nils-herrmann/clean_scirepeval huggingface dataset:
Photosense: Make sense of your photos with enriched harmonic music via emotion association

This paper proposes a novel audiovisual presentation system, called PhotoSense, to enrich photo navigation experience by associating emotionally harmonic music with a given photo collection. Different from many conventional photo visualization systems which predominantly focus on the visual elements for presentation, we explore both visual and aural perspectives which can enhance the browsing experience from each other. This is achieved by building an emotion space shared by visual and aural domains, and a set of emotion classifiers which can associate each visual and aural element with this space. Furthermore, we design a sequence matching algorithm to associate a set of music with a photo collection by maximizing similarity in the emotion space. Photo-Sense represents one of the first mash-up applications which build a natural connection between the ever increasing personal photo collections on the Web and music-sharing sites. Experiments show that PhotoSense provides better browsing experience for photo collections.
Modeling and Mining of Users' Capture Intention for Home Videos

With the rapid adoption of consumer digital video recorders and an increase of home video data, content analysis has become an interesting and key research issue to provide personalized experiences and services for both camcorder users and viewers. In this paper, we present a novel view to tackle this issue, which aims at modeling and mining of the capture intention of camcorder users. Based on the study of intention mechanism in psychology, a set of domain-specific capture intention concepts is defined. A comprehensive and extensible scheme consisting of video structure decomposition, intention-oriented feature analysis, as well as singular-value-decomposition-based intention segmentation and learning-based intention classification is proposed to mine the users' capture intention. Experiments were carried on home video sequences of 90 h in total, taken by 16 persons over the past 20 years. Both the user study and objective evaluations indicate that our proposed intention-based approach is an effective complement to existing home video content analysis schemes
Development of ‘Intelligent Pioneer’ unmanned vehicle

The paper presents the architecture of an unmanned vehicle called `Intelligent Pioneer' developed by the authors. The unmanned vehicle has the ability of navigating in urban environments autonomously without GPS or any other satellite navigation system. The vehicle is able to select its own routes by perceive the traffic signs and interact with other vehicles or pedestrians under the traffic rules. Various urban driving skills including lane keeping, U-turns, parking, obstacle avoidance, and merging into moving traffic have been developed for the vehicle. The vehicle attended the Future Challenge of Intelligent Vehicles in China organized by National Nature Science Foundation of China in 2010 and 2011. `Intelligent Pioneer' finished all of the competition programs and won the first position in 2010 and the third position in 2011.
ZigBee temperature monitoring system based on Wireless Sensor Network

In the paper, a simple Wireless Sensor Network Monitoring System was built based on the Chip CC2530 of TI and ZigBee protocol stack. The paper is mainly targeted at the construction of the ZigBee network and the configuration of the logical type of nodes in the program; it also introduced the composition of ZigBee network node, as well as the function of the Wireless Sensor Network Monitoring System.
The design and control of Amoeba-like robot

Considering the constraint of the rigid structure of the conventional robots in the collapsed environment, this paper proposes a novel robot of whole flexibility, of which the construction materials, the driving materials and the controlling models are all soft. The new robot imitates the locomotion mechanism of the Amoeba, actuated by the IPMC (ionic polymer-metal composites) actuators. Flexible thin film material is made into circle column shape as the skin of the robot. Meanwhile the liquid is injected into the circle column cavity. The IPMC actuators pasted on the skin of the robot and stimulated by regular control signals can make the robot move forwards, backwards, enter the narrow hole and so on. The robot makes it another possibility in the application of disaster search and rescue.
An approach of lane detection based on Inverse Perspective Mapping

Urban lane detection is an essential task for unmanned vehicle system. This paper describes an approach of lane detection algorithm based on Inverse Perspective Mapping, first using overall optimal threshold method to obtain binary image for reducing noise; next using Inverse Perspective Mapping to transform binary image space to top view space; then using k-means clustering algorithm to analysis linear discriminant for reducing interference affect; finally, fitting lane discontinuous on the top view space according road models. Experimental results are presented to demonstrate the effectiveness and superiority of the urban lane detection algorithm.
Efficient video mosaicing based on motion analysis

Presenting more comprehensive information than key frame and any subset of frames, mosaic has attracted a growing attention in recent years as a useful element for a variety of vision tasks. In this paper, we present an efficient approach to video mosaicing based on motion analysis with investigating two important issues that significantly affect the performance of mosaicing. First, given a video shot, a method based on motion entropy analysis is introduced to determine whether the visual content in a shot or video segment is suited to be represented by a mosaic. The second is to decide which subset of frames in the shot is the best to be selected for efficient and effective mosaicing by constructing a global motion path. Experimental comparisons with typical mosaicing method approve that with this approach, the visual quality of mosaic is significantly improved, as well as the computation time is remarkably reduced.
VideoSense: A Contextual In-Video Advertising System

With Internet delivery of video content surging to an unprecedented level, video has become one of the primary sources for online advertising. In this paper, we present VideoSense as a novel contextual in-video advertising system, which automatically associates the relevant video ads and seamlessly inserts the ads at the appropriate positions within each individual video. Unlike most video sites which treat video advertising as general text advertising by displaying video ads at the beginning or the end of a video or around a video, VideoSense aims to embed more contextually relevant ads at less intrusive positions within the video stream. Specifically, given a Web page containing an online video, VideoSense is able to extract the surrounding text related to this video, detect a set of candidate ad insertion positions based on video content discontinuity and attractiveness, select a list of relevant candidate ads according to multimodal relevance. To support contextual advertising, we formulate this task as a nonlinear 0-1 integer programming problem by maximizing contextual relevance while minimizing content intrusiveness at the same time. The experiments proved the effectiveness of VideoSense for online video service.
Viscoelastic analysis on a novel adhesive tread-based footpad for Three-Dimensional climbing robots

This paper proposes a novel tread-based footpad for 3-Dimensional (3D) climbing robots. Different structures for 3D climbing robots were compared. To take advantage of the self-preloading ability, the tread-based footpad was designed as a part of the quadruped climbing robot. The footpad utilizes PU (Polyurethane) adhesive belt to adhere. The preloading of adhesion is performed by the translational motion and rotation output by the robot at the connecting point. The relationship between the attitude angle and the peeling angle was studied, and an optimum attitude angle was provided to maximize the adhesive force. The process of the footpad's lifting was studied as well. Finite Element Method (FEM) was used to simulate the process. In experiments the footpad was tested. The footpad is promising in the fabrication of a quadruped 3D climbing robot for long-time stay on steep-sloped surfaces or even ceilings.
Look Closer to See Better: Recurrent Attention Convolutional Neural Network for Fine-Grained Image Recognition

Recognizing fine-grained categories (e.g., bird species) is difficult due to the challenges of discriminative region localization and fine-grained feature learning. Existing approaches predominantly solve these challenges independently, while neglecting the fact that region detection and fine-grained feature learning are mutually correlated and thus can reinforce each other. In this paper, we propose a novel recurrent attention convolutional neural network (RA-CNN) which recursively learns discriminative region attention and region-based feature representation at multiple scales in a mutual reinforced way. The learning at each scale consists of a classification sub-network and an attention proposal sub-network (APN). The APN starts from full images, and iteratively generates region attention from coarse to fine by taking previous prediction as a reference, while the finer scale network takes as input an amplified attended region from previous scale in a recurrent way. The proposed RA-CNN is optimized by an intra-scale classification loss and an inter-scale ranking loss, to mutually learn accurate region attention and fine-grained representation. RA-CNN does not need bounding box/part annotations and can be trained end-to-end. We conduct comprehensive experiments and show that RA-CNN achieves the best performance in three fine-grained tasks, with relative accuracy gains of 3.3%, 3.7%, 3.8%, on CUB Birds, Stanford Dogs and Stanford Cars, respectively.
Robust lane marking detection under different road conditions

In this paper a new lane marking detection algorithm in different road conditions for monocular vision was proposed. Traditional detection algorithms implement the same operation for different road conditions. It is difficult to simultaneously satisfy the requirements of timesaving and robustness in different road conditions. Our algorithm divides the road conditions into two classes. One class is for the clean road, and the other one is for the road with disturbances such as shadows, non-lane markings and vehicles. Our algorithm has its advantages in clean road while has a robust detection of lane markings in complex road. On the remapping image obtained from inverse perspective transformation, a search strategy is used to judge whether pixels belong to the same lane marking. When disturbances appear on the road, this paper uses probabilistic Hough transform to detect lines, and finds out the true lane markings by use of their geometrical features. The experimental results have shown the robustness and accuracy of our algorithm with respect to shadows, changing illumination and non-lane markings.
Lidar Scan matching EKF-SLAM using the differential model of vehicle motion

Simultaneous localization and mapping is a mobile robot positioning themselves and creating the map of the environment at the same time, which is the core problem of the vehicle achieve the authentic intelligent. EKF-SLAM is a widely used SLAM algorithm based on the extended Kaiman Alter. The EKF-SLAM proposed in this paper based on the differential model of vehicle motion, which consider the vehicle trajectory as many small straight Une segments. The algorithm effectively reduce the positioning error compared with the dead reckoning and has more simplified and generic model compared with the EKF-SLAM algorithm based on vehicle kinematics model. Meanwhile, it has a lower requirements on the hardware acquisition system. The algorithm is more robust than the traditional EKF-SLAM So the algorithm will have a certain reference value on the SLAM research and provide a new way on the SLAM research based on the differential model of vehicle motion.
Obstacle-climbing capability analysis of lunar rover based on double-half-revolution mechanism on lunar soil

Taking a new type of lunar rover which is based on a double-half-revolution mechanism as the research object, based on the force analysis between the wheel-leg and lunar soil, its obstacle-climbing force model on lunar soil was established. As the obstacle-climbing model of uneven terrain was relatively complicated and the numbers of independent equation were less than those of unknown variables, a new evaluation index of the obstacle-climbing capability was presented. Taking the friction feasible region as the evaluation index, the larger the friction feasible region, the better the obstacle-climbing capability, and when the friction feasible region the wheel-leg suffered did not exist; the mechanism would not have the obstacle-climbing capability under the initial conditions. When giving the slope angle and obstacle height, the forward obstacle-climbing capability of this lunar rover was analyzed on lunar soil, including single wheel-leg obstacle-climbing and two wheel-legs obstacle-climbing simultaneously. Simulation results show that the feasible solution regions of T1, T2, T3 and T4 are affected by applying specific frictional coefficient.
A bone reaming system using micro sensors for Internet force-feedback control

The development of a medical surgical tool, packaged with micro sensors for transmission of supermedia information over the Internet is described in this paper. We define supermedia as a set of communication media, which encompasses acoustic, force, visual, audio, temperature, tactile, and chemical (e.g., taste and smell) information, and which can be physically experienced by a communicator. In this project, we specifically develop supermedia capability for a bone-reaming system that is used for intramedullary fixation procedure of fractured bone treatments. Thus far, transmission of temperature, force, and pressure information from MEMS sensors over the Internet has been demonstrated. Force-reflective control over the Internet using force information from a micro tip has also been shown. We have also packaged a MEMS pressure sensor inside a bone reaming guide-rod and proved that pressure variations inside a long cavity that simulated the environment inside a bone can be monitored, even with the guide-rod rotating up to 600 rpm. This paper describes our experimental methods and gives the experimental results for these accomplishments.
Mico-displacement measurment and analysis of one antenna box structure based on temperature compensation

In engineering applications, the material strength and stiffness have a great influence on the accuracy of one antenna box structure, and temperature is another influence factor. In this paper, taking one antenna box structure for example, considering the temperature compensation of the structure, a micro-displacement measurement system was built to realize the micro-displacement measurement of the structure. The finite element method was used to verify and prove the reliability of this test method.
Autonomous Grasping of a Space Robot Multisensory Gripper

Most robot grippers can hardly be applied to space service due to their devoid of the ability of outputting large force, autonomously making decision and sensing the environment. In this paper, a space underactuated gripper which can stably grasp various objects based on fewer actuators, large force and autonomous decision and multisensory information feedback is introduced. Firstly, the versatile grasping patterns of the gripper with characteristics of underactuation are presented. The multiple sensors are mounted on the gripper including PVDF contact force sensors, a line structure light sensor which detects grasped object approximate shape and volume, and a wrist force sensor which detects the grasped object mass. Secondly, autonomous grasping which is characterized by autonomous decision-making and control is focused on. Control strategies are also proposed to make proper prosthetics and stable grasping according to force sensors information. The grasping rules are extracted from original experiment sample data. Through fuzzy neural network, grasping map is established among comprehensive fuzzy features, including grasping task and object features, and the grasping patterns. Finally, the experimental results demonstrate that the gripper can achieve autonomous and stable grasping
Design and Implementation of a 6-DOF Robot Control System Based on CAN Fieldbus

This paper presents the design (hardware and software) and implementation of a control system for a 6-DOF robot. The motivation of the work is to explain the use of the architecture on available real-time distributed control systems. Based on the analysis of functions and configuration, we design a systemic modularized control structure with CAN field bus which is used to connect distributed hardware and software modules. The superiority of CAN field bus and how it has been implemented to construct control system coupled with electromechanical devices are described. Then the analysis gives the mechanical structural characteristics and corresponding control principle of the robot. Finally, an evaluation of the performance of the robotic control system is provided. The experiment with the prototype proves that both the accuracy and efficiency can be achieved simultaneously by the control system based on use of CAN field bus. It is believed that attributes observed in this control system can be used for automatic production, space exploration, treatment operation, etc.
When multimedia advertising meets the new Internet era

The advent of media-sharing sites, especially along with the so called Web 2.0 wave, has led to the unprecedented Internet delivery of community-contributed media contents such as images and videos, which have become the primary sources for online advertising. However, conventional ad-networks such as Google Adwords and AdSense treat image and video advertising as general text advertising by displaying the ads either relevant to the queries or the Web page content, without considering automatically monetizing the rich contents of individual images and videos. In this paper, we summarize the trends of online advertising and propose an innovative advertising model driven by the compelling contents of images and videos. We present recently developed ImageSense and VideoSense as two exemplary applications dedicated to images and videos, respectively, in which the most contextually relevant ads are embedded at the most appropriate positions within the images or videos. The ads are selected based on not only textual relevance but also visual similarity so that the ads yield contextual relevance to both the text in the Web page and the visual content. The ad insertion positions are detected based on visual saliency analysis to minimize the intrusiveness to the user. We also envision that the next trend of multimedia advertising would be game-alike advertising.
Grasp characteristics of an underactuated robot hand

An underactuated robot hand with three fingers has been developed to achieve planar pinch grasp and enveloping grasp. The grasp characteristics of the underactuated hand are studied. In planar pinch grasp, which depends on two or three distal phalanges to work together, the key factors to influence grasp stability are investigated, and the sufficient and necessary conditions for stable grasp are proposed with force-closure conception. The allowed maximum external wrench is calculated when the grasp can't meet force-closure condition. In enveloping grasp, the phalanges driven by an actuator can't be controlled independently and have local motion lead to unstable grasp. Based on the definition of grasp configuration and driving force, the relationship between grasp configuration and external wrench is studied. The transition difficulty of grasp configuration is employed to evaluate the stability of enveloping grasp. Finally, some cases of stimulation are given to validate the evaluation.
A Sliding Mode Control approach to longitudinal control of vehicles in a platoon

In the actual driving conditions, such as a smooth curved path or complex road traffic conditions, the velocity of the platoon often changes in acceleration or deceleration, which will cause the increase of the spacing error obviously, even cause the platoon system instability. So a robust control technique is applied to solve this problem. The robust control strategy adopted in this paper is Sliding Mode Control (SMC), which has a great robustness to system parameters change and external disturbances. Two controllers are designed to control the velocity of vehicles and direction in the platoon in this paper. The longitudinal controller is controlled to regulate the longitudinal distance between vehicles at a desired spacing using the sliding mode control technique. The lateral control aligns the vehicle direction by the steering controller which is actually a PID controller. The experiment simulations show that the designed model can realize the stability of vehicle tracking control. The designed two controllers can ensure that the vehicle stays on the reference path, and the platoon has a relatively small spacing error and lateral error.
Dynamic motion planning for autonomous vehicle in unknown environments

A dynamic motion planning approach for an autonomous vehicle navigated without GPS and unmanned driven in unknown environments is presented. The unknown environments bring several technology challenges, including high-speed operation, complex interaction with environment, parking in unstructured lots, and passing dynamic obstacles. In this approach, we combine the global path planning and the local path planning with a hierarchical structure. The exploration method to navigate in unknown environments is described in detail. An autonomous vehicle, Intelligent Pioneer, was developed to verify the dynamic motion planning approach. The Intelligent Pioneer showed good performances in dynamic motion planning and won the first prize of the 2010 Future Challenge of Intelligent Vehicles in China.
Interactive Multimodal Visual Search on Mobile Device

This paper describes a novel multimodal interactive image search system on mobile devices. The system, the Joint search with ImaGe, Speech, And Word Plus (JIGSAW<formula formulatype="inline"><tex Notation="TeX">${+}$</tex> </formula>), takes full advantage of the multimodal input and natural user interactions of mobile devices. It is designed for users who already have pictures in their minds but have no precise descriptions or names to address them. By describing it using speech and then refining the recognized query by interactively composing a visual query using exemplary images, the user can easily find the desired images through a few natural multimodal interactions with his/her mobile device. Compared with our previous work JIGSAW, the algorithm has been significantly improved in three aspects: 1) segmentation-based image representation is adopted to remove the artificial block partitions; 2) relative position checking replaces the fixed position penalty; and 3) inverted index is constructed instead of brute force matching. The proposed JIGSAW<formula formulatype="inline"><tex Notation="TeX">${+}$</tex></formula> is able to achieve 5% gain in terms of search performance and is ten times faster.