to extract the full information of the road surface including road lanes,road markings and their correspondences.Based on the prior knowledge of pavement information,we explore and use the deep progressive relationship between lane segmentation and pavement mark-ing detection.Then,different attention mechanisms are adapted for different tasks.A lane detection accuracy of 0.807 F1-score and a ground marking accuracy of 0.971 mean average precision at intersection over union(IOU)threshold 0.5 were achieved on the newly labeled see more on road plus(CeyMo+)dataset.Of course,we also validated it on two well-known datasets Berkeley Deep-Drive 100K(BDD100K)and CULane.In addition,a post-processing method for generating bird’s eye view lane(BEVLane)using lidar point cloud information is proposed,which is used for the construction of high-definition maps and subsequent decision-making planning.The code and data are available at https://github.com/mayberpf/RAIEnet.

Orbit Weighting Scheme in the Context of Vector Space Information Retrieval

This study introduces the Orbit Weighting Scheme(OWS),a novel approach aimed at enhancing the precision and efficiency of Vector Space information retrieval(IR)models,which have traditionally relied on weighting schemes like tf-idf and BM25.These conventional methods often struggle with accurately capturing document relevance,leading to inefficiencies in both retrieval performance and index size management.OWS proposes a dynamic weighting mechanism that evaluates the significance of terms based on their orbital position within the vector space,emphasizing term relationships and distribution patterns overlooked by existing models.Our research focuses on evaluating OWS’s impact on model accuracy using Information Retrieval metrics like Recall,Precision,InterpolatedAverage Precision(IAP),andMeanAverage Precision(MAP).Additionally,we assessOWS’s effectiveness in reducing the inverted index size,crucial for model efficiency.We compare OWS-based retrieval models against others using different schemes,including tf-idf variations and BM25Delta.Results reveal OWS’s superiority,achieving a 54%Recall and 81%MAP,and a notable 38%reduction in the inverted index size.This highlights OWS’s potential in optimizing retrieval processes and underscores the need for further research in this underrepresented area to fully leverage OWS’s capabilities in information retrieval methodologies.

Exploring International Media and Information Literacy Initiatives: Insights From DW Akademie’s MIL Model

Media and Information Literacy(MIL)is one of the most important topics in today’s mediatized world.Under the leadership of United Nations Educational,Scientific and Cultural Organization(UNESCO),many international organizations in the world,as foreign donors,annually announce many projects and grants for the promotion and development of the field of MIL in the countries of the world.One of the main actors of this movement is DW Akademie with different media and MIL projects several countries of the world.This research paper delves into the role of DW Akademie’s MIL model in shaping a media-savvy generation.The study explores the theoretical underpinnings and practical applications of Deutsche Welle(DW)Akademie’s MIL model,analysing its effectiveness in fostering media literacy skills.The research employs a multi-faceted approach,incorporating case studies to assess the model’s impact across diverse demographics.The paper also considers the model’s alignment with global educational policies and proposes recommendations for its integration into broader frameworks.By investigating DW Akademie’s MIL model,this research contributes to the ongoing discourse on media literacy education,providing valuable insights for educators,policymakers,and researchers.The findings offer a nuanced understanding of the model’s position in cultivating a media-savvy generation poised to navigate the complexities of the information age.