Miracle-dz/UniFAR-FTUs huggingface dataset:
Stereo Camera Based Virtual Cane System with Identifiable Distance Tactile Feedback for the Blind

In this paper, we propose a new haptic-assisted virtual cane system operated by a simple finger pointing gesture. The system is developed by two stages: development of visual information delivery assistant (VIDA) with a stereo camera and adding a tactile feedback interface with dual actuators for guidance and distance feedbacks. In the first stage, user's pointing finger is automatically detected using color and disparity data from stereo images and then a 3D pointing direction of the finger is estimated with its geometric and textural features. Finally, any object within the estimated pointing trajectory in 3D space is detected and the distance is then estimated in real time. For the second stage, identifiable tactile signals are designed through a series of identification experiments, and an identifiable tactile feedback interface is developed and integrated into the VIDA system. Our approach differs in that navigation guidance is provided by a simple finger pointing gesture and tactile distance feedbacks are perfectly identifiable to the blind.
Perceptual grouping for persistent scatterers in urban high-resolution SAR images

Persistent Scatterer (PS) analysis of urban areas using high resolution SAR data is an important and by this time mature technique to estimate deformation and 3D information. Due to the high resolution a large number of PS is available per building. Beyond that the scatterers residing on one building often form patterns, which hold information about the relations between the PS. We present an approach to find horizontal rows of PS, utilizing some prior knowledge about the building under investigation. The found rows are then employed to facilitate the estimation of height information.
Turkish document semantic categorization using web-based encyclopedia article association

The rapid growth of text, video and image documents sharing on the internet, has created a new research fields to categorize these documents automatically. Especially text document categorization is the one of the hardest processing problem in any language. Also it becomes more difficult in Turkish text document categorization than the any other language since Turkish is an agglutinating language and it includes additional spelling rules. In this paper, we develop a Turkish document semantic categorization system which uses web-based encyclopedia article association to enlarge text words scopes to get better comparison performance over predefined keywords. In word comparisons, we defines some string matching algorithms which are used in literature like Naïve matching, Levenshtein distance, Smith-Waterman distance, Jaro-Winkler distance and Jaccard index. Also we compare the performance of these string matching algorithms on a dataset obtained from three important Turkish newspaper websites, Milliyet, Hurriyet and Ntvmsnbc, under five different semantic categories which includes politic, sport, economy, magazine and technology.
A Linear Programming Approach to Semidefinite Programming Problems

A semidefinite programming problem can be regarded as a convex nonsmooth optimization problem, so it can be represented as a semi-infinite linear programming problem. Thus, in principle, it can be solved using a cutting plane approach; we describe such a method. The cutting plane method uses an interior point algorithm to solve the linear programming relaxations approximately, because this resulted in the generation of better constraints than a simplex cutting plane method. Further, the bundle method of Helmberg and Rendl can be used to generate a set of linear constraints. Typically, these alone are not sufficient to give a good linear programming relaxation. Nonetheless, if they are used in conjunction with some families of problem specific constraints, tight LP relaxations can be obtained. Solving SDP via LP 2
Integration of omics data to investigate common intervals

During the last decade, we witnessed the huge impact of the comparative genomics for understanding genomes (from the genome organization to their annotation). However, those genomic approaches quickly reach their limits when one looks at investigating the functional properties of genes in the wide genome context. Such limitation may be overcome thanks to recent high-throughput experimental progresses like those obtained via metabolic and co-expression studies, that produce so-called omics data. Therefore, integrating those data and state-of-the-art computational genomic comparison is a natural evolution. This paper achieves such an integration and proposes a heuristic algorithm IISCS that incorporates omics knowledge into the IILCS heuristic, already known as accurate to compare genomes. When applied on bacteria, one emphasize large functional units composed of several operons.
Fusion of 3D Vision Techniques and RFID Technology for Object Recognition in Complex Scenes

This work presents a new method for object recognition in complex scenes combining vision-based techniques applied to the 3D data obtained using range sensors, and object identification coming from Radio Frequency tags (RFID technology). Vision based algorithms for 3D recognition have many restrictions in practical applications: uncertainty, incapability for real time tasks; but they work well for pose determination once the object is recognized. On the other hand, RFID technology allows detecting the presence of specific objects in a scene but it cannot provide their localization. In this paper, we show the powerful recognition tool obtained by fusioning both techniques. The phases of the proposed procedure are described and an in depth experimental demonstration is included. A performance analysis of the method is made by comparing the recognition algorithm with and without the RFID phase. Obtained results, concerning to success rate increasing and computational cost reduction, confirm the robustness of this fusion approach and prove its effectiveness.
The proximity ligation assay reveals that at DNA double-strand breaks WRAP53β associates with γH2AX and controls interactions between RNF8 and MDC1

We recently demonstrated that WRAP53β acts as a key regulator of ubiquitin-dependent repair of DNA double-strand breaks. Here, we applied the proximity ligation assay (PLA) to show that at such breaks WRAP53β accumulates in close proximity to γH2AX and, furthermore as demonstrated by their co-immunoprecipitation (IP) binds to γH2AX, in a manner dependent on the ATM and ATR kinases. Moreover, formation of complexes between MDC1 and both its partners RNF8 and phosphorylated ATM was visualized. The interaction of MDC1 with RNF8, but not with ATM requires WRAP53β, suggesting that WRAP53β facilitates the former interaction without altering phosphorylation of MDC1 by ATM. Furthermore, our findings highlight PLA as a more sensitive method for the analysis of recruitment of repair factors and complex formation at DNA breaks that are difficult to detect using conventional immunofluorescence.
Efficient scheduling schemes for hd-quality content distribution

Recent advances in storage and networking technology are rapidly changing users’ TV viewing patterns. PVRs enables people to watch what they want when they want independent of the broadcasting schedule by recording or timeshifting live TV programs into their local storages. Furthermore, Peer-to-Peer (P2P) networking technology provides an alternative TV content distribution channel to unidirectional broadcasting. However, due to the current limited broadband bandwidth, it is difficult to support HD-quality TV content streaming between PVRs on the Internet. In this paper, we propose a novel broadcast HD-quality streaming architecture for real-time content distribution over fast network connections. We describe two efficient scheduling schemes such as matching of a communication pair and switching/replication for system load-balancing to further utilize system resources such as networks and disks. By simulation experiments, we show the effect of our proposed schemes.
Data Series Management: The Road to Big Sequence Analytics

Massive data series collections are becoming a reality for virtually every scientific and social domain, and have to be processed and analyzed, in order to extract useful knowledge. Current data series management solutions are ad hoc, requiring huge investments in time and effort, and duplication of effort across different teams. Systems like relational databases, Column Stores, and Array Databases are not a suitable solution either, since none of these systems offers native support for data series. Our vision is to design and develop a generalpurpose Data Series Management System, able to copewith big data series, that is, very large and fast-changing collections of data series, which can be heterogeneous (i.e., originate from disparate domains and thus exhibit very different characteristics), and which can have uncertainty in their values (e.g., due to inherent errors in the measurements). Just like databases abstracted the relational data management problem and offered a black box solution that is now omnipresent, the proposed system will allow analysts that are not experts in data series management, as well as common users, to tap in the goldmine of the massive and ever-growing data series collections they (already) have
Chinese Word Ordering Errors Detection and Correction for Non-Native Chinese Language Learners

Word Ordering Errors (WOEs) are the most frequent type of grammatical errors at sentence level for non-native Chinese language learners. Learners taking Chinese as a foreign language often place character(s) in the wrong places in sentences, and that results in wrong word(s) or ungrammatical sentences. Besides, there are no clear word boundaries in Chinese sentences. That makes WOEs detection and correction more challenging. In this paper, we propose methods to detect and correct WOEs in Chinese sentences. Conditional random fields (CRFs) based WOEs detection models identify the sentence segments containing WOEs. Segment point-wise mutual information (PMI), inter-segment PMI difference, language model, tag of the previous segment, and CRF bigram template are explored. Words in the segments containing WOEs are reordered to generate candidates that may have correct word orderings. Ranking SVM based models rank the candidates and suggests the most proper corrections. Training and testing sets are selected from HSK dynamic composition corpus created by Beijing Language and Culture University. Besides the HSK WOE dataset, Google Chinese Web 5gram corpus is used to learn features for WOEs detection and correction. The best model achieves an accuracy of 0.834 for detecting WOEs in sentence segments. On the average, the correct word orderings are ranked 4.8 among 184.48 candidates.
Cross-Language Experiment

The contribution addresses the cross-language experiment. The aim was to test the possibility of the con- version French phoneme models into Czech ones. This mo- del conversion uses the Hidden Markov Models (HMM) classification procedure. The first step consists of the ite- rative mapping of French models to Czech ones. The map- ping is given by the analysis the confusion matrix. The se- cond step is the Baum-Welch re-estimation resulting in the final models for Czech language. Despite of the differences between French and Czech languages the final recognition score reaches 64% for the phoneme recognition and 74% for digit recognition. Relatively low recognition accuracy is caused by the inadequate noise model. The experiences gained with the cross-language experi- ment were utilized for the classification of simple human body movements. The solution of this problem and results are described in the second part of this contribution under the title EEG Signals Classification-Introduction to the Problem.
Enhancement and cleaning of handwritten data by using neural networks and threshold technical

This paper propos the use threshold technical and artificial neural network (ANN) for clean and enhancement scanned image for recognition task. we show noise reduction and cleaning image can used different filter that result is not gratify. Multilayer perceptron (MLP) are trained in supervised methods using a cleaning image product with threshold technical and the corresponding noise handwritten image that product from scanning with scan machine. Results showes that this method is very performance from using filter for cleaning Image. Process of cleaning image is the preprocessing for system Handwritten recognition that we do this work in this paper.
Discrete Cosine Transform Domain Parallel LMS Equalizer

The least mean square (LMS) algorithm is the most popular adaptive ltering method due to its simplicity and predictable behavior. The convergence properties of the LMS algorithm can be improved by updating the lter coe cients in the transform domain. This paper presents a new transform domain LMS equalizer, called Discrete Cosine Transform Domain Parallel LMS (DCTPLMS) equalizer, which updates the lter coe cients in the discrete cosine transform domain for the purpose of equalization of time-varying channels. Computer simulation results obtained by using a second order Markov communication channel model show that the proposed DCTPLMS equalizer provides a signi cant performance improvement relative to the conventional DCT-domain LMS as well as other time-domain based LTEs and DFEs. Key{Words: DCTPLMS equalizer, Time-varying channel, DCTLMS algorithm, LMS algorithm, Adaptive equalization.
Design and implementation of Taxi advertisement system

Nowadays advertising is widely used to promote various products. Counting-based advertising system is a promising solution for operators to enhance system resource utilization with potential profit, which is the focus of this paper. On the system, each advertisement order comprises the display length, the contract period, and the expected play count. The objective is to fulfill the expected play count within the contract period for each advertisement. However, operators face the challenge of deciding whether they should admit new orders or not without the knowledge of total amount of available time. Therefore, we propose an efficient method based on support vector machine (SVM) to predict the available time of the system in the future. In addition, a scheduling mechanism is established in consideration of fairness among advertisements. We then conduct a series of simulations by using the real data provided by Taiwan Taxi Company to evaluate the performance of our proposed advertising system. The experiment results show that our proposed scheme can highly satisfy the needs for accepted advertisements in both prediction and scheduling phases.
Leaders and followers behaving badly: A meta-analytic examination of curvilinear relationships between destructive leadership and followers’ workplace behaviors

We draw from social psychological and resource-based theories to meta-analytically examine the existence, form, and magnitude of curvilinear relationships between destructive leadership and followers’ workplace behaviors (i.e., job performance, organizational citizenship behaviors, and workplace deviance). Overall, our meta-analytic results demonstrate weak evidence of curvilinear relationships between destructive leadership and followers’ workplace behaviors. However, we did find some support for the application of social psychological theories when examining the curvilinear effects of destructive leadership on followers’ workplace behaviors at extreme levels of destructive leadership (i.e., two standard deviations below and above the mean). Our findings are important because they (1) provide support for prior research that has examined the linear effects of destructive leadership on followers’ workplace outcomes and (2) refine our knowledge of the effects of destructive leadership on followers’ workplace outcomes by demonstrating the existence, form, and magnitude of curvilinear effects at extreme levels of destructive leadership. Overall, this study’s meta-analytic regression, relative weight, and semipartial correlation results have important implications for (1) how to interpret the conclusions drawn from prior destructive leadership research, (2) how to conduct future studies that examine destructive leadership, and (3) practitioners’ attempts to deter destructive leadership and limit its harmful effects on followers.
EFFECTS OF NON-PHOTOCHEMICAL PROCESSES O N THE MERIDIONAL DISTRIBUTION AND TOTAL AMOUNT OF OZONE IN THE ATMOSPHERE

The photochemical equilibrium distribution of oAone below 41 km. is computed for the solstices and equinoxes from recent rocket obscrvatioiis of the solar ultraviolct energy received at the top of the atmosphere. In this study an attempt is made to investigate the important part played by the mean scnsonal transport processes in distributing the ozone below 41 km. in the stratosphere To make such an investigation i t is assumed that a steady state meridional distribution of ozone is produced when photochemical and transport processes arc acting together. Relevant theory and numerical procedure to compute such a steady state mcridional distribution of ozone have been developed. In order t o make a model of the transport processes that is needed for thc calciilation of the distribution of ozone, theoretical and observational information available a t prcsciit on the various transport processcs present in the stratosphere is reviewed. Further, in the calculations of ozone an attempt is made to combine the mean meridional motions and the large-scale mixing processes within the limits acceptable to the current ideas on these transport processes. The seasonal distribution of tgtal ozone thus computed from the model of the transport processes and with an assumption of steady state csnditioris shon s a satisfactory agreement \\ itti the observed seasonal and latitudinal variation of t.otal ozone. The nieaii annual total ozone variation with latitude deduced from the csmpiitcd seasonal distribution of total ozone, demonstrates the ability of the method developed here to :tccaunt for the mean ariniial total ozone variation with latitude obscrvcd in the earth’s atmosphere. The model of the transport processes devclopcd in this study to calculate the distribution of o ~ o i i e in the atmosphere emphasizes the importance of the large-scale eddy diffusion processes. The theoretical and observational findings from the spread of Wig5 (a radioactive isotope of tungsten introduced into the stratosphere by nuclcar explosions) have been very useful in making this model of the transport processes.
Learning temporal signatures for Lip Reading

This paper attempts to tackle the problem of lipreading by building visual sequence classifiers that are based on salient temporal signatures. The temporal signatures used in this paper allow us to capture spatio-temporal information that can span multiple feature dimensions with gaps in the temporal axis. Selecting suitable temporal signatures by exhaustive search is not possible given the immensely large search space. As an example, the temporal sequence used in this paper would require exhaustively evaluating 22000 temporal signatures which is simply not possible. To address this, a novel gradient-descent based method is proposed to search for a suitable candidate temporal signature. Crucially, this is achieved very efficiently with O(nD) complexity, where D is the static feature vector dimensionality and n the maximum length of the temporal signatures considered. We then integrate this temporal search method into the AdaBoost algorithm. The results are spatio-temporal strong classifiers that can be applied to multi-class recognition in the lipreading domain. We provide experimental results evaluating the performance of our method against existing work in both subject dependent and subject independent cases demonstrating state of the art performance. Importantly, this was also achieved with a small set of temporal signatures.
Survey of odd and even length filters in tree-structured filter banks for subband image compression

The performance of subband image coders depends on proper choice of filter banks. Although odd length filters in the filter banks produce waveform type artifacts, this can be alleviated by enforcing a smooth interpolation property to the synthesis lowpass filter. Evaluation of even, odd, and combinations of even and odd length filters in tree-structured filter banks, where the filter coefficients are obtained by optimizing for coding gain at each stage, is done for image coding purposes. Favorable results are obtained when a combination of odd and even length filters are used.
Standardized Mutual Information for Clustering Comparisons: One Step Further in Adjustment for Chance

Mutual information is a very popular measure for comparing clusterings. Previous work has shown that it is beneficial to make an adjustment for chance to this measure, by subtracting an expected value and normalizing via an upper bound. This yields the constant baseline property that enhances intuitiveness. In this paper, we argue that a further type of statistical adjustment for the mutual information is also beneficial - an adjustment to correct selection bias. This type of adjustment is useful when carrying out many clustering comparisons, to select one or more preferred clusterings. It reduces the tendency for the mutual information to choose clustering solutions i) with more clusters, or ii) induced on fewer data points, when compared to a reference one. We term our new adjusted measure the standardized mutual information. It requires computation of the variance of mutual information under a hypergeometric model of randomness, which is technically challenging. We derive an analytical formula for this variance and analyze its complexity. We then experimentally assess how our new measure can address selection bias and also increase interpretability. We recommend using the standardized mutual information when making multiple clustering comparisons in situations where the number of records is small compared to the number of clusters considered.
WORD LEVEL TIMING IN SPONTANEOUS JAPANESE SPEECH

This study provides evidence against the hypothesis that Japanese has word level mora-timing. Unlike previous studies which used careful speech, this paper evaluates timing in a corpus of spontaneous Japanese speech from 11 speakers. Correlations between word duration and number of moras in the word are shown to be much lower than in careful speech studies. Furthermore, if there were durational normalization at the level of the word, then there should be some unit across which this normalization takes place. However, we show that there is no consistency across speakers as to whether the lexical word or the prosodic word serves as such a unit. Analyses of arbitrarily truncated words further confirm that a linear accumulative model of variance can explain the data, but a model with mora compensation cannot.