In order to solve the problem of recommendation of points of interest, this paper proposes an algorithm of recommendation of points of interest based on user check-in space clustering.According to the administrative region information of interest points in LBSN and the distribution characteristics of user check-in, a new spatial clustering algorithm is designed in this paper.First, according to the distribution of user check-ins, the whole data set was clustered in cities, and the user rating information was normalized.Then the recommendation scores of candidate recommendation points were calculated according to the user preference model, social relation model and geographical correlation model.The final recommendation list is obtained by calculating the recommendation probability of the points of interest.Experiments on the Yelp data set show that the proposed algorithm has higher precision and recall rate than the traditional algorithm.
In this paper, we introduce an anchor-free and single-shot instance segmentation method, which is conceptually simple with 3 independent branches, fully convolutional and can be used by easily embedding it into mobile and embedded devices.Our method, refer as EOLO, reformulates the instance segmentation problem as predicting semantic segmentation and distinguishing overlapping objects problem, through instance center classification and 4D distance regression on each pixel.Moreover, we propose one effective loss function to deal with sampling high-quality center of gravity examples and optimization for 4D distance regression, which can significantly improve the mAP performance.Without any bells and whistles, EOLO achieves 27.7% in mask mAP under IoU50 and reaches 30 FPS on 1080Ti GPU, with single-model and single-scale training/testing on the challenging COCO2017 dataset.For the first time, we show the different comprehension of instance segmentation in recent methods, in terms of both up-bottoms, down-ups, and direct-predict paradigms.Then we illustrate our model and present related experiments and results.We hope that the proposed EOLO framework can serve as a fundamental baseline for a single-shot instance segmentation task in Real-time Industrial Scenarios.
In this paper, we proposed the FPGA based digital implementation of synchronization methodology for 6-D chaotic systems via nonlinear feedback adaptive control technique.We derived new results for the adaptive controllers and the parameter update laws based on Lyapunov stability theory to achieve the synchronization between identical 6-D chaotic systems.Since the digitization of chaotic synchronization is necessary for digital communication, the proposed adaptive synchronization methodology is implemented in digital circuits based on Field Programmable Gate Array chip.The digital chaotic signal also generated using MATLAB simulink and Xilinx System Generator technology.The numerical simulation and FPGA outputs are used to prove the robustness and effectiveness of our proposed methodology.
Frequent subgraph extraction from a substantial number of small graphs is a crude activity for some, information mining applications.To extricate frequent subgraphs, existing systems need to identify countless which is super straight with the cardinality of the dataset.Given the huge developing volume of graph information, it is hard to play out the regular subgraph extraction on a unified machine proficiently.Along these lines, there is a need to explore how to effectively play out this extraction over expansive datasets utilizing MapReduce.Parallelizing existing strategies straightforwardly utilizing MapReduce does not yield great execution as it is hard to adjust the remaining task at hand among the figure hubs.This structure receives the MRFSE procedure to iteratively remove Frequent subgraphs, i.e., all incessant size-( i+1) subgraphs are created dependent on continuous size-I subgraphs at the ith emphasis utilizing a solitary MapReduce work.To productively separate successive subgraphs, arrangement and mining stage are utilized which incorporates isomorphism testing to wipe out copy designs.Frequent subgraphs extraction should be possible productively and effectively by utilizing a disseminated domain named Hadoop MapReduce structure.
This paper proposes an algorithm that accurately detects the grid-shaped mosaic region used to cover certain regions of video data based on edge projection.The proposed algorithm first detects Canny edges from the image and detects candidate regions of the mosaic using horizontal and vertical line edge projection.The actual mosaic regions are then finally detected by filtering candidate regions of the mosaic using geometric features.Experimental results show that the proposed algorithm detects the area corresponding to the mosaic block more accurately than the other detection methods from various input images.
Speech Recognition is a tremendous application from the history that is identification and conversion of spoken words into text.The performance and quality of work had increased a lot.This performance lead to the research work on Emotion Recognition based on the language spoken that is obtaining the kind of emotion from the spoken speech which is an application based on human-robot interactions.Emotions can be recognized in a better way using Speech processing, Artificial Intelligence techniques and linguistic semantics.Systems are given training in such a way to detect the emotions from the spoken utterances.This paper contains about the survey from the history to the present works that took place in the speech emotion recognition and also the experiment results.The survey contains about the works that took place from the by different scientists and their usage of different features, classifiers etc.The paper also holds three categories, one is different databases that are involved, second is what features are involved for representation of speech and third about the classification schemes.The survey also includes the conclusions of performances and limitations of current speech emotion recognition.
The data analysis in this study was conducted to compare the advantages and disadvantages of the 1.5 T 3D TOF HSR method and the 3.0 T 3D TOF SR method, in order to determine whether 1.5 T can complement the image quality of intracranial vessels For SNRs and CNRs, significant results were obtained owing to the high scores of 3.0 T (p<0.05).In the qualitative analysis, significant results were obtained for the A3, M3-M4, and P3-P4 segments owing to the high scores of 1.5 T (p<0.05).However, both 1.5 T and 3.0 T 3D FFE TOF methods provided images that allowed qualitative assessment.The findings of this study confirmed that 1.5 T 3D HRS MRI can complement 3.0 T 3D SR MRI.
In this paper, the mixed H-infinity and Kalman filter is proposed for multiple target tracking in the video arrangements. Here, the proposed system will be the joined execution of Kalman filter and the H-infinity filter. The Kalman filter is the best filter that is a linear combination of the measurements. That is why; it is widely used in tracking systems. The H∞ filter, also called the mini-max filter. The H∞ filter does not make any assumptions about the noise and it required only last time step and current state estimation for object tracking. Consequently, there would be no necessity for a high limit of computational stockpiling. This mixed filter uses a lower gain in order to obtain better performance, where as the pure H-infinity filter uses a higher gain because it does not take Kalman filter performance into account. The mixed Hinfinity and the Kalman filter, used to find the location and speed of the objects when objects are moves with a certain motion law. The Kalman filter doesn't limit the mean square error. In this way, the H-infinity filter limits the mean square error and also utilized to limit the impact of unexpected noise whose insights are obscure. Usage of the proposed system was implemented in MATLAB and the execution of this system has better execution.
Manually creating and editing the motion of a character handling a ball is a very cumbersome task because the character's motion must be synchronized with the movement of the ball in time and space according to the laws of physics.Thus, we propose a convenient way to automatically synthesize character animation for the control of a ball by using motion capture data.Because it is difficult for a beginner to control a ball skillfully, we do not use an actual ball.Instead, we capture motions that mimic the control of a ball.We analyze the motion capture data to find the frames and locations where the character interacts with the ball and create ball movement that follows the laws of physics.We can then synthesize character animation for the depiction of ball control in real time.
A system for spatial drawing must have a display device that shows stereoscopic images to the user, a controller serving as a brush for drawing, and a function that creates a line and a curved surface and visualizes the virtual space.Herein, a software framework was designed for spatial drawing by analyzing the functions for spatial drawing applications in a virtual environment based on existing studies and produced a virtual reality spatial drawing application with virtual drawing tools.The application employed a traditional painting metaphor.Furthermore, a brush module and a palette module were designed for the spatial drawing interface and linked to the line and surface generator modules to change drawing attributes, e.g., color and texture.
Biosensors have played a major role in diagnosis of various diseases and are also associated with detection of micro-organisms and other biological components.There are various types of biosensors available in the field, each having benefits one over the other.This paper explains the basic theory and operational setup of SPR based biosensors which are fast in their performances and are real time implemented.These plasmonic based biosensors includes waveguide arrangements along with a Au/Ag bimetallic enhancement concept.One of the benefits of coupling of light source with surface electrons will give raise to surface Plasmon which is very efficient in recognition of biomolecules without any external biomarkers.Placing a second metal layer above the dielectric layer as well as below, metal-insulator-metal (MIM) waveguide had been developed.These structures allow extremely high model confinement of light.Using this structure biological analysis of blood components have been performed and the resultant signature graphs are obtained in terms of resonant frequency and wavelengths.These numerical simulation outcome shows the resonance dips of the structure, high resonant transmission contrast ratio and the resonance wavelength has a linear relationship with the refractive index of dielectric material therefore the aperture.The numerical simulation results obtained from the transmission spectra are used to analyze the sensing characteristic of the structure.The sensitivity of the biosensor is also calculated.
Traditional human feature extraction algorithm based on Gabor transform folds the human face image and multiple scales and multiple direction kernel function for Gabor to obtain Gabor human feature with sampling and cascade. The obtained Gabor feature dimension of human face is high, the recognition process wastes time rather without rotation invariance, and performance of human face figure decreases at plane rotation. LBP is used in operator for texture analysis due to algorithm thought is sample, computation complexity is low and discernment is strong, etc. The above-mentioned analyzed and used widely for several years, LBP operator has fortissimo gray invariance and rotation invariance to overcome the problems of rotation shifting and uneven illumination. This dissertation adopts feature extraction method for combination of Gabor wavelet and LBP to research human face recognition to put forward to LBP algorithm with uniform pattern for improving the accuracy of human face feature recognition and flexibility of practical operation. The dissertation provides optimization selection and integration for human face feature extracted by Gabor wavelet and LBP to put forward to improved algorithm: feature extraction methods combined with 2D-Gabor wavelet and uniform LBP. This dissertation algorithm makes progress to improve recognition rate and decrease data redundancy with flexibility and effectiveness for human face recognition.
The purpose of this paper is to examine the role of business incubators in sustaining the growth and survival of startups.In addition, this study aims to explore how business incubators provide different facilities to startups and the effectiveness of these services and facilities.Business incubation systems in Pakistan are in their early stages and face several issues.This study focuses on developing a better understanding of business incubators.The standardized questionnaire technique is used to gather information on all areas of concern pertaining to startups by focusing on their survival and growth.The scale used in the questionnaire is the five-point Likert scale.The research sample of this study comprises startups located at seven business incubators -Plan9, Plan10, LUMS, NSPIRE, NUST, UETP and PASHA.The findings of the study reveal that the incubation facilities, financing, technology R&D, sources of R&D, joint R&D projects, network opportunities, R&D projects, current benefits, and incubator business objectives have a significant positive relationship with incubator performance.All these factors facilitate measurement of the incubator's performance.Effective incubation of startups will help create new jobs and wealth.The results provide guidelines to business incubators to take necessary actions for the survival and growth of startups.This study has been conducted in collaboration with the founders of startups, and it is the first of its kind with respect to Pakistan.
