nils-herrmann/clean_scirepeval huggingface dataset:
Landmark Summarization With Diverse Viewpoints

Landmark summarization with diverse viewpoints is very important in landmark retrieval, as it can create a comprehensive description of a landmark for users. In this paper we present an approach for summarizing a collection of landmark images from diverse viewpoints. First, we group landmark images with content overlap by viewpoint album (VA) generation. Second, we model the relative viewpoint of each image within the VA based on the spatial layout of distinctive descriptors of a landmark. Third, we express the relative viewpoint of an image with a 4-D viewpoint vector, including horizontal, vertical, scale, and rotation. Finally, we summarize the landmarks in terms of viewpoints. Experimental results show the effectiveness of the proposed landmark summarization approach.
3D simulation design based on openGL for four-legged robot

This paper introduces and analyses a three dimensional real-time kinematic simulation system for four-legged robot. The effective method of constructing interface between 3D geometrical modeling software and simulation system in OpenGL is applied in the geometrical modeling module for the robot. The construction of kinematic model and the demonstration of animation are analyzed emphatically. Further more, the structure of the functional modules of simulation system is discussed in detail
Neural optimal control of robotic manipulators with CMAC networks

In this paper, an adaptive GA CMAC-based inverse kinematics solution of a robotic manipulator is presented. Real-time control of the end effectors of a robot requires computationally efficient solutions of the inverse kinematics. The inverse kinematics of a robotic manipulator is nonlinear and in some cases it cannot be solved in closed form. Some traditional solutions such as iterative and geometric are inadequate if the manipulator is more complex. Neural network such as CMAC approaches are studied in solving the inverse kinematics problem. But conventional CMAC can not give us appropriate values for the parameters of CMAC module such as the learning rate of CMAC and the size of generalization. Without suitable parameters, the convergence speed of CMAC can be slow. In this paper, we adopt the adaptive GA to search for the optimal parameters. Furthermore, the developed method is applied to a two-joint robot. Finally, the effectiveness of the proposed adaptive GA CMAC model control system is verified by simulation experimental results.
Knowledge discovery over community-sharing media: From signal to intelligence

The explosive growth of photos/videos and the advent of mediasharing services have drastically increased the volume of usercontributed multimedia resources, which bring profound social impacts to the society and pose new challenges for the design of efficient search, mining, and visualization methods for manipulation. Besides plain visual or audio signals, such large-scale media are augmented with rich context such as user-provided tags, geolocations, time, device metadata, and so on, benefiting a wide variety of potential applications such as annotation, automatic training data acquisition, contextual advertising, and visualization. We review the research advances for enabling such applications and present a brief outlook on open issues and major opportunities.
Multi-agent based intelligent virtual training system

Integrated virtual reality with intelligent tutoring system, a multi-agent framework was proposed for intelligent virtual system for training in optional environment to improve traineepsilas emergency decision-making ability as well as their technical level. In order to make sure agentpsilas training task plans are reliable and adaptive, a declarative formalism was applied to represent the virtual training task knowledge. Moreover, to mediate the interactions between trainee and virtual environment, the architecture of virtual trainee agent was constructed and realized, which is a comprehensive model of 3D virtual human as highly-capable individuals and combines with perceptual, behavioral, mental state, and cognitive modules. Finally, a practical intelligent virtual training system was represented, and the primary results show the robustness of our system and its ability to produce an effective virtual environment for safety training.
Author Topic Model-Based Collaborative Filtering for Personalized POI Recommendations

From social media has emerged continuous needs for automatic travel recommendations. Collaborative filtering (CF) is the most well-known approach. However, existing approaches generally suffer from various weaknesses. For example , sparsity can significantly degrade the performance of traditional CF. If a user only visits very few locations, accurate similar user identification becomes very challenging due to lack of sufficient information for effective inference. Moreover, existing recommendation approaches often ignore rich user information like textual descriptions of photos which can reflect users' travel preferences. The topic model (TM) method is an effective way to solve the “sparsity problem,” but is still far from satisfactory. In this paper, an author topic model-based collaborative filtering (ATCF) method is proposed to facilitate comprehensive points of interest (POIs) recommendations for social users. In our approach, user preference topics, such as cultural, cityscape, or landmark, are extracted from the geo-tag constrained textual description of photos via the author topic model instead of only from the geo-tags (GPS locations). Advantages and superior performance of our approach are demonstrated by extensive experiments on a large collection of data.
Anisotropic Manifold Ranking for Video Annotation

Graph-based semi-supervised learning (SSL) has attracted lots of interests in machine learning community as well as many application areas including video annotation recently. However, one of the two basic assumptions, structure assumption, which is an essential point of graph-based SSL, is not embedded into the pairwise similarity measure. Accordingly, we propose a novel graph-based SSL method for video annotation, named anisotropic manifold ranking (AniMR), based on a structure-related similarity measure. This method takes the influence of the density difference between samples into account to improve the pairwise similarity. Furthermore, we will show that AniMR can also be deduced from partial differential equation (PDE) based anisotropic diffusion. It demonstrates that the label propagation in AniMR is anisotropic, which is intrinsically different from the isotropic label propagation process in general graph-based SSL methods. Experiments conducted on the TRECVID data set show this approach outperforms ordinary graph-based SSL methods and is effective for video semantic annotation.
Design of vertical climbing robot with compliant foot

This paper presents ICBot (inchworm-like robot with claws), a vertical climbing robot which uses inchworm-like motion and bidirectional claws. The robot mainly consists of four parts, upper support, lower support, crank-slider mechanism between them, and compliant feet with bidirectional claws. A single motor drives the crank-slider mechanism, resulting in lower support and upper support move relatively, just like the inchworm motion. The bidirectional claws make the robot attach and release easily. ICBot measures 12cm in length and 30g in weight. It is capable of climbing vertical pearl brocade plate, softwood and other soft or rough surface.
A Multiple Attribute-based Decision Making model for autonomous vehicle in urban environment

In this paper, a maneuver decision making method for autonomous vehicle in complex urban environment is studied. We decompose the decision making problem into three steps. The first step is for selecting the logical maneuvers, in the second step we remove the maneuvers which break the traffic rules. In the third step, Multiple Attribute Decision Making (MADM) methods such as Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are used in the process of selecting the optimum driving maneuver in the scenario considering safety and efficiency. AHP is used for obtaining the weights of attributes, TOPSIS is responsible for calculating the ratings and ranking the alternatives. Road test indicates that the proposed method helps the autonomous vehicle to make reasonable decisions in complex environment. In general, the experiment results show that this method is efficient and reliable.
Service Quality Evaluation by Exploring Social Users’ Contextual Information

Nowadays, with the boom of social media and e-commerce, more and more people prefer to share their consumption experiences and rate services on review sites. Much research has focused on personalized recommendation. However, quality of service also plays an important role in recommender systems, and it is the main concern of this paper. An overall rating that indicates the popular view usually represents the evaluation. There are some challenges when we do not have enough review information to extract public opinion. Take, for example, a movie for which one user rates a two star rating, and another rates a five star rating. In this case, it is difficult to conduct a quality evaluation fairly. However, it is possible to be improved with the help of big social users' contextual information. In this paper, we propose a model to conduct service quality evaluation by improving overall rating of services using an empirical methodology. We use the concept of user rating's confidence, which denotes the trustworthiness of user ratings. First, entropy is utilized to calculate user ratings' confidence. Second, we further explore spatial-temporal features and review sentimental features of user ratings to constrain their confidences. Last, we fuse them into a unified model to calculate an overall confidence, which is utilized to perform service quality evaluation. Extensive experiments implemented on Yelp and Douban Movie datasets demonstrate the effectiveness of our model.
Aligned Copper Nanorod Arrays for Surface-enhanced Raman Scattering

Highly ordered copper nanorod arrays have been synthesized using potentiostatic electrodeposition within the confined nanochannels of a porous anodic alumina membrane (PAAM). These arrays were evaluated as potential surface- enhanced Raman scattering (SERS) active substrates using Rhodamine 6G as a reported molecule. SERS activity was shown to depend upon the length of the nanorods exposed to the surface which is controlled by the etching time. The Cu nanorods with average lengths of 200 nm exposed to surface exhibited the maximum SERS enhancement. Theoretical analyses indicate that this large SERS enhancement may be partially explained by the shape, density, and lateral arrangement of the Cu nanorod arrays.
Multisensory gripper and local autonomy of extravehicular mobile robot

This paper presents the development of the multisensory robot gripper for extravehicular mobile robot (EMR) and its sensor based local autonomy. For stable extravehicular walking and performing delicate tasks in unstructured and complex environment, our EMR gripper employed a simple and reliable mechanism and it is equipped with multisensory apparatus. Local autonomy of the space robot is an important requirement for on-orbit manipulation. Detecting contact state between robot gripper and environment is essential to fulfill space robot local autonomy. But we often face the problem of lack of sensory information when we try to know the contact state. A new way to detect: contact state under inadequate sensory information is proposed. By combing force sensor information with gripper geometry and mechanical analysis, some spatial contact information between robot and the trusswork can be derived. Then robot can adjust its position and orientation by fine motion displacement based on contact information to fulfill steady grasping. This method is implemented on a walking/grasping task, which is a simple and important fundamental task for extravehicular space robot.
Environment-Map-free Robot Navigation Based on Wireless Sensor Networks

It's a new and good method to apply wireless sensor networks on robot navigation. We proposed an environment map free navigation for robot based on wireless sensor networks. In this system, the robot did not need to obtain the environment map and can get online navigation. The wireless sensor nodes collected environment and position information and made distributed information fusing to give a path for the robot. The robot then communicated with the wireless sensor network and went through following network's order. To combine the shorter path and the safer path, we proposed a navigation cost method for robot's navigation. It makes know by analysis that the environment map free navigation algorithm for robot in wireless sensor networks can achieve an online navigation and get highly precise navigation.
Personalized Recommendation Combining User Interest and Social Circle

With the advent and popularity of social network, more and more users like to share their experiences, such as ratings, reviews, and blogs. The new factors of social network like interpersonal influence and interest based on circles of friends bring opportunities and challenges for recommender system (RS) to solve the cold start and sparsity problem of datasets. Some of the social factors have been used in RS, but have not been fully considered. In this paper, three social factors, personal interest, interpersonal interest similarity, and interpersonal influence, fuse into a unified personalized recommendation model based on probabilistic matrix factorization. The factor of personal interest can make the RS recommend items to meet users' individualities, especially for experienced users. Moreover, for cold start users, the interpersonal interest similarity and interpersonal influence can enhance the intrinsic link among features in the latent space. We conduct a series of experiments on three rating datasets: Yelp, MovieLens, and Douban Movie. Experimental results show the proposed approach outperforms the existing RS approaches.
Design and experiment of a tank-like wall-climbing robot using fibril dry adhesives

This paper presents the design, analyses, and fabrication of a tank-like wall-climbing robot using gecko-inspired dry adhesives. The robot uses customized timing adhesive belts, which is flexible as well as patterned using MEMS techniques. The Kendall strip tape model is modified, considering features of the timing belt, to analyze the peeling process of the viscoelastic tread. The relationship between the peeling force and the pretension strain of the treads is predicted. The normal force distribution of the treads is analyzed in the robot's adhesive process. Conditions for robot's stable climbing are derived. A prototype is fabricated and tested.
Development of the lifting and propulsion mechanism of biped robot running on water

The basilisk lizard's function of running on water is used to analyse the dynamical mechanism of the biped robot which has the same function. The movement trajectories of the a Watt-I six-bar linkage are brought out by combining the movement equations of the four bar mechanism and the coordinate transformation equations, which are used to simulate the foot trajectories of the basilisk lizard, and the lifting and propulsion mechanism of the biped robot running on water is carried out. The links' parameters are optimized by taking the trajectories overlap ratio as the target function. The prototype of the biped robot running on water is made by the results of the kinetic analysis on the robot. And the lifting and propulsion force curve on the robot from water is measured. The experiment results show that the lifting and propulsion system satisfy the function requirement of biped robot running on water.
A foundry fabricated high-speed rotation sensor using off-chip RF wireless signal transmission

A novel MEMS surface-micromachined non-contact high-speed rotation sensor with total surface area under 4 mm/sup 2/ was developed using the MCNC Multi-User MEMS Processes (MUMPs). This paper reports the initial characterization of the sensor, including rotation and vibration tests. Initial results indicate that this piezoresistive sensor is capable of wirelessly measuring rotation speeds at /spl sim/2Hz/rpm/V with 5V input in the 100 to 6000 rpm rotation range. We believe our groundwork will allow the MEMS community to use the MUMPs foundry service to design simple and reliable high-speed rotation sensors that can be interfaced with commercial wireless chips for signal transmission.
Error analyzing for RSSI-based localization in wireless sensor networks

Analyzing the measuring errors of nodes using received signal strength indications (RSSI) method, such as the parameter error of RSSI theoretical model and the obstacle error between neighbor nodes, this paper proposed a localization algorithm based on analyzing of RSSI errors in wireless sensor networks called ERSSI. Based on the two errors mentioned, it got the online parameter changing method for RSSI theoretical model and reduced the effect of those small obstacles. We show by both theoretical analysis and simulations that this algorithm can get low localization errors when the size of obstacles is small.
A bridge crack image detection and classification method based On climbing robot

Traditional bridge crack detection methods are of high cost and high risk. We propose a bridge crack detection and classification method based on a climbing robot using image analysis with a miniature camera mounted on the robot to collect images. First, the motion blur of acquired image is removed by Wiener filtering method. Second, wavelet transform is used to enhance fracture of the crack in the image. Third, to complete the crack image recognition, the surface morphology analysis is applied to extract crack fragments and then KD-tree is used to connect them. Finally, support vector machine method is used to classify cracks based on a series of basic visual characteristics and geometric features. Compared with geometrical characteristic classification method and BP neural network classification method, our results show that the proposed method has a better perform in crack image recognition.
A kind of cognitive driver assistance system with adaptive authority adjusting

Driver assistance system is a kind of significant means to improve the safety and comfort of driving. The distinctness between classic driver assistance models and cognitive driver assistance models were investigated. The principles and methods of adaptive authority adjusting were developed from the perspective of cognitive coordination and cooperation. The different levels of vehicle driving automation were given. The driver and driver assistance system were integrated into coordination and cooperation control system with adjustable level of autonomy which based on the adaptive authority adjusting strategy. Finally, the integrated system structure and prototype system were given. The adaptive authority adjusting strategy increases the abilities of coordination and cooperation between driver and driver assistance system.
Direct Kinematics Problem of Parallel Robot Based on LS-SVM

Although parallel robot is widely used on many fields now, it is still a fascinating problem of kinematics solution of parallel robot. Using common methods involves the solving a series of simultaneous non-linear equations and, usually, non-unique, multiple sets of solutions are obtained from one set of data. Here a method based on LS-SVM is presented, the proposed method is applied to the parallel robot and satisfactory results are obtained. It proves that the method is feasible and effective. The results show that this approach can be used for the on-line control of parallel manipulators
Fractal Object Generation Based on CAD and CAM

This paper first apply high dimension complex and self-square function J(z)=z2+c to generate special data set on 3D fractal, then take the set as the research object and produce the related STL model through the partition by its symmetry character and the triangulation of the consequent set, at last adopt Rapid Prototype technique to manufacture the fractal object by the CAD model. This research and technique route not only solve the problem that fractal can only be simulated and the related object can not be manufactured owing to the complex surface, but also build the bridge connecting fractal, CAD and CAM, which is an important experiment and innovation in fractal application research.
Design and Implementation of a Fencing Training Robot

A mobile robot that is served for training the fencing athletes is introduced. The pilot and sensing units are designed and set on the robot at particular positions. To ensure a fast and smooth motion when starting, running and braking the robot, the driver unit is carefully designed on the base of analysing the torque-frequency curve of the step motor. This fencing training robot not only can used to train an athlete's each single special ability such as stepping, hitting accuracy, and response, but also can used to train the combined ability. At the same time, it can give a quantitative evaluation of training effect to guide the next training plan. The robot has been used in practice
Design and fabrication of an integrated three-dimensional tactile sensor for space robotic applications

An integrated three-dimensional tactile sensor with robust structure and soft contact surface suitable for space robotic applications was developed. The sensor has a maximum force range of 50 N in the vertical direction and /spl plusmn/10 N in the x-y horizontal directions. The sensitivity of the sensor cells in the vertical direction is 13 m V/V and in the x and y horizontal directions are both 2.3 mV/N. The tactile sensor includes 4/spl times/8 sensing cells each exhibiting an independent linear response to the three components of forces. Post bulk-micromachining was performed on foundry fabricated CMOS chips to produce the sensor cells. With neural network training, the tactile sensor produced reliable 3-axes force measurements and repeatable response on tactile images. Design analysis, fabrication procedures, and experimental results are presented in this paper.
Automatic Generation of Social Event Storyboard From Image Click-Through Data

Recent studies have shown that a noticeable percentage of Web search traffic is about social events. While traditional Web sites can only show human-edited events, in this paper, we present a novel system to automatically detect events from search log data and generate storyboards where the events are arranged chronologically. We chose image search log as the resource for event mining, as search logs can directly reflect people’s interests. To discover events from log data, we present a smooth nonnegative matrix factorization framework, which combines the information of query semantics, temporal correlations, search logs, and time continuity. Moreover, we consider the time factor to be an important element, since different events will develop in different time tendencies. In addition, to provide a media-rich and visually appealing storyboard, each event is associated with a set of representative photos arranged along a timeline. These relevant photos are automatically selected from image search results by analyzing image content features. We use celebrities as our test domain, which takes a large percentage of image search traffic. Experiments consisting of Web search traffic on 200 celebrities, for a period of six months, show very encouraging results compared with handcrafted editorial storyboards.