Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on classifier of multi-dimensional data based on radar chart mapping

Analyzes the basically methods that radar chart presents multi-dimensional data,and then introduces feature selection and information fusion technique based on radar chart feature.A novel method based on chart feature for designing the classifier of multi-dimensional data is proposed,which uses radar chart to map.This method is also simple and intuitionistic.Multi-dimensional data and applied fuzzy rules to recognize the radar chart in order to achieve automatic classification.Different category multi-dimensional data forms different radar chart.Radar chart feature shows the mostly data feature.The result of experiment presents better result of category and precision.
A Navigation Aid for Blind People Based on Visual Simultaneous Localization and Mapping

Most navigation aids for blind people require users to equip various equipment and multi-sensor subsystems for environmental detection. This study integrates the visual simultaneous localization and mapping system with pre-established maps to develop a navigation aid system for blind people. The system operates similarly to how Google Map uses pre-established environmental maps and landmarks. While the user walks, the system reads the map in the database and synchronizes feature points from the visual simultaneous localization and mapping system onto the environment map. In addition, the aid employs audio cues to notify users of signpost information and enables users to make inquiries on specific destinations via human–machine interaction.
Segmented detail separation and enhancement considering the visual CSF property for HDR imaging

High dynamic range (HDR) images are rendered through base-detail separations. The representative detail preserved algorithm iCAM06 has a tendency to reduce the sharpness of dim surround images, because of the discrete calculation of the fast-bilateral filter (FBF). This paper proposes a noble base-detail separation and detail compensation technique using the contrast sensitivity function (CSF) in the segmented frequency domain. Experimental results show that the proposed rendering method has better sharpness features than previous methods correlated by the human visual system.
An Experimental Research on Brain-Computer Interface Based on Steady State Visual Evoked Potential

For acquiring steady state visual evoked potential(SSVEP)applied to brain-computer interface system,a method combining average and FFT is proposed.Input signal are obtained by their frequency figure of SSVEP.Times of average and best color of visual stimulation are confirmed by experiments.A method of acquiring SSVEP with mixed visual stimulation is studied.Experiments showed that SSVEP can reflect the control purposes of users and can be applied to BCI system.
IoT-Based Solid Waste Management Solutions: A Survey

With the increase of population density and the rural exodus to cities, urbanization is assuming extreme proportions and presents a tremendous urban problem related to waste generation. The increase of waste generation has been considered a significant challenge to large urban centers worldwide and represents a critical issue for countries with accelerated population growth in cities. The Internet of Things (IoT) and cloud computing offer an automation possibility through cyberphysical systems that will change the way solid waste management is performed. Considering IoT requirements, a review analysis of waste management models available in the literature is performed in detail in this paper. Then, a deep review is undertaken of the related literature based on IoT infrastructure for efficient handling of waste generated in urban scenarios, focusing on the interaction among concessionaires and waste generators (citizens) from the perspective of a shorter collection time with reduced costs, as well as citizenship promotion. An IoT-based reference model is described, and a comparison analysis of the available solutions is presented, with the goal to highlight the most relevant approaches and identify open research issues on the topic.
An IPv6 Address Assignment Protocol Based on Multi-agents for Wireless Sensor Networks

The auto assignment of IP address is required in order that the wireless sensor networks can be applied effectively and communicates with the Internet easily.In this paper,we present SNMAAP (Sensor Networks Multi-agents Address Assignment Protocol),an IPv6 address assignment protocol based on multi-agents for sensor networks,utilizing the IPv6 to meet the wireless sensor network requirement of considerable network addresses.By using agent nodes in the network,not only each node can get an IP address in a short period of time,but also the probability of the address collision and overhead is low.We simulate the SNMAAP and the other two address assignment protocols,the IPv6 Stateless Auto-configuration and MANETconf,on the OPNET Modeler.The simulation results demonstrate that under the same condition,SNMAAP guarantees a unique IP address assignment and has lower latency,communication and duplicate address detection overhead.
Generation Mehtod of Network Attack Graphs Based on Privilege Escalation

After researching a variety of attack graphs generation methods,this paper proposes a related algorithm based on privilege escalation,and designs an effective tool to generate attack graphs.This tool describes network attack model in database language,which including 3 attributes that is host description,network connectivity and exploit rule,and stores network configurations and host information into database automatically.Attack affair graph is generated according to the dependency algorithm that integrates the breadth-first forward exploration and the backward.The attack graph can achieve the whole analysis of network security.
A Text Classification Method Based on Ontology

Text classification is an important research issue of intelligent science,whose emphasis is the precision.Using ontology as a dictionary has improved the precision of classification,but the own architecture of ontology has been ignored,and the effect of Multi-Classification and Multi-label has no modification.The structure of ontology is a well classification standard,which can improve the result of the problem of Multi-Classification and Multi-label.This paper proposes a text classification method guided by ontology,and based on fuzzy mathematical programming.It uses the concepts of ontology as the classes,and maps a text to a concept,according to some predefined rules and parameters for classification.Experiments show that the proposed method can generate more detailed result,and it shows better generalization ability.
Cascade MQDF classifier for handwritten character recognition

The accuracy of unconstrained handwritten character recognition is improved by a cascade MQDF classifier. The cascade structure based ensemble method combines recognition results at the measurement level. The generalized recognition confidence is used as the measurement of recognition result. The algorithm uses multilayer Gaussian models to elaborately descript the sample distributions to improve the recognition rate. The paper then uses the maximum likelihood model to interpret the ensemble algorithm mechanism. The algorithm was applied to the HCL2000 and THOCR-HCD handwritten Chinese character recognition databases and achieved 10.75%、 9.82% and 25.31% error reductions.
Internet Storage Service Model Based on IPv6

With rapid increase of the requirement for remote data storage and backup,this paper proposes an Internet storage service model based on IPv6.It designs an Internet storage access protocol in application layer,and proposes a secure storage model based on the features of IPv6.The goal is to provide a standard and secure remote storage service for the next generation Internet.
A Review on Continuum Robot

As a novel biologically inspired robot,the continuum robot features a kind of flexible "invertebrate" backbone with no discrete joint and rigid link.The continuum robot has excellent bending ability,good adaptability to unstructured and highly congested environments.It not only can grasp or grip object with the end-effector attached at the end of the robot, like traditional robots,but also can grasp object by using whole arm manipulation.In this paper,the bionics principles and structure characteristics of continuum robot are analyzed,the present research state of the continuum robot is reviewed,the potential application is foreseen,and the problems needing further research are discussed.
Color Image Segmentation Algorithm Based on Region Growth

Color image with complicated texture is insufficiently dealt with a traditional seed region growth method.Aiming at this problem,an improved seeded region growth method to segment color image is presented.The research is based on YCbCr model.The texture features are obtained by discrete cosine transform.The seeds and seeded region are produced automatically.The region-merging is used to improve the image segmentation result.Experimental results show the algorithm can effectively improve segmentation accuracy for different image natures.
Looping minds: how cognitive science exerts influence on its findings

Drawing on the distinction between natural and human kinds, I will discuss the looping effects of human kinds through the lens of contemporary cognitive (neuro)science. I will try to show that cognitive science is mainly in the business of investigating, understanding and explaining human kinds. As new conceptualisations of the human mind, agency and our nature are being created (by, for instance, neuroscience), they open up the possibility for new, different understandings of what it means to be a human being. This, I will argue, can change how people think and behave and thus change the very phenomena cognitive science investigates. Consequently, cognitive science can affect its very (future) findings. This holds especially true when society embraces new conceptualisations of the human mind and new ways of self-understanding become part and parcel of social discourse, activities, and/or structures. The quest for understanding the human mind, I will claim, is a looping journey, where what we "discover" about the human mind is inherently dependent on how we, as human beings, understand ourselves; and how we understand ourselves is, to a certain degree, dependent on how science understands us and on how we interpret what it has to say about our nature. At the end of the article, this will lead me to consider cognitive science as an intrinsically ethical endeavour.
A Survey on Software Watermarking

With the rapid development of software industry, the copyright protection of software product already becomes a very important issue. In this paper, the software watermarking technique is presented in detail. An overview of software watermarking including the taxonomy, the methods of attacking, the current algorithms, and their advantages and disadvantages are presented in this paper. Finally the state of arts and possible new directions of software watermarking are also stated.
Predictive Methods of Always Best-Connected Networks in Heterogeneous Environment

Heterogeneous networks are comprised of dense deployments of pico (small cell) base stations (BSs) overlaid with traditional macro BSs, thus allowing them to communicate with each other. The internet itself is an example of a heterogeneous network. Presently, the emergence of 4G and 5G heterogeneous network has attracted most of the user-centric applications like video chatting, online mobile interactive classroom, and voice services. To facilitate such bandwidth-hungry multimedia applications and to ensure QoS (quality of service), always best-connected (ABC) network is to be selected among available heterogeneous network. The selection of the ABC network is based on certain design parameters such as cost factor, bandwidth utilization, packet delivery ratio, security, throughput, delay, packet loss ratio, and call blocking probability. In this chapter, all the above-mentioned design parameters are considered to evaluate the performance of always best-connected network under heterogeneous environment for mobile users.
Survey on the Networks-on-Chip Interconnection Topologies

Along with the development of device,process and application technology,chip multiprocessor is becoming the mainstream technology.As the scale of chip multiprocessor as well as the number of integrated on-chip cores is getting larger and larger,the network-on-chip,which is dedicated to the interconnection and communication among on-chip cores and other components,is becoming one of the performance bottlenecks of chip multiprocessor.The topology of network-on-chip defines the physical layouts and the interconnection patterns of network nodes,determines the cost,latency,throughput,area,fault tolerance and power of network-on-chip,and impacts on the network routing policies,the placement and routing designs of network chips.Therefore,the topology is one of the key technologies of network-on-chips.The paper compared various topological structures of network-on-chips in brief,analyzed their performances,and proposed recommendations for future research on the topology of network-on-chip.
Research on page ranking algorithm based on K-means clustering algorithm and information entropy

Through the analysis of the classic PageRank algorithm,it has several defects on biasing history web pages,theme drifting,dividing the weight of each hyperlink as equal and so on,some theories on vector space model and information entropy defined in information theory are brought in.As a result,an improved algorithm called PRKE algorithm is proposed.Web is represented by using a vector which constitutes of several key words which could represent the character of the current web,keeping the weight of a key word in a web as the weight of each component in the vector.Then using the K-means clustering algorithm to cluster for those existed web and use the information entropy to represent the weight of each cluster after the clustering to realize the macroscopical sort.At last,by adding some parameters about time and theme similarity into the classic PageRank algorithm to realize the microcosmic sort.The experimental result shows that the improved algorithm acquires higher improvement in both retrieve accuracy and page hit rate than the classic PageRank algorithm.
An Improved Parallel Algorithm for Mining Association Rules

Based on investigation of mining association algorithms rules,the paper analyzes parallel association rules algorithm in details.At the same time,the parallel calculating architecture of data mining is given.To overcome problems existing in performance and efficiency,algorithm for parallel mining association rules based on computing server as the central processor is put forward,which can develop each advantage of local processor and reduce the cost of communication among local processor.Theoretic analysis and experimental result show that it holds better calibility and ability to deal with massive data,especially under the condition of the more local processor number.
Finger vein recognition based on Deep Convolutional Neural Networks

In the process of a finger vein image acquisition, finger vein images are susceptible to external factors like finger posture and light source conditions, which will result in poor recognition accuracy. Therefore, a finger vein recognition method based on improved convolution neural net work is proposed to improve the accuracy and robustness of the image recognition. Firstly, the collected finger vein image is preprocessed by image segmentation, finger root key point location and image extraction in the region of interest (ROI). Secondly, according to the application context of finger vein recognition, the convolution neural network structure is adjusted appropriately, and the output of convolution layer is standardized in batches. The optimized neural network is used to automatically extract, classify and identify the features of the preprocessed images. A large number of experiments were performed on public finger print data sets of Shandong University. The optimal recognition rates are 90% respectively. The experiments verify the effectiveness of this method.
DHT-OFDM Based Spatial Modulation for Optical Wireless Communication

The combination of orthogonal frequency division multiplexing (OFDM) and spatial modulation (SM) can enhance the capacity of optical wireless communication (OWC) systems with low complexity. In this paper, we propose a novel SM scheme for intensity modulation/direct detection (IM/DD) OWC systems by employing discrete Hartley transform based OFDM (DHT-OFDM). Due to the use of DHT with one-dimensional constellations, the Hermitian symmetry constraint, which is generally imposed in conventional discrete Fourier transform based OFDM (DFT-OFDM) to obtain a real-valued output signal, is not required in DHT-OFDM. As a result, DHT-OFDM based SM can achieve much higher spectral efficiency than that of DFT-OFDM based SM in OWC systems. Simulation results show that, for an indoor $4\times 4$ SM-OWC system with a spectral efficiency of 6 bits/s/Hz, DHT-OFDM achieves a remarkable 4.5-dB transmit signal-to-noise ratio reduction for an overall bit error rate of 10-3 in comparison to conventional DFT-OFDM.
Regional feature based fast human face detection

Automatic face recognition (AFR) is one of the most attractive and challenging tasks in fields of computer vision and pattern recognition, the first critical step of AFR is face detection. A fast face detection algorithm based on regional feature is proposed. In contrast with the award winning mosaic method, three main improvements were introduced here: 1). organ based blocking scheme and more intuitive mosaic rule design, 2). sub block type adaptive technique according to different face shape, 3). fast organ based rough detection and hierarchical local searching method. Also directional gradient statistics were used as sub block feature instead of absolute gray value ones. Experimental results show that the algorithm can find the face rapidly with relative high accuracy, with little limit to the complexity of background, lighting condition, face size, person number, resolution of the image etc.
Chinese short text clustering based on dynamic vector

Since Chinese short text is short of keywords and full of anomalous words,it brings about short text similarity drift and the traditional text clustering method is not directly suitable for short text clustering.To solve the problem of sparse key-words and similarity drift in short text segments,this paper proposes a new method to build dynamic text vector by text similarity based on HowNet.This method can measure the similarity between short text segments by dynamic text vector,then find short text relationship,so as to relieve these two characteristics'bad influence on the clustering performance and therefore to gain a better clustering result.Experiments show the method can get better performance in Chinese short text clustering,compared with traditional method.
High Effective Two-round Remote File Fast Synchronization Algorithm

Fast remote file synchronization has a widespread application in many scenarios such as the file backup and recovery, Web and ftp site mirroring, content distribution network, Web access and so on. This paper presents a high effective two-round fast synchronization algorithm tpsync which combines content-based variable-sized chunk and fixed-sized sliding block methods. tpsync is implemented with two rounds. For the first round, tpsync adopts content-based variable-sized chunk to locate the local change between similar files in coarse-grained scale. In the second round, tpsync looks up the differential data in the local changed data segment with fixed-sized sliding block method in fine-grained scale, and finally achieves the file synchronization by two-round data interaction. This paper executes a comparison experiment between tpsync and the traditional single-round synchronization method rsync. Extensive experiments on text, binary and database files demonstrate that tpsync can achieve a higher performance on average synchronization time and the amount of network traffic data than rsync.
New semi-fragile watermarking for JPEG image authentication

This paper presented a watermarking scheme for JPEG image authentication.The watermark was generated based on the relative sign and magnitudes of Discrete Cosine Transform(DCT) coefficients which were invariant due to an important property of JPEG compression.Combined with an effective method to include all the coefficients either explicit or implicit,the proposed algorithm improved its security level against malicious attacks in transform domain,without embedding more watermarking information in the original image.At the same time,an identification of false tampered blocks in the proposed authentication algorithm improved the accuracy of locating tampered areas.Analysis and experimental results are provided to demonstrate that the watermarked image possesses good perceptual transparence,and that the proposed algorithm takes JPEG compression as an acceptable manipulation.Meanwhile,it is sensitive to other malicious attacks and can locate the tampered areas.
Digital signal processing techniques for peak-to-average power ratio mitigation in MIMO–OFDM systems

The focus of this thesis is to mitigate the very large peak-to-average transmit power ratios (PAPRs) inherent to conventional orthogonal frequency division multiplexing (OFDM) systems, particularly in the context of transmission over multi-input multi-output (MIMO) wireless broadband channels. This problem is important as a large PAPR generally needs an expensive radio frequency (RF) power amplifier at the transmitter due to the requirement for linear operation over a wide amplitude range and such a cost would be compounded when multiple transmit antennas are used. Advanced signal processing techniques which can reduce PAPR whilst retain the integrity of digital transmission therefore have considerable potential for application in emergent MIMO–OFDM wireless systems and form the technical contributions of this study. [Continues. ]
MUSICAL GAMES IN CLASSROOM TEACHING

Contemporary concept of education involves a student maximally engaged intellectually, independent in gaining new knowledge and directly involved in the teaching process. Bearing this in mind, in the initial teaching it is necessary for students to be maximally engaged as active factors in the teaching process. One of the way, close and familiar to them, is to achieve it through the game. Teaching contents in primary music education are adequate for application of various didactic music games which shall engage the students in many ways and enable them to acquire elementary concepts in theory of music through play and fun. Therefore, the main goal of this paper was to estimate the adoption of dynamics as the variation in loudness and their marking in the musical notation through didactic music games. The sample consisted of 240 students of the third grade of primary schools in Vranje. , On the basis of the assessment scale index the absorption and reproduction of dynamic variations through the game „Izgubljeno pile“ was examined. The best results were achieved by the students for the strong dynamic performance (forte), then the gradual increase (crescendo), while the weaker results were achieved for reproduction of soft dynamic performanse (piano) and gradual decrease (decrescendo). The obtained results can contribute to the overcoming of dynamic shading, as well as in the use of didactic music games as a Special purpose songs when learning from a musical notation.