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The purpose of this paper is to evaluate the effect of main parameters and their interactions on the workers' Lifting Index in a steel rolling mill.

NIOSH (National Institute for Occupational Safety and Health) lifting equation has been used to evaluate the risk of lifting tasks with respect to low back injury under varying load (10, 15, 20 kg), frequency (2, 3, 4 lifts/min), and twisting angle (0, 30, 45 degree).

The level of importance of the parameters on lifting index at origin and destination has been determined using analysis of variance (ANOVA).The analysis draws on lifting parameters and uses both main effects and interactions to describe the variation in Lifting Index and to identify the social influence associated with back injury. The interactions between object weight and twisting angle and object weight and lifting frequency turn out to be significant (p<0.05), whereas the interaction between twisting angle and lifting frequency is less significant (p=0.061).

The study includes a specific location (steel rolling mills located in Jammu region of India) only.

The findings suggest that focus should be made on all lifting parameters, rather than sole emphasis on the load to be lifted.

The paper supports the view that load, twisting angle and lifting frequency greatly influence the physical stressfulness of the task. It is suggested that the workplace should be designed for negligible twisting and moderate lifting frequency, so as to have minimum Lifting Index.

A classifier technique is one of the important tools which may be used to classify the data or information into systematic manner based on certain criteria pertaining to get the accurate statistical information for decision making. It plays a vital role in the various applications, such as business organization, e-commerce, health care, scientific and engineering application. The purpose of this paper is to examine the performance of different classification techniques in lift index (LI) data classification.

The analyses consist of two stages. First, the random data are generated for lifting task through computer programming, which is then put into the National Institute for Occupational Safety and Health equation for LI estimation. Based on the evaluated index, the task may be classified into two groups, i.e. high-risk and low-risk task. The classified task is considered to analyze the performance of different tools like Artificial Neural Network (ANN), discriminant analysis (DA) and support vector machines (SVMs).

The work clearly demonstrates the accuracy and computational ability of ANN, DA and SVM for data classification problems in general and LI data in particular. From the research it may be concluded that SVM may outperform ANN and DA.

The research is limited to a particular kind of data that may be further explored by selecting the different controllable parameters and model specification. The study can also be applied to realistic problem of manual loading. It is expected that this will help researchers, designers and practicing engineers by making them aware of the performance of classification techniques in this area.

The objective of this research work is to assess and compare the relative performance of some well-known classification techniques like DA, ANN and SVM, which suggest that data characteristics considerably impact the classification performance of the methods.

Offers guidance on how to achieve proper maintenance of building lifts. Details equipment audit and the maintenance contract. Discusses lift operations, performance measurement, user requirements and insurance and legal requirements. Finally looks at remote and third party monitoring.

The purpose of this study is to use the individual blade pitch control (IBC), reduce actively both the rotor hub vibratory loads and airframe vibration responses for the lift-offset compound helicopter at a high-speed flight condition.

The Sikorsky X2 technology demonstrator (X2TD) is used as the lift-offset compound helicopter. The X2TD lift-offset rotor is modelled and its rotor hub vibratory loads at a flight speed of 250 knots are predicted using a rotorcraft comprehensive analysis code, CAMRAD II, and the airframe structural dynamics is represented with a finite element analysis code, MSC.NASTRAN. When the propulsive trim methodology is applied for rotor trim, the best input condition for IBC using multiple harmonic inputs is searched to reduce the rotor vibration, while the rotor aerodynamic performance (the rotor effective lift-to-drag ratio) is improved or maintained at least. Finally, the reduction in airframe vibration responses is investigated when the best input condition for IBC with multiple harmonics is applied to the lift-offset rotor.

When the IBC with the single harmonic input using the 2/rev actuation frequency, amplitude of 2° and control phase angle of 120° (2P/2°/120°) is considered for X2TD rotor, the rotor vibration is reduced by about 26.37% only and the rotor effective lift-to-drag ratio increases slightly by 0.98%. When X2TD rotor uses the IBC with multiple harmonic inputs (2P/2°/45° + 5P/1°/90°), the rotor hub vibratory loads and airframe vibration responses are reduced by 44.69% and from 0.48 to 79.10%, respectively, while rotor effective lift-to-drag ratio is improved by 0.77%, as compared to the baseline without IBC.

This study is the first study to use the 2/rev actuation for IBC to the four-bladed lift-offset coaxial rotor and to investigate to obtain simultaneously the rotor vibration reduction, rotor performance improvement and airframe vibration reduction, using IBC with multiple harmonic inputs.

This study seeks to explore the aerodynamic performance of wings with different shapes at low Reynolds numbers.

The airfoils of these wings are made from aluminum plates, and the maximum cord length and wingspan are 15 cm. Wings A to D are plates with 6 percent Gottingen camber but different wing planforms. The forward‐half sections of wings E and F are dragonfly‐like, whereas the rear‐half sections of wings E and F are flat and positively cambered, respectively. The aspect ratios of these wings are close to one, and the ratios of plate thickness to the maximum cord length are 1.3 percent. Experimental results indicate that the wings with Gottingen camber have a superior lift and lift‐to‐drag ratio, whereas the wings with dragonfly‐like airfoils perform well in terms of drag and pitch moment.

The aerodynamic measurements of the wings demonstrate that the wing with the Gottingen camber airfoil, a swept‐back leading edge and a straight trailing edge is suitable for use in micro aerial vehicle (MAV). An MAV is fabricated with this wing and the aerodynamic performance of the MAV is examined and compared with the bare wing data.

This study develops several criteria to the design of MAV‐sized wings. For example, the thickness ratio of airfoil must be small, usually less than 2 percent. Besides, the airfoil must be cambered adequately. Furthermore, a wing planform with a swept‐back leading edge and a straight trailing edge would be contributive to the successful flights of MAVs.

The purpose of this paper is to develop an expert system capable of assessing risk associated with manual lifting in construction tasks and proffer some first aid advices which are comparable with those obtainable from human experts.

The expert system, musculoskeletal disorders – risk evaluation expert system (MSDs-REES), used Microsoft.Net C# programming language to write the algorithm of the fuzzy inference system with variables load, posture and frequency of lift as inputs and risk of low back pain as the output. The algorithm of the inference engine applied sets of rules to generate the output variable in crisp value.

The result of validation, between the human experts’ calculated risk values and MSDs-REES-predicted risk values, indicated a correlation coefficient of 0.87. Between the predicted risk values generated using MSDs-REES and the existing package (MATLAB version 7.8), there was a strong positive relationship statistically with correlation coefficient of 0.97.

The study provided a very simple expert system which has the ability to provide some medical-related injury prevention advice and first aid information for injury management, giving it a unique attribute over the existing applications.

This study aims to evaluate enterprise technology innovation capability in prefabricated construction (PC) from an input-output perspective, using six integrated enterprises in China as cases.

An evaluation system for enterprise technology innovation capability in PC was constructed, including total input, technology output (TO) and project output. All the evaluation indexes were quantified, and the subject and object indexes weights were determined using the fuzzy cognitive map and information entropy, respectively. The final scores and ranks were evaluated through gray relational analysis (GRA) based on the combined weights.

It was found that enterprise technology innovation capability in PC was low in China, with its unbalanced development in different dimensions and the poorest performance in TO, currently.

This research has developed an evaluation system for technology innovation capability in PC at the enterprise level and scientifically quantified all the indexes, which is a breakthrough over existing studies. The GRA model based on the combined weights proposed in this study can be applied to other comparable fields and regions, with its easy operation.

This study aims to provide a way to derive inter-brand similarities from user-generated content on online brand forums, which enables the authors to analyze the market structures based on consumers' actual information searching and sharing behavior online. This study further presents a method for deriving inter-brand similarities from data on how the sales of competing brands covary over time. The results obtained by the above two methods are compared to each other.

In drawing similarities between brands, the authors utilized a newly proposed measure that modified the lift measure. The derived similarity information was applied to multidimensional scaling (MDS) to analyze the perceived market structure. The authors applied the proposed methodology to the imported car market in South Korea.

In light of some clear information such as the country of origin, the market structure derived from the presented methodology was seen to accurately reflect the consumer's perception of the market. A significant relevance has been found between the results derived from user-generated online content and sales data.

The presented method allows marketers to track changes in competitive market structures and identify their major competitors quickly and cost-effectively. This study can contribute to improving the utilization of the overflowing information in the big data era by proposing methods of linking new types of online data with existing market research methods.

The purpose of this paper is to optimize the downrange for hypersonic boost‐glide (HBG) missile under near‐real condition, and to validate the suitability of proposed wall cooling materials.

The trajectory optimization problem is characterized by a boost phase followed by a glide phase. A multi‐phase trajectory optimization tool is adopted to optimize the downrange. The associated optimal control problem has been solved by selecting a direct shooting method. The dynamics has been transcribed to a set of nonlinear constraints and the arising nonlinear programming problem has been solved through a sequential quadratic programming solver. An aerothermodynamics analysis method is introduced to calculate the aerodynamic heating at nose, leading edge, and ventral centerline regions.

HBG missile is suitable for long‐range attack, and the optimal trajectory solved is a novel boost‐glide‐skip trajectory, i.e. boost firstly, glide secondly, and skip at last. The proposed wall materials are valid.

This paper provides further study on the methods of trajectory design and aerothermodynamics analysis for HBG missile.

This paper investigates the semantic association mechanisms of weak demand signals that facilitate innovative product development in terms of conceptual and temporal precedence, despite their inherent ambiguity and uncertainty.

To address this challenge, a domain ontology approach is proposed to construct a customer demand scenario-based framework that eliminates the blind spots in weak demand signal identification. The framework provides a basis for identifying such signals and introduces evaluation indices, such as depth, novelty and association, which are integrated to propose a three-dimensional weak signal recognition model based on domain ontology that outperforms existing research.

Empirical analysis is carried out based on customer comments of new energy vehicles on car platform such as “Auto Home” and “Bitauto”. Results demonstrate that in terms of recognition quantity, the three-dimensional weak demand signal recognition model, based on domain ontology, can accurately identify six demand weak signals. Conversely, the keyword analysis method exhibits a recognition quantity of four weak signals; in terms of recognition quality, the three-dimensional weak demand signal recognition model based on domain ontology can exclude non-demand signals such as “charging technology”, while keyword analysis methods cannot. Overall, the model proposed in this paper has higher sensitivity.

This paper proposes a novel method for identifying weak demand signals that considers the frequency of the signal's novelty, depth and relevance to the target demand. To verify its effectiveness, customer review data for new energy vehicles is used. The results provide a theoretical reference for formulating government policies and identifying weak demand signals for businesses.