Search

The construction industry currently is confronted with significant challenges, stemming from a decreasing working population coupled with an aging workforce. Accordingly, the development of teleoperated hydraulic excavators is being investigated to optimize operations. The ability to switch between multiple machines during operations is expected to reduce transportation and labor costs, thereby increasing productivity. However, work efficiency may be severely affected when operators switch between different classes of machines, such as excavators with varying sizes and capabilities. Each machine class operates differently, and immediate adjustments to the dynamic characteristics may be challenging. Previous research has demonstrated that operators of teleoperated hydraulic excavators struggle to perceive load, as they rely on visual information from cameras instead of tactile feedback. Consequently, loading information, particularly related to the attachment’s maximum exertion force, is difficult to estimate. This study proposes a load index called “attachment joint-load ratio” to mitigate decreased work efficiency when switching machines. This index considers the attachment’s maximum exertion force and attempts to provide operators with intuitive feedback about load conditions. This study focuses on excavation work and compares the operating characteristics of a standard hydraulic excavator with a conventional load feedback method. The objective is to ascertain whether feedback regarding the attachment joint load ratio can mitigate the effects of transitioning between machine classes on work efficiency. Using a simulator that mimics a teleoperated hydraulic excavator based on the proposed feedback method, we conducted experiments and verified the effectiveness of the proposed method.

This study examines in what way tactile impressions affect consumers’ willingness to pay for a product. We used a sample of 139 students and staff from a large university in Japan. Participants, who are also consumers of smartphone covers, were asked to share their willingness to pay for smartphone covers with four types of surface textures (A, B, C, and D) when the reference smartphone cover price was either 100 yen or 1,000 yen (1000 yen = 7.89 EUR). The smartphone covers were differentiated by surface smoothness, height, slipperiness, dampness, granularity, stickiness, and dryness. The results showed that respondents were willing to pay a premium for most of the textures. Furthermore, our study found that consumers’ willingness to pay for a surface texture depends on demographic and socio-economic features. This study’s results provide preliminary evidence on the value of tactile impressions, providing a foundation for more comprehensive studies in the future.

Appropriate reaction force design is essential to improve the lever operability of a hydraulic excavator that is difficult to operate. However, the force characteristics a human perceives when operating these levers are unknown. It is unclear whether the reaction force characteristics of the conventional lever are optimum for humans. Thus, this study aims to clarify the perceived force characteristics during the lever operation and verify the effectiveness of the lever reaction force design. In this study, a perceived force prediction method was proposed based on a musculoskeletal simulation for the lever operation. Also, it was confirmed that the perceived force could be estimated within a 7.8%–14.3% root mean square error. Furthermore, we developed the lever with the reaction force characteristics in which the perceived force varied linearly with the lever angle and confirmed that the proposed lever significantly improved operability when performing the leveling task with the excavator.

The recent increase in sedentary lifestyles has highlighted the importance of physical activity in our daily lives. Although fall accidents are a common cause of injuries among the elderly, walking is one of the simplest physical activities available. Therefore, walking route selection and identification of walking behavior in different scenarios remains a widely researched area. This paper is about developing a walking-route recommender system that proposes a safe route to the user and reduces the probability of fall accidents. We determine route candidates after the start and endpoints are fed to the system. Then the tripping risk involved in each route candidate is identified by performing several walking simulations of a digital human model on a three-dimensional laser-scanned point cloud. Finally, a safe route is determined after considering the user’s age and the tripping risk. It was confirmed that tripping risk could be competently estimated according to the considered age group.

Teleoperated excavators have a risk of overturning or falling when digging because it is more difficult to receive information regarding the machine posture and the work object condition than in the case of actual machine boarding. In this study, the machine instability derived from the attachment posture and the digging reaction force has been proposed. In addition, for feedback regarding the machine instability to the operator, an intuitive visual presentation method using a meter is proposed. To verify the effect of the proposed machine instability feedback, an excavation operation simulator was constructed, and an experiment was conducted. As a result, by using the machine instability feedback, it was confirmed that digging could be performed without generating the tilting and forward movements of the machine body, and that the ratio of the time during which the machine instability exceeded 100% decreased, while the productivity remained constant. Additionally, by verifying the effect of the subject experiment, even in the actual teleoperated excavator, it was confirmed that the work could be conducted without generating a greater tilting of the machine body, while maintaining productivity. Therefore, the possibility of working safely in the teleoperated excavator using machine instability feedback was clarified.

We investigated the effect of restricting the field of view from the cockpit on the operation of a hydraulic excavator. We developed a computer simulation for the turning operation of an excavator and we performed an experiment. In the experiment, we recorded the operation time required to complete various reaching tasks. We found that the operation time depends on the distance from the start position to the target position, target size, and the field-of-view width. We propose an extension to Fitts' law model to represent the operation time according to the operation's index of difficulty, which consists of the target distance, target size, and field-of-view width. The developed model was evaluated by the simulation results and the results obtained by an experiment with an actual hydraulic excavator. We observed significant improvement in the coefficient of determination between the operation time obtained by the experiments and the proposed index of difficulty.

Information-centric networking (ICN) is a new approach to networking contents rather than devices that hold the contents. It has recently attracted much attention of network research and standardization communities. National and multi-national funded research projects have progressed worldwide. International Telecommunication Union - Telecommunication Standardization Sector (ITU-T) started ICN standardization activities in 2012. In parallel, the standards-oriented research cooperation is progressing in the Information-Centric Networking Research Group (ICNRG) of the Internet Research Task Force (IRTF). All these global efforts have been collectively advancing the novel network architecture of ICN. However, there are very few surveys and discussions on the detailed ICN standardization status. To update the reader with information about the ICN research and standardization related activities, this paper starts with the history of global activities on ICN from 2010, giving references to various projects. It then describes the recent progress in the standardization of ICN component technologies in ITU-T and various documents produced by ICNRG. Lastly, it discusses the future directions for progressing ICN.

In this study, we develop a technique to measure walking under noncontact conditions by using an ultrahigh sensitivity electrostatic induction technique. The results of walking measurements using this technique indicate that the detected electrostatic-induced current waveform exhibits a peak at the time of foot contact or detachment owing to walking. Based on these results, we construct a theoretical model in which an induced current is generated, and the correspondence relationship between walking and electrostatic-induced current is revealed. Furthermore, when comparing the walking signals of each participant, we used a scalogram obtained by performing a wavelet transformation on the walking signal. Person identification was attempted by learning the participant's scalogram using a convolutional neural network (CNN).

Gettering sinks for metallic impurities formed by carbon-cluster ion implantation in epitaxial silicon wafers have been investigated using technology computer-aided design and atom probe tomography (APT). We found that the defects formed by carbon-cluster ion implantation consist of carbon and interstitial silicon clusters (carbon-interstitial clusters). Vacancy-type clusters are not dominant gettering sinks for metallic impurities in the carbon-cluster ion implanted region. APT data indicated that the distribution of oxygen atoms in the defects differs between Czochralski-grown silicon and epitaxial silicon wafers. The high gettering efficiency observed in carbon-cluster ion implanted epitaxial silicon wafers in comparison with Czochralski-grown silicon wafers is due to the distribution of oxygen atoms in the defects. Defects not containing O atoms provide strong gettering sinks for metallic impurities. These defects are formed by only carbon-interstitial clusters. Oxygen atoms inside the defects modify the amount of carbon-interstitial cluster formation on the defects. It is suggested that the gettering efficiency for metallic impurities in carbon-cluster ion implanted epitaxial silicon wafer is determined by the amount of carbon-interstitial clusters.

In this paper, we propose a method for texture image labeling that works with a small number of training images. Our method is based on a tree of shapes and histogram features computed on the tree structure. Labeling results could be obtained by simply classifying the histogram features of all nodes in a tree of shapes. However, it is difficult to obtain satisfactory results, because features of smaller nodes are not sufficiently discriminative. Consequently, our method selects optimal discriminative subtrees for image labeling. We model an objective function that includes the parameters of a classifier and a set of thresholds for each training image to be used to select optimal subtrees. Then, labeling is performed by mapping the classification results of selected subtrees into corresponding blobs in the image. Experimental results with synthetic and real data sets that we created for evaluation show that the proposed method performs qualitatively and quantitatively much better than the existing methods.