Miracle-dz/UniFAR-FTUs huggingface dataset:
Dominant interaction group detection in team sports

With sport performance analysis shifting towards a team’s overall behaviour, the need for automatically discovering formations, such as players temporarily forming a common group of interactions, emerges to complement the coach’s observations. We propose a novel framework to detect a structured group of players, encoded in the form of contextdependent team players’ interactions. In real scenarios, considering a tendency among the players’ movements to occupy a common interested region on a sport field, we predict the future candidate area of group interactions (tendentious zone) before the group formations occur. Consequently, the tendentious zone guides the future players’ movements and provides prior information about their future positions on the field. Building a graph of all players’ positions and considering their motion stability towards the tendentious zone, we aim to discover an optimal subgraph indicating a dominant group of players by maximising the similarity among them. To quantify the similarity of any two players, we consider their relative proximity as well as the common social attention model. Experiments on new sports datasets consistently show the superiority and effectiveness of the proposed approach over existing group detection methods.
Timing jitter in digital filtering of analog signals

Effects of timing jitter in digital filtering of analog signals are analyzed. Jitter may be introduced into the system when the incoming analog signal is being sampled and when the samples of the output of the digital filter are being read out for reconstruction back into an analog signal. These two jitters are called readin and readout jitters, respectively. General expressions are derived for the spectrum of the analog output in the presence of jitter and for the mean-square error introduced by the jitter. Four specific cases are then considered. They are readin jitter only, readout jitter only, independent jitter, and locked jitter. In each case, the general expression for the spectrum of the analog output is reduced to a more explicit form, and a simple upper bound on the mean-square error is derived. An example is included to illustrate the effect of high-frequency jitter and the effect of jitter due to 60-cycle pickup.
Differential evolution algorithm for multi-project resource leveling problem

Abstract In this paper, the model of RLP which in the multi-project environment is expanded to the RLPMP using the minimum of the variance of total resource consumption within unit time for all projects as the optimization objective. In order to ensure the optimal individual will not be destroyed by operations such as crossover or variation and still maintain convergence of differential evolution algorithm, we try to introduce the elitist reservation to the differential evolution algorithm. Case analysis showed that the improved differential evolution algorithm can solve the model of RLPMP and then improve the balance of multi-project resources effectively.
Spell Checker for Non Word Error Detection: Survey

Spell checker is a software tool which is used to detect the spelling errors in a text document. A spell checker can also provide suggestions to correct the misspellings. The error can be either non word error or real word error. Detecting real word error is really difficult task and requires advanced statistical and Natural Language Processing (NLP) techniques. Currently we have many methods for detecting non word errors in a text document. This paper mainly deals with the non word error detection methods for various languages.
Strand-based musculotendon simulation of the hand

This dissertation develops a framework for modelling biomechanical systems, with special focus on the muscles, tendons, and bones of the human hand. Two complementary approaches for understanding the functions of the hand are developed: the strand simulator for computer modelling, and an imaging apparatus for acquiring a rich data set from cadaver hands. Previous biomechanical simulation approaches, based on either lines-of-force or solid mechanics models, are not well-suited for the hand, where multiple contact constraints make it difficult to route muscles and tendons effectively. In linesof-force models, wrapping surfaces are used to approximate the curved paths of tendons and muscles near joints. These surfaces affect only the kinematics, and not the dynamics, of musculotendons. In solid mechanics models, the 3D deformation of muscles can be fully accounted for, but these models are difficult to create and expensive to simulate; moreover, the fibre-like properties of muscles are not directly represented and must be added on as auxiliary functions. Neither of these approaches properly handles both the dynamics of the musculotendons and the complex routing constraints. We present a new, strand-based approach, capable of handling the coupled dynamics of muscles, tendons, and bones through various
Signed Network Node Relevance Measurements

In this paper, we perform the initial and comprehensive study on the problem of measuring node relevance on signed social networks. We design numerous relevance measurements for signed social networks from both local and global perspectives and investigate the connection between signed relevance measurements, balance theory and signed network properties. Experimental results are conducted to study the eects of signed relevance measurements with four real-world datasets on signed network analysis tasks. ACM Reference format: Tyler Derr, Chenxing Wang, Suhang Wang, and Jiliang Tang. 2016. Signed Network Node Relevance Measurements. In Proceedings of ACM Conference, Washington, DC, USA, July 2017 (Conference’17), 10 pages. DOI: 10.1145/nnnnnnn.nnnnnnn
Digital phase-locked loop constructed by AND-filter

A type of digital phase-locked loop (DPLL) with an AND-filter instead of a random walk filter (RWF) is proposed in order to increase phase acquisition speed. This loop is compared with conventional loops. It is found that the phase acquisition speed of this proposed loop is better than that of either of the conventional loops with the same noise suppression effect. Performance is verified by computer simulation. <<ETX>>
A Conceptual Model for Investigating Online Group Buying in Virtual Communities

In virtual communities, people can pool together to buy a product at a lower price, which is called online group buying (OGB). We argue that besides product-related features, the initiators’ social capital is a key factor in one successful OGB event. Based on Social Capital Theory, we present a conceptual model for investigating the relationship between initiators’ social capital and the success of OGB event. Our study offers implications on: 1) how can the virtual community managers attract and sustain more members by facilitating successful OGB events; 2) what may become the future of online group buying mechanism, which is a booming phenomenon in electronic commerce.
Efficacy of Computer Animated Aids in Statistics for Graduate Students of SLP

Historically, many graduate students experience difficulty grasping basic concepts of statistical methods. Nevertheless, in their professional career they are often required to understand research papers that extensively use statistics. Pretests of a sample of students confirmed significant confusion over basic concepts such as the p-value, Type-I and II errors, statistical power, and so forth. Therefore, we decided to develop a set of computer animated modules that directly demonstrate various statistical concepts. Following the computer animated demonstrations, we administered a posttest. According to preliminary findings on the posttest, the approach appears to be effective.
NEW SOFTWARE TO HELP EFL STUDENTS SELF-CORRECT THEIR WRITING

Jim Lawley, Universidad Nacional de Ensenanza a Distancia This paper describes the development of web-based software at a university in Spain to help students of EFL self-correct their free-form writing. The software makes use of an eighty-million-word corpus of English known to be correct as a normative corpus for error correction purposes. It was discovered that bigrams (two-word combinations of words) present in a student’s writing but which are not found, or which are suspiciously rare, in the normative corpus are likely to contain errors. The program highlights such bigrams in compositions, and guidance is provided to help students decide if they have indeed made a mistake, and if so, how to correct it. A cohort of students who volunteered to trial the software for a month reported positively on their experience; it had helped them find mistakes in their own and their peers’ writing and had greatly accelerated the selfcorrection process.
Interactive Spaces: Model for Motion-based Music Applications

With the extensive utilization of touch screens, smartphones and various reactive surfaces, reality- based and intuitive interaction styles have now become customary. The employment of larger interactive areas, like floors or peripersonal three-dimensional spaces, further increase the reality- based interaction affordances, allowing full-body involvement and the development of a co- located, shared user experience. Embodied and spatial cognition play a fundamental role for the interaction in this kind of spaces, where users act in the reality with no device in the hands and obtain an audio and graphical output depending on their movements. Starting from the early experiments of Myron Krueger in 1971, responsive floors have been developed through various technologies including sensorized tiles and computer vision systems, to be employed in learn- ing environments, entertainment, games and rehabilitation. Responsive floors allow the spatial representation of concepts and for this reason are suitable for immediate communication and engagement. As many musical features have meaningful spatial representations, they can easily be reproduced in the physical space through a conceptual blending approach and be made available to a great number of users. This is the key idea for the design of the original music applications presented in this thesis. The applications, devoted to music learning, production and active listening, introduce a novel creative approach to music, which can be further assumed as a general paradigm for the design of motion-based learning environments. Application assessment with upper elementary and high school students has proved that users engagement and bodily inter- action have a high learning power, which can be a valid resource for deeper music knowledge and more creative learning processes. Although further interface tests showed that touch screen interaction performs better than full-body interaction, some important guidelines for the design of reactive floors applications have been obtained on the basis of these test results. Moreover, the conceptual framework developed for the design of music applications can represent a valid paradigm also in the general field of human-computer interaction.
Leveled Homomorphic Encryption in Certificateless Cryptosystem

To lower communication complexity, a Certificateless homomorphic encryption (CLHE) scheme based on the Learning with errors (LWE) problem is constructed by introducing a new technique called probabilistic encoding with weakly homomorphic property. This technique can conveniently convert an intended message into two elements in a ring, which will be respectively encrypted under both public keys of a user in certificateless cryptosystem. Upon knowing both elements simultaneously, the original message can be easily recovered. It is hidden perfectly by the probabilistic property of encoding. This CLHE removes evaluation keys by using the approximate eigenvector method given by Gentry et al., which makes it into a pure CLHE. It is proven to be semantic secure in the Random oracle model (ROM). The results indicate it is able to homomorphically evaluate any functions in a class functions with given multiplicative depth L.
Open Data as Open Educational Resources: Towards Transversal Skills and Global Citizenship

Open Data is the name given to datasets which have been generated by international organisations, governments, NGOs and academic researchers, and made freely available online and openly-licensed. These datasets can be used by educators as Open Educational Resources (OER) to support different teaching and learning activities, allowing students to gain experience working with the same raw data researchers and policy-makers generate and use. In this way, educators can facilitate students to understand how information is generated, processed, analysed and interpreted. This paper offers an initial exploration of ways in which the use of Open Data can be key in the development of transversal skills (including digital and data literacies, alongside skills for critical thinking, research, teamwork, and global citizenship), enhancing students’ abilities to understand and select information sources, to work with, curate, analyse and interpret data, and to conduct and evaluate research. This paper also presents results of an exploratory survey that can guide further research into Open Data-led learning activities. Our goal is to support educators in empowering students to engage, critically and collaboratively, as 21st century global citizens.
Engaging Intuitive Visual Thinking in Urban Design Modelling: A Real-Time Hypothesis

This paper will present prototypical software being used in the teaching of urban design to students and for use by professionals in the early stages of a project. The system is intended to support a heuristic approach to design. That is, it supports a process of refining ideas and understandings through a process of trial and error. The support or aid to design comes in the form of a didactic real-time programme. Its power lies in its ability to provide instantaneous response to operations on the data that can allow one to develop threedimensional spatial ideas in an intuitively driven manner. This condition appears to occur for both novice and expert computer operators. The presentation will present our experience to-date in using conventional computer graphic tools to represent design ideas and contrast it with a video demonstration of our prototypical dynamic urban design modelling software for the Silicon Graphics IRIS computers.
Illumination invariant face recognition based on active near-infrared differential imaging

Changes in the illumination condition cause dramatic variation in face appearance and seriously affect the performance of face recognition systems. This problem is addressed in the thesis by introducing an approach based on active Near-Infrared differential imaging. Assuming a static scene, a linear response of the sensor to the scene radiation and no saturation, it is shown theoretically and empirically in this thesis that the active differential imaging technique yields a face image independent of the change in ambient illumination. By taking the difference of two face images, one captured with the active illumination on and one with it off, the resulting image contains the face illuminated only by the active illumination source. This technique is compared with several representative illumination invariant face recognition techniques on a database containing faces captured under different illuminations and at different time. The results in face identification and verification experiments demonstrate the significant advantage of this Near-Infrared differential imaging technique over the other techniques. This thesis also presents a multistage approach to automatic face localisation for the Near-Infrared face images. This multistage approach is a combination of a novel pupil detection approach based on edge following and chaincode representation, and an approach based on FloatBoost learning. Accurate face localisation results are achieved by the proposed multistage approach, and this leads to the excellent face recognition performance in fully automatic scenario. A subject appears at two different locations before and after the active illumination is turned on if he/she is moving. This causes motion artifact in the difference image from the active differential imaging system and degrades the performance of the face recognition system. The thesis presents an approach based on motion compensation to deal with this problem. It is shown from the experimental results that the proposed approach successfully removes the motion artifacts and improves the face recognition performance significantly.
An Efficient Image Segmentation Method Based on Linear Discriminant Analysis and K-means Algorithm with Automatically Splitting and Merging Clusters

Image segmentation plays a significant role in image processing, pattern recognition and as well as in computer vision. It aims to classify the meaningful objects residing in the image. This paper presents an efficient image segmentation method in which the linear discriminant analysis (LDA) is used for initial segmentation of the image through unsupervised manner. After the initial segmentation, the segmented image is used by the K-means algorithm for further segmentation. Finally, the procedures of automatically splitting and merging of clusters are applied to obtain the better segmented image. For analyzing the performance, we calculate the Davies-Bouldin index (DB-index) measure. The observation shows that, this method gives the better results compared with K-means algorithm, self organizing feature map (SOFM) and LDA based image segmentation method and also LDA and K-means algorithm based image segmentation method for a set of natural images.
Modeling open channel flow resistance with dune bedform via heuristic and nonlinear approaches

Flow resistance in open channels with dune bedform is a substantial issue due to the influence of dunes on the hydraulic roughness, which can affect the performance of hydraulic constructions. There are a number of nonlinear approaches that have been developed to predict the roughness coefficient in alluvial channels, such as developed equations based on the mean velocity or shear stresses. However, due to the multitude of factors influencing roughness, establishing an accurate determination of the roughness coefficient is difficult. This study applies Gene expression programing (GEP) and nonlinear approaches to predict the Manning9s coefficient in dune bedform channels. Four different experimental data series were used for modeling. In order to develop the models, three scenarios with different input combinations were considered: scenario 1 considers only flow characteristics, scenario 2 considers flow and bedform characteristics, and scenario 3 considers flow and sediment characteristics. The results proved that GEP is capable of predicting the Manning9s coefficient. It was found that for estimation of the roughness coefficient in dune bedform channels, scenario 3 performed more successfully than others. Sensitivity analysis showed that the Reynolds number plays a key role in the modeling process. Comparisons between GEP models and existing equations indicated that GEP models yield better results.
Optimization of Handover in Mobile System by Using Dynamic Guard Channel Method

Handover process is a very essential process in the Global System for Mobile Communication system (GSM). Its study is one of the major key performance indicators in every GSM network, and its linked to the quality of service of an each service provider strives to attain. The failure of the handover process is regarded as the drop of quality of service which in turn dissatisfies the customers. This study, contributes more on improving call drop rate in general, reduce handover failure rate and thus save on upgrade costs, this will be beneficial to GSM service providers to easily optimize their network faults relating to the resource management. In this paper, dynamic guard channel algorithm is presented that was developed using JAVA Software. This algorithm prioritizes the handover calls over the new originated calls. All handover calls are ongoing calls and if they are dropped it causes frustrations. Matlab was used to compare simulated results to the other schemes by use of graphs and charts. From this paper we were able to establish and come up with a definitive solution to the handover crisis befalling telecommunication companies.
Comparison of Resampling Methods for Bias-Reduced Estimation of Prediction Error: A Simulation Study Based on Real Datasets from Biomarker Discovery Studies

Stepwise logistic regression is the traditional and most commonly used method for identifying biomarkers and evaluating the magnitude of their eﬀects based on clinical data. Here, we evaluated the performance of the resampling methods leave-one-out cross-validation, 10-fold cross-validation, bootstrap, and . 632+ bootstrap in terms of internal validation of prediction analysis using stepwise logistic regression. We conducted simulation studies to compare the ability of these methods to estimate prediction accuracy based on simulation settings (including statistical models) derived from two real biomarker discovery studies (Ogata et al., Leukemia Research 2012; 36: 1229–1236; Yoshimi et al., Molecular Psychiatry 2016; 21: 1504–1510). The simulation results revealed that leave-one-out cross-validation, 10-fold cross-validation, and . 632+ bootstrap were comparable in terms of the root mean square error. We therefore recommend the application of these methods to similar biomarker discovery studies that involve approximately ten biomarkers with or without binary biomarkers (such as sex) and various degrees of correlation between the biomarkers. samples were deﬁned to evaluate the methods accurately, and the cut oﬀ values were set at three values for application of ROC. Our results indicate that the performances of leave-one-out cross-validation, 10-fold cross-validation, and . 632+ bootstrap are comparable under previously encountered conditions.
Cognitive radio communication device for performing spectrum sensing and data communication

The radio communication apparatus is provided that the at least includes two RF chains. Cognitive radio communication apparatus is at least two RF chains can reduce data communication is silent or have a time (quiet time) is interrupted utilized to carry out the detection characteristics. And one of the RF chain during a single RF chain to perform the feature detection is so capable of performing data communication, that the wireless communications apparatus to meet the QoS (Quality of Service) required by the user. Cognitive radio, sensing, spectrum, frequency, in-band, out-of-band, energy detection, feature detection
A Novel RSS-Ratio Position Estimation Scheme for Wi-Fi Networks

the importance of location based service has been addressed frequently in various fields and the interest about core technique of various positioning scheme for indoor has been increased. The positioning scheme based on Wi-Fi is widely used because the infrastructure is already set up in many indoor spaces. The fingerprinting and the lateration schemes are typical techniques for Wi-Fi based positioning. However, these schemes have some problems for actual execution, such as hard-works for building data base and the time-varying characteristics of wireless signal. In this paper, a novel received signal strength (RSS)-ratio based positioning is proposed to mitigate the problems of conventional schemes. The performance of proposed scheme is evaluated in normal office environment according to various number of selection APs. According to the experiment results, the positioning error of proposed scheme is reduced about 82% than that of conventional RSS lateration scheme. Keywords-positioning; Wi-Fi positioning; received signal strength (RSS); RSS ratio