基于属性相似性的Item-based协同过滤算法

通过分析传统Item-based协同过滤推荐中的稀疏性问题以及新项目的冷开始问题,提出了一个基于属性相似性的Item-based协同过滤算法。该算法利用项目属性的相似性来修正原始相似性计算,综合考虑项目属性和用户评价对推荐的影响,改进了传统相似性度量方法在评价数据稀疏和新项目推荐中测量结果不够准确的问题。

PEV:一种新的用于Item-Based协同过滤算法的相似性度量方法

在Item-Based协同过滤算法中,项目之间相似性的度量是整个算法的关键.通过分析传统的相似性度量方法在系统评分数据稀疏的情况下所存在的弊端,提出一种新的用于Item-Based协同过滤算法的相似性度量方法,该方法从邻近度、影响力、有用性三个方面综合考虑了用户评分对项目相似性的影响.实验结果表明,该方法能够有效地避免传统相似性度量方法所存在的问题,使得数据稀疏性对最终推荐结果的负面影响变小,在一定程度上提高系统的推荐精度.

基于组合加权评分的Item-based协同过滤算法

针对Item-based协同过滤算法中用户评分数据稀疏性严重影响推荐质量的问题,提出一种基于组合加权评分的Item-based协同过滤算法,以用户评分项并集作为用户相似性计算基础,并提出一种组合加权评分方法来对并集中的未评分项进行计算和填补,从而降低了数据稀疏性。实验结果表明该算法能有效提高推荐质量。

众创空间创客团队的“ITEM”融合模式与循环迭代——基于青创迭代创空间案例研究

以青创迭代创空间两个典型创客团队为案例研究对象,从创客团队的角度,研究其兑现创意、实现创业的过程和内在机理,提出了众创空间"ITEM"融合与循环迭代模型。研究发现:第一,创客团队的创新创业包括创意、技术、企业家精神、制造四个主环节且相互融合;第二,创客团队"ITEM"融合是一个循环迭代的过程。通过深入现实创客团队调研,总结出的融合模式和循环迭代模式对深入理论探讨和创客团队创新创业实践具有参考价值。

Ultra-processed food,obesity,and colon cancer:A systematic review and meta-analysis

BACKGROUND Recently,there has been a significant increase in the consumption of ultraprocessed foods worldwide.However,the association between the consumption of ultra-processed food,obesity,and the prevalence of colon cancer remains controversial.AIM To find out the association between the consumption of ultra-processed food,obesity,and the prevalence of colon cancer.METHODS A comprehensive systematic literature search of PubMed,Scopus,Web of Science,and Google Scholar for grey literature was done for articles published before 8th March 2023.The search was done to retrieve potential peer-reviewed articles that explored the association between the consumption of ultra-processed food,obesity,and the prevalence of colon cancer.RESULTS Of the 246 potential articles assessed,17 met the inclusion criteria.Meta-analysis results demonstrated that high consumption of ultra-processed food is associated with an increased risk of obesity[odds ratio(OR):1.65;95%CI:1.07-2.45;P<0.05].Consequently,there is a positive association between obesity and an increased risk of colon cancer(OR 1.48;95%CI:0.77-2.87;P>0.05).CONCLUSION Consuming ultra-processed foods increases the risk of obesity and colon cancer.

ITEM ToolKit软件在电力系统可靠性分析中的应用

美国ITEM软件公司推出的ITEM ToolKit可靠性分析软件,功能强大,操作方便,在介绍其基本功能的基础上,阐述了如何将其应用于电力系统可靠性分析中,该软件可以满足电力系统多种可靠性分析的需求。

自适应用户的Item-based协同过滤推荐算法

传统Item-based协同过滤算法计算两个条目间相似性时,将每个评分视为同等重要,忽略了共评用户(对两个条目共同评分的用户)与目标用户间的相似性对条目间相似性的影响。针对此问题,提出了一种自适应用户的Item-based协同过滤算法。该算法将共评用户与目标用户的相似性作为共评用户评分重要性的权重,以实现针对不同的目标用户,为目标条目选择不同的、适合目标用户的最近邻居集,从而提高推荐准确性。实验结果表明,提出的算法可以显著提高推荐系统的推荐质量。

ITEM软件在基于故障树诊断中的应用

在复杂的故障树中,手工定量分析故障树和求取最小割集比较的困难。利用可靠性工程软件ITEM对故障树进行建造和分析,快速地求取出了故障树的顶事件的发生概率,最小割集数及其发生的概率。从结果中得到各个底事件的重要度,分析出各个底事件在故障树中对顶事件发生贡献度大小和在故障树结构中的重要性,从而给出了系统设计的薄弱环节,为提高和保证系统的可靠性提供了有效的方法。并从给的最小割集量级上进行比较,为系统故障源搜索提供较好的测试步骤。

Optimization approach of background value and initial item for improving prediction precision of GM(1,1) model

A combination method of optimization of the back-ground value and optimization of the initial item is proposed. The sequences of the unbiased exponential distribution are simulated and predicted through the optimization of the background value in grey differential equations. The principle of the new information priority in the grey system theory and the rationality of the initial item in the original GM（1,1） model are ful y expressed through the improvement of the initial item in the proposed time response function. A numerical example is employed to il ustrate that the proposed method is able to simulate and predict sequences of raw data with the unbiased exponential distribution and has better simulation performance and prediction precision than the original GM（1,1） model relatively.

Frequent item sets mining from high-dimensional dataset based on a novel binary particle swarm optimization

A novel binary particle swarm optimization for frequent item sets mining from high-dimensional dataset(BPSO-HD) was proposed, where two improvements were joined. Firstly, the dimensionality reduction of initial particles was designed to ensure the reasonable initial fitness, and then, the dynamically dimensionality cutting of dataset was built to decrease the search space. Based on four high-dimensional datasets, BPSO-HD was compared with Apriori to test its reliability, and was compared with the ordinary BPSO and quantum swarm evolutionary(QSE) to prove its advantages. The experiments show that the results given by BPSO-HD is reliable and better than the results generated by BPSO and QSE.

The Application of Trapezoidal Fuzzy AHP on Evaluation Item Weight Calculation of Highway Network Programming Schemes

The fuzzy theory is invited in this paper to calculate weights of evaluation items, which is a very important stage in highway network evaluation. Highway network evaluation is a composite of various attributes that lack of pertinency and comparability, and their commonality is that they are more or less tainted with uncertainty, with different daily decision making problems of diverse intensity, the results can be misleading if the fuzziness of human decision-making is not taken into account. So we introduce fuzzy theory into the measurement of evaluating weights to overcome the issue and Analytic Hierarchy Process in scheme ranking. It is testified to be a more reliable way through the case study of Yangtze River Delta highway network evaluation.

Analysis of an Inventory System for Items with Stochastic Demand and Time Dependent Three-Parameter Weibull Deterioration Function

In recent times, mathematical models have been developed to describe various scenarios obtainable in the management of inventories. These models usually have as objective the minimizing of inventory costs. In this research work we propose a mathematical model of an inventory system with time-dependent three-parameter Weibull deterioration and a stochastic type demand in the form of a negative exponential distribution. Explicit expressions for the optimal values of the decision variables are obtained. Numerical examples are provided to illustrate the theoretical development.

STROBE Statement—Checklist of items that should be included in reports of case-control studies STROBE声明:病例对照研究报告写作清单①对文题、摘要、引言、方法的写作要求

Ⅰ.Title and abstract标题和摘要1(a)Indicate the study's design with acommonly used term in the title or the abstract

Reducing Item Exposure in Computerized Adaptive Testing Systems Using Automatic Item Generation

This paper studies the technics of reducing item exposure by utilizing automatic item generation methods. Known test item calibration method uses item parameter estimation with the statistical data, collected during examinees prior testing. Disadvantage of the mentioned item calibration method is the item exposure; when test items become familiar to the examinees. To reduce the item exposure, automatic item generation method is used, where item models are being constructed based on already calibrated test items without losing already estimated item parameters. A technic of item model extraction method from the already calibrated and therefore exposed test items described, which can be used by the test item development specialists to integrate automatic item generation principles with the existing testing applications.

Financial reporting of cash flow： Arbitrary items and management preferences

The international financial reporting standard for cash flow statement （IAS 7） provides options for the classification of certain cash flow items （arbitrary items）. Therefore, business firms may classify the arbitrary items using the option that would maximize their own interest. This reduces the comparability of financial statements amongst business firms. This study aims to investigate the factors explaining management preferences in the selection of financial reporting practices on the arbitrary cash flow items. It concludes that managers tend to magnify the CFO reported in order to maximize the shareholders＇ wealth, which in turn would maximize their compensation. Managers of business firms with a relatively smaller size of CFO tend to classify interest paid and dividends paid as non-CFO in order to magnify their CFO. They also tend to classify interest received as CFO in order to inflate their relatively smaller size of CFO up to expectation. Similarly, managers of business firms with a relative larger size of dividends paid would classify the dividends paid outside CFO.

An Ordering Policy for Deteriorating Items with Time-Dependent Quadratic Demand and Salvage Value under Permissible Delay in Payment

The article deals with an economic order quantity (EOQ) inventory model for deteriorating items in which the supplier provides the purchaser a permissible delay in payment. This is so when deterioration of units in the inventory is subject to constant deterioration rate, demand rate is quadratic function of time and salvage value is associated with the deteriorated units. Shortages in the system are not allowed to occur. A mathematical formulation is developed when the supplier offers a permissible delay period to the customers under two circumstances: 1) when delay period is less than the cycle of time;and 2) when delay period is greater than the cycle of time. The method is suitable for the items like state-of-the-art aircrafts, super computers, laptops, android mobiles, seasonal items and machines and their spare parts. A solution procedure algorithm is given for finding the optimal order quantity which minimizes the total cost of an inventory system. The article includes numerical examples to support the effectiveness of the developed model. Finally, sensitivity analysis on some parameters on optimal solution is provided.

Study on C-E Translation of Lexical Items with Chinese Characteristics in the Report on the 19th National Congress of the CPC

The 19th National Congress of the Communist Party of China is a meeting of great importance held during the decisivestage of building a moderately prosperous society in all respects.As a window to know about the latest changes of China,it is au-thoritative and of much value to study.As time goes by,there emerge more lexical items with Chinese characteristics.This articlestudies Chinese-English translation skills of lexical items with Chinese Characteristics in the Report on the 19th National Congressof the CPC.First,it classifies these lexical items into several kinds including those related with economy,politics,culture,peo-ple’s wellbeing and other lexical items,and then studies them respectively.

Synergic Effect of Reworking for Imperfect Quality Items with the Integration of Multi-Period Delay-in-Payment and Partial Backordering in Global Supply Chains

In intercontinental trade and economics goods are bought from a global supplier.On occasion,the expected lot may include a fraction of defective items.These imperfect items still have worth and can be sold to customers after repair.It is cost-effective and sustainable to rework such items in nearby repair workshops rather than return them.The reworked items can be returned from the workshop to the buyer when shortages are equal to the quantity of imperfect items.In the meantime,the supplier correspondingly deals a multi-period delay-in-payments strategy with purchaser.The entire profit has been maximized with paybacks for interim financing.This study aims to develop a synergic inventory model to get the most profit by making an allowance for reworking,multi-period delay-in-payments policy,and shortages.The findings of the proposed model augment inventory management performance by monitoring cycle time as well as fraction of phase with optimistic inventory for a supply chain.The results demonstrate that profit is smaller if the permitted period given by supplier to buyer is equal to or greater than the cycle time,and profit is greater if the permitted period is smaller than the cycle time.The algebraic method is engaged to make a closed system optimum solution.The mathematical experiment of this study is constructed to provide management insights and tangible practices.

Quantum search for unknown number of target items by hybridizing fixed-point method with trail-and-error method

For the unsorted database quantum search with the unknown fraction λ of target items, there are mainly two kinds of methods, i.e., fixed-point and trail-and-error.(i) In terms of the fixed-point method, Yoder et al. [Phys. Rev. Lett.113 210501(2014)] claimed that the quadratic speedup over classical algorithms has been achieved. However, in this paper, we point out that this is not the case, because the query complexity of Yoder’s algorithm is actually in O(1/λ01/2)rather than O(1/λ1/2), where λ0 is a known lower bound of λ.(ii) In terms of the trail-and-error method, currently the algorithm without randomness has to take more than 1 times queries or iterations than the algorithm with randomly selected parameters. For the above problems, we provide the first hybrid quantum search algorithm based on the fixed-point and trail-and-error methods, where the matched multiphase Grover operations are trialed multiple times and the number of iterations increases exponentially along with the number of trials. The upper bound of expected queries as well as the optimal parameters are derived. Compared with Yoder’s algorithm, the query complexity of our algorithm indeed achieves the optimal scaling in λ for quantum search, which reconfirms the practicality of the fixed-point method. In addition, our algorithm also does not contain randomness, and compared with the existing deterministic algorithm, the query complexity can be reduced by about 1/3. Our work provides a new idea for the research on fixed-point and trial-and-error quantum search.

An Improved Algorithm for Mining Correlation Item Pairs

Apriori algorithm is often used in traditional association rules mining,searching for the mode of higher frequency.Then the correlation rules are obtained by detected the correlation of the item sets,but this tends to ignore low-support high-correlation of association rules.In view of the above problems,some scholars put forward the positive correlation coefficient based on Phi correlation to avoid the embarrassment caused by Apriori algorithm.It can dig item sets with low-support but high-correlation.Although the algorithm has pruned the search space,it is not obvious that the performance of the running time based on the big data set is reduced,and the correlation pairs can be meaningless.This paper presents an improved mining algorithm with new association rules based on interestingness for correlation pairs,using an upper bound on interestingness of the supersets to prune the search space.It greatly reduces the running time,and filters the meaningless correlation pairs according to the constraints of the redundancy.Compared with the algorithm based on the Phi correlation coefficient,the new algorithm has been significantly improved in reducing the running time,the result has pruned the redundant correlation pairs.So it improves the mining efficiency and accuracy.