Unbalanced Scale Research Articles

Evaluation of the efficiency of agrarian institutions of higher education of Ukraine using the DEA method

The relevance of the study is determined by the need to perfect the evaluation of the efficiency of scientific and educational activities of the country’s higher education institutions and determine the causes of inefficiency. The purpose of this study was to improve the evaluation of the efficiency of scientific publication activities of agrarian higher education institutions of Ukraine using the Data Envelopment Analysis method. The study was conducted according to the general heuristic method, the authors also employed mathematical and statistical methods of processing and analysis of input and output data, computer methods for the implementation of research tasks and abstract-logical methods for determining the degree of relevance, formulation of conclusions. The study substantiated the feasibility of using the non-parametric method of Data Envelopment Analysis to evaluate the efficiency of the scientific and educational activities of higher education institutions, as well as the feasibility of using Voluntary Retirement Services and Compulsory Retirement Service models, which are input-oriented, to evaluate the technical, purely technical, large-scale efficiency of scientific publication activity. Based on statistical information for 2020-2021, the technical, purely technical, large-scale efficiency of the scientific publication activity of 38 agricultural institutions of higher education of Ukraine were evaluated using the Data Envelopment Analysis method. According to the results of calculations, 18% of the educational institutions under study have the maximum value of technical and large-scale efficiency. The average technical efficiency is 0.6, the average pure technical efficiency – 0.7, and the average scale efficiency – 0.85. The analysis of the estimated values of relative efficiency allowed identifying the reasons for the inefficiency of each higher education institution under study, including suboptimal use of educational resources and an unbalanced scale of activity. Based on the study results, a rating of agrarian institutions of higher education in Ukraine in terms of the efficiency of scientific publication activities was compiled, which can be used as an addition to conventional ratings for analysing scientific and educational activities. The results of this study can be used to rank higher educational institutions by efficiency, to find the reasons for their ineffective activities

Working intentions of medical students in response to healthcare workplace violence and descending resources reform in China

BackgroundIn order to curb healthcare workplace violence (WPV) and better allocate healthcare resources, China launched the descending resources reform in 2013 and tightened the anti-violence legal environment simultaneously. Medical students are expected to reconsider their working intentions of entering the medical market (inter-market effect) and choosing high- or low-level hospitals (intra-market effect) in response to the evolving WPV. The goal of this study was to explore the link between the perceived WPV incidence and medical students’ willingness to practice medicine in the context of China’s descending resources reform.MethodMedical students were selected with cluster sampling from 8 medical colleges in Zhejiang Province, China, and 1497 valid questionnaires were collected by using a five-point unbalanced scale, to perform cross-sectional empirical research using the ordered logit model (OLM).ResultsThe perceived WPV incidence negatively correlate with the willingness of medical students to practice medicine but positively correlate with their willingness to practice in low-level hospitals, indicating the existence of inter- and intra-market effects. The anti-violence legal environment has no direct link with working intention but contributes to the perceived decline in the incidence of violence. Descending resources reform has simultaneous opposite effects on medical students, with the coexistence of prudent motives driven by reform costs and optimistic expectations of sharing external benefits.ConclusionsSafety needs and risk aversion motive play an important role in medical students’ career choice when facing severe WPV. Tightening of the anti-violence legal environment and the descending resources reform could drive medical students to low-level hospitals.

A fault diagnosis method for underwater thruster based on RFR-SVM

A fault diagnosis method for underwater thruster based on Random Forest Regression (RFR) and Support Vector Machine (SVM) is proposed in this paper. Aiming at the problem of insufficient fault diagnosis accuracy caused by the extremely unbalanced scale of normal samples and fault samples, a data argumentation method of fault samples based on RFR is proposed. Considering the over-fitting phenomenon of machine learning in the case of small samples, tsfresh package, and kernel principal component analysis (KPCA) are used to extract features from thruster time series data, and then the SVM is used to train the thruster fault diagnosis model. Finally, the effectiveness of the proposed method is verified by experiment in a pool environment.

Kernel principal components based cascade forest towards disease identification with human microbiota

BackgroundNumerous pieces of clinical evidence have shown that many phenotypic traits of human disease are related to their gut microbiome, i.e., inflammation, obesity, HIV, and diabetes. Through supervised classification, it is feasible to determine the human disease states by revealing the intestinal microbiota compositional information. However, the abundance matrix of microbiome data is so sparse, an interpretable deep model is crucial to further represent and mine the data for expansion, such as the deep forest model. What’s more, overfitting can still exist in the original deep forest model when dealing with such “large p, small n” biology data. Feature reduction is considered to improve the ensemble forest model especially towards the disease identification in the human microbiota.MethodsIn this work, we propose the kernel principal components based cascade forest method, so-called KPCCF, to classify the disease states of patients by using taxonomic profiles of the microbiome at the family level. In detail, the kernel principal components analysis method is first used to reduce the original dimension of human microbiota datasets. Besides, the processed data is fed into the cascade forest to preliminarily discriminate against the disease state of the samples.ResultsThe proposed KPCCF algorithm can represent the small-scale and high-dimension human microbiota datasets with the sparse feature matrix. Systematic comparison experiments demonstrate that our method consistently outperforms the state-of-the-art methods with the comparative study on 4 datasets.ConclusionDespite sharing some common characteristics, a one-size-fits-all solution does not exist in any space. The traditional depth model has limitations in the biological application of the unbalanced scale between small samples and high dimensions. KPCCF distinguishes from the standard deep forest model for its excellent performance in the microbiota field. Additionally, compared to other dimensionality reduction methods, the kernel principal components analysis method is more suitable for microbiota datasets.

EAWNet: An Edge Attention‐Wise Objector for Real‐Time Visual Internet of Things

With the upgrading of the high‐performance image processing platform and visual internet of things sensors, VIOT is widely used in intelligent transportation, autopilot, military reconnaissance, public safety, and other fields. However, the outdoor visual internet of things system is very sensitive to the weather and unbalanced scale of latent object. The performance of supervised learning is often limited by the disturbance of abnormal data. It is difficult to collect all classes from limited historical instances. Therefore, in terms of the anomaly detection images, fast and accurate artificial intelligence‐based object detection technology has become a research hot spot in the field of intelligent vision internet of things. To this end, we propose an efficient and accurate deep learning framework for real‐time and dense object detection in VIOT named the Edge Attention‐wise Convolutional Neural Network (EAWNet) with three main features. First, it can identify remote aerial and daily scenery objects fast and accurately in terms of an unbalanced category. Second, edge prior and rotated anchor are adopted to enhance the efficiency of detection in edge computing internet. Third, our EAWNet network uses an edge sensing object structure, makes full use of an attention mechanism to dynamically screen different kinds of objects, and performs target recognition on multiple scales. The edge recovery effect and target detection performance for long‐distance aerial objects were significantly improved. We explore the efficiency of various architectures and fine tune the training process using various backbone and data enhancement strategies to increase the variety of the training data and overcome the size limitation of input images. Extensive experiments and comprehensive evaluation on COCO and large‐scale DOTA datasets proved the effectiveness of this framework that achieved the most advanced performance in real‐time VIOT object detection.

Fuzzified synthetic extent weighted average for appraisal of design concepts

Decision-making models such as Analytical Hierarchy Process (AHP), Weighted Decision Matrix (WDM), Pugh Matrix and the likes have been able to assist in the decision process considering the objectives of each evaluation criteria in the alternatives. However, these models need to consider the qualitative and subjective nature of the design features. In order to reduce the unbalanced scale of judgment and the uncertainty associated with the crisp information in the decision process, fuzzified and hybridized models are necessary. Existing hybridized decision models applied for machine concept selection deploy several design features and sub-features at the conceptual product design, which thus make the decision making process to be tedious. In light of this, this article presents a hybridized decision-making model, which harness the comparative strength and computational integrity of fuzzy pairwise comparison matrix and fuzzy weighted average, to numerically analyse a reasonable amount of machine design features, thereby making decision making process less tedious. Design for reconfigurability and functionality which are peculiar to reconfigurable machines was introduced using a Reconfigurable Assembly Fixture (RAF) as a case study while other design features related to design concept evaluation were grouped under design for X. The result of the hybridized model shows that, concept three is the optimal design from four sets of designs. This is compared to previous publication using the RAF design concepts with different design features and sub-features. The comparison indicates that there is a close range in the final values of the designs due to the inclusion of several sub-features in the decision process which were not used in the previous study.

Distance‐based intuitionistic multiplicative multiple criteria decision‐making methods for healthcare management in West China Hospital

AbstractIntuitionistic multiplicative sets use an asymmetric, unbalanced scale to express information from positive, negative, and indeterminate information. They have been found capable of comprehensively and objectively representing a person's intuitive understanding and hence have attracted much attention. Distance techniques are widely used to measure the degree to which arguments deviate from one another. Several fuzzy set extensions have been developed, but little research has been conducted on measures of distance between intuitionistic multiplicative sets. In this paper, we start by presenting a variety of measures of the distance between intuitionistic multiplicative sets, including Hausdorff distance measures, weighted distance measures, ordered weighted distance measures, and continuous weighted distance measures. We then develop a distance‐based intuitionistic multiplicative‐technique for order preference by similarity to ideal solution method and a distance‐based intuitionistic multiplicative‐Vlsekriterijumska Optimizacija I Kompromisno Resenje method for handling multiple criteria decision‐making problems with intuitionistic multiplicative evaluation information. To demonstrate the practical application of these distance measures and the proposed methods, we provide a case study of hospital management of inpatient admission. The paper ends with comparative analyses of the two methods and some concluding remarks.

Derivatives and differentials for multiplicative intuitionistic fuzzy information

By using the unsymmetrical scale instead of the symmetrical scale, the multiplicative intuitionistic fuzzy sets (MIFSs) reflect our intuition more objectively. Each element in a MIFS is expressed by an ordered pair which is called a multiplicative intuitionistic fuzzy number (MIFN) and is based on the unbalanced scale (i.e., Saaty’s 1-9 scale). In order to describe the derivatives and differentials for multiplicative intuitionistic fuzzy information more comprehensively, in this paper, we firstly propose two new basic operational laws for MIFNs, which are the subtraction law and the division law. Secondly, we describe the change values of MIFNs when considering them as variables, classify these change values based on the basic operational laws for MIFNs, and depict the convergences of sequences of MIFNs by the subtraction and division laws. Finally, we focus on the multiplicative intuitionistic fuzzy functions and derive some basic results related to their continuities, derivatives and differentials, and also give their application in selecting the configuration of a computer.

Application of Hybrid VIKOR Model in Selection of Maintenance Strategy

This paper focuses on the use of Fuzzy Analytic Hierarchy Process (FAHP) and VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian (VIKOR) to select an optimum maintenance strategy for a textile industry. In the proposed methodology, first the weight of each criterion is calculated by using improved AHP with fuzzy set theory to overcome the problems of unbalanced scale of judgments, uncertainty and imprecision in the pair-wise comparison process and then the VIKOR method is applied to compensate the imprecise ranking of the AHP in the selection of maintenance strategy. The real case study is conducted for a textile industry to illustrate the utilization of the proposed model for the maintenance strategy selection problem. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied to make sure that the result of the proposed model can be acceptable. A sensitivity analysis is also conducted to show the validity of the proposed model. The paper gives an insight into multi criteria decision-making (MCDM) techniques to select an optimum maintenance strategy for a process industry using a case study.

Application of Hybrid VIKOR Model in Selection of Maintenance Strategy

This paper focuses on the use of Fuzzy Analytic Hierarchy Process (FAHP) and VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian (VIKOR) to select an optimum maintenance strategy for a textile industry. In the proposed methodology, first the weight of each criterion is calculated by using improved AHP with fuzzy set theory to overcome the problems of unbalanced scale of judgments, uncertainty and imprecision in the pair-wise comparison process and then the VIKOR method is applied to compensate the imprecise ranking of the AHP in the selection of maintenance strategy. The real case study is conducted for a textile industry to illustrate the utilization of the proposed model for the maintenance strategy selection problem. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied to make sure that the result of the proposed model can be acceptable. A sensitivity analysis is also conducted to show the validity of the proposed model. The paper gives an insight into multi criteria decision-making (MCDM) techniques to select an optimum maintenance strategy for a process industry using a case study.Request access from your librarian to read this article's full text.

Maintenance Strategy Evaluation Using ANP and Goal Programming

An optimal maintenance strategy mix is necessary for increasing availability and reliability levels of production facilities without significantly increasing operational costs. The selection of maintenance strategies is a typical Multiple Criteria Decision-Making (MCDM) problem with conflicting goals. Consideration of interdependence among the criteria and alternative policies for maintenance strategy provides valuable cost savings and greater benefits for any hybrid flow systems. For any decision maker, it is convenient to prioritize the criteria of MCDM problems and goals of goal programming problems in fuzzy terms. This paper presents an integrated approach for maintenance policy selection, using fuzzy Analytic Network Process (ANP) within a Goal Programming, based on fuzzy preemptive priority where goal hierarchies are specified in different levels of fuzzy importance. To overcome the criticism of inconsistency, unbalanced scale of judgments and uncertainty in the pair-wise comparison process, criteria weights are determined using modified fuzzy LLSM method.

A Hybrid Multiple Criteria Decision Making Technique for Prioritizing Equipments

Prioritization of equipment is an important factor for decision making to optimize maintenance management in Reliability Centered Maintenance (RCM). Many factors must be considered as part of the prioritization of equipment for maintenance activities. Consequently, evaluation procedures involve several objectives and it is often necessary to compromise among conflicting tangible and intangible factors. Multiple Criteria Decision Making (MCDM) is a useful approach to solve these problems. In this study, a hybrid model is developed for prioritizing the equipment in hybrid flow systems. The first stage involves identifying the criteria. The second stage is prioritizing the different criteria using fuzzy Analytical Network Process (ANP), in which the weight of each criterion is calculated using modified fuzzy Logarithmic Least Square Method (LLSM) to overcome the criticism of inconsistency, unbalanced scale of judgments, uncertainty and imprecision in the pair-wise comparison process, then finally ranking of equipment using fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS).

Selection of maintenance policy for textile industry using hybrid multi‐criteria decision making approach

PurposeThe purpose of this paper is to focus on the use of analytic hierarchy process (AHP) under fuzzy environment and technique for order preference by similarity to ideal solution (TOPSIS) to select an optimum maintenance strategy for a textile industry.Design/methodology/approachFirst by using improved AHP with fuzzy set theory, the weight of each criterion is calculated to overcome the criticism of unbalanced scale of judgments, uncertainty, and imprecision in the pair‐wise comparison process. Then this paper introduces a model that integrates improved fuzzy AHP with TOPSIS algorithm to support maintenance strategy selection decisions.FindingsAn efficient pair‐wise comparison process and ranking of alternatives can be achieved for maintenance strategy selection through the integration of AHP with fuzzy set theory and TOPSIS.Originality/valueThe paper points out a new insight of multi‐criteria decision making techniques to select optimum maintenance policy for a process industry with the use of a case study.

Byron's Copy of Childe Harold IV: Emendations and Annotations

My attention was drawn to the following matter by a correspondence that arose in early January 1873 in The Times on the subject of Byron's grammatical solecisms. This had been prompted by a review of Browning's Prince Hohenstiel-Schwangau, Saviour of Society (1871) and Fifine at the Fair (1872) in The Times for Thursday 2 January 1873, in which the reviewer severely censured Browning for 'a most ill-advised sneer' at Byron's address to the ocean at the end of Childe Harold IV, and particularly at the 'piece of bad grammar, audaciously committed for the sake of the rhyme' in 'there let him lay' (CHP IV, 180).1 The following day there appeared a letter from a certain 'A. A.' who applauded the reviewer's censure but went on to suggest that 'lay' was probably a misprint for 'pray'.2 In response to this John Murray III wrote to say that 'lay' was only an apparent solecism as there were in fact two misprints in the punctuation: 'The full stop after lay has no business there, the sentence runs on into the following stanza' where, after 'capitals' (181), 'there should be a full stop instead of a comma'.3 This irresponsible claim, which far from remedying any defect makes nonsense of two stanzas, met with the derision it deserves and Murray later retracted it.4 But he added: It is curious that in these verses on the Ocean another error should occur in all the old editions of Childe Harold which I will, with your leave, take the opportunity to point out and correct. The line - 'Thy waters wasted them while they were free' - runs in the original MS., now at last in my possession, 'Thy waters washed them power while they were free, And many a tyrant since.'5 On reading this C. M. Ingleby, writing from the Athenaeum, expressed his delight in having confirmation of what he himself had suggested in a paper read before the Royal Society of Literature the previous May.6 But he was still dissatisfied: While accepting the reading of the MS., however, as authoritative, I do not admit that it is happy, for it is the winds that wafted 'the slaves and signs of power' - viz., commercial wealth - and not the waters that washed them to the specified nations, 'and many a tyrant since'. [...] Lord Byron himself once proposed to read [...] 'Thy waters wafted power while they were free,' which reading would have stultified the succeeding words.7 How he came by this last piece of information is difficult to say; but that he was correct was confirmed by a letter that appeared in The Times on the same day from Thomas Kerslake, a Bristol bookseller, who said that he possessed Byron's annotated copy of Childe Harold IV - which had formerly belonged to Hobhouse who had given it to 'the owner' (who remains unidentified) whence it had come into his (Kerslake's) possession - and from that copy he quoted both the 'proposed' reading and some of the annotations. 8 That copy is now in the Robert H. Taylor Collection at Princeton University and is the subject of this present writing. On 24 September 1818 Byron wrote to Murray from Venice: In the one hundredth and thirty-second stanza of Canto 4th. the stanza runs in the Manuscript - 'Left the unbalanced scale - Great Nemesis['] and not 'lost' - which is nonsense - as what losing a scale means - I know not - but leaving an unbalanced scale or a scale unbalanced is intelligible. - Correct this - I pray - not for the public or the poetry - but I do not choose to have blunders made in addressing any of the deities - so seriously as this is addressed - yrs [scrawl for signature] P.S. - In the Translation from the Spanish - alter 'In increasing Squadrons flew' to 'To a mighty Squadron grew' what does 'thy waters wasted them' mean (in the Canto) that is not me. Consult the M.S. always. [...] In referring to the mistake made in stanza 132 I take the opportunity to desire that in future in all parts of my writings relating to religion you will be more careful - & not forget that it is possible that in addressing the deity a blunder may become a blasphemy - & I do not choose to suffer such infamous perversions of my words or of my intention. …

Multicriteria analysis with fuzzy pairwise comparison

The analytic hierarchy process (AHP) is a popular method for solving multicriteria analysis (MA) problems involving qualitative data. However, this method is often criticized due to its use of an unbalanced scale of judgements and its inability to adequately handle the inherent uncertainty and imprecision of the pairwise comparison process. This paper presents a fuzzy approach for tackling qualitative MA problems in a simple and straightforward manner. As a result, effective decisions can be made based on adequate modeling of the uncertainty and imprecision in human behavior. An empirical study of a tender selection problem at Monash municipal government of Victoria in Australia is conducted. The result shows that the approach developed is simple and comprehensible in concept, efficient in computation, and robust in modeling human evaluation processes which make it of general use for solving practical qualitative MA problems.

Evaluating weapon system using fuzzy analytic hierarchy process based on entropy weight

The performance evaluation of weapon systems are multiple criteria decision making problems. The descriptions and judgements on weapon systems are usually linguistic and fuzzy. The traditional method of Analytic Hierarchy Process (AHP) are mainly used in crisp (non-fuzzy) decision applications with a very unbalanced scale of judgements. To overcome these problems, we will propose a new and general decision making method for evaluating weapon systems using fuzzy AHP based on entropy weight. We will use symmetric triangular fuzzy number 1 to 9 to indicate the relative strength of the elements in the hierarchy, and build fuzzy judgement vectors (matrix) through comparison of the performance scores. We will derive the priority among the alternatives by the entropy weight through the use of interval arithmetic, α-cuts, and index of optimism (the degree of optimism of the decision maker) to estimate the degree of satisfaction of the judgement. In this way it does not require a series of pairwise comparison judgements as required by the traditional AHP method. By multiplying the fuzzy subjective weight vector W ̃ with the corresponding fuzzy judgement matrix X ̃ (the orderly list of fuzzy judgement vectors x ̃ ·i for every criterion C i ), a fuzzy problem can be solved and a weapon system selection example will be used to illustrate our method and compare it with other methods.

Influence of explicit standards on judgments with unbalanced response scales.

In previous research (Weiss & Hodgson, 1963) , skewed distributions of response categories were shown to affect the absolute judgments of line-drawn squares by ptoducing a shift in the assignment of stimuli toward the segment of the scale which was overrepresented in the response system. The unbalanced scales had three categories on one side and only one on the other side of the midpoint interval. This effect was removed when a stimulus that was designated as an example of an average-sized square was shown from time to time, even though absolute judgments of the other stimuli were still required. In order to obtain a more sensitive and rigorous test of the potential influence of the unbalanced scale when a standard for judgment is available, it seemed desirable to carry out research in which Ss would serve in all conditions and, hence, intra-subject rather than inter-subject comparisons would be the basis of the analyses and in which the method of constant stimuli coupled with the rating-scale feature of the method of single stimuli would be used. Also, since the effect of the skewed scales when a middle standard is present might be evidenced only when discrimination is relatively poor, a more suitable test would require small stimulus differences between the standard and the immediately neighboring, series stimuli. Smdents (N = 27) at Hunter College judged the lengths of comparison lines thac were exposed one at a time in the window of a memory drum. A standard line, which represented the middle line o f the series, was shown for 2 sec. followed by a blank interval of 2 sec. and then a comparison line for 2 sec. From a complete set of 15 lines, forming an arithmetic progression from 13/16 in. to 3 3 /16 in., with 2/16 in. the constant addend, three partially overlapping subsets were formed; these comprised the lines designated 1-9, 4-12, and 7-15, in order of increasing length. Three response scales were used: a 3category balanced one, containing the categories + (larger), 0 (equal) , - (small e r ) ; and two 5-category unbalanced ones comprising +, 0, -1, -2, -3 or +3, +2, f 1 , 0, -. Nine different Graeco-Latin squares were formed. The cells represented the combinations of response scales with stimulus subsets; the columns, the order of the three combinations for any S; and the rows, Ss. Hence, each S was exposed to each scale and to each subset. Each set of lines with its assigned response scale was judged six times before the next combination was presented. Based on analyses of variance, there was no evidence rhat the nature of the scale had any differenrial effect on the number of stimuli judged smaller than, larger than, or equal to rhe standard, o r o n the size of stimulus iudged equal to the standard. This result was obtained whether the early trials, the later trials, o r all trials for a subset were examined, and whether only the responses to the three middle stimuli or to all stimuli were analyzed. Hence, the data confirm the outcomes of the research by Weiss and Hodgson (1963) and support their inference thac the effects of unbalanced scales are limited to situations where the average category of judgment is not held by some standard to a specified portion of the stimulus continuum.

Effects of Unbalanced Response Scales on Judgments of Social Stimuli

The general purpose of the research was to determine if scale judgments of certain social stimuli would be differentially affected by the distribution of scale categories constituting the response scale. Previous research (Weiss & Hodgson, 1963) had demonstrated such an effect on judgments of neutral, physical stimuli. Two experiments were therefore conducted in which 72 and 248 college students judged the social prestige of 40 occupations. Ss used one of four types of scales: a 3-category balanced scale (+, 0, −), a 7-category balanced scale (+3 to −3), a 5-category unbalanced minus scale (+, 0, −1, −2, −3), or a 5-category unbalanced plus scale (+3, +2, +1, 0, −). The non-discriminating plus and minus categories were to be used for occupations that were above or below the average in prestige, regardless of how far above or below they might be. The zero category designated those average in prestige. And the discriminating plus or minus categories represented degrees of prestige above or below the average. The data revealed significant effects of the scales on the typical social prestige of occupations assigned to the ‘average’ category of judgment. Relative to the balanced scales, the unbalanced ones induced a shift in the prestige value of the ‘average’ category in the direction of the single, non-discriminating category. Relative to the 7-category balanced scale, the 3-category one produced a shift in the direction of the non-discriminating plus side. The data were interpreted primarily in terms of relationships between implicit category standards, latitudes of categories, and the distribution of the judged stimuli.