Miracle-dz/UniFAR-FTUs huggingface dataset:
Image retrieval based on convolutional neural network and kernel-based supervised hashing

With the increasing amount of image data, the present image retrieval methods have several problems, such as the steps of the visual features coding are fixed, lack of learning ability, low expression ability of the features, high dimension of the features, which restrict the retrieval performance severely. Aiming at these problems, an image retrieval method based on convolutional neural network and kernel-based supervised hashing is proposed. Firstly, we use the learning ability of convolutional neural network to mine the internal implication relation of the images and extract the deep features. Then, introduce the kernel-based supervised hashing and train the high-dimension deep features with the supervised information, map the high-dimensional features to the low-dimensional compact binary codes. Finally, image retrieval on the mass image datasets is accomplished effectively in low-dimensional hamming space. The experimental results on ImageNet-1000 and Caltech-256 demonstrate that our method can enhance the expression ability of the image features effectively, and reduce the dimensionality of the high-dimension image features, the image retrieval performance is superior to the state-of-the-art methods.
An Adaptive Huffman Decoding Algorithm for MP3 Decoder

This paper proposes a novel array data structure to represent Huffman code table and an adaptive algorithm for Huffman decoding based on Single-side Growing Huffman Coding approach which provides a memory efficient and high-speed decoding algorithm. The search time of the proposed algorithm for finding a symbol is the ceiling of (CL/4) where CL is the code length of the corresponding symbol. The implementation of the proposed algorithm is applied for MP3 decoding and the experimental result shows that our algorithm is applicable to all Huffman decoding applications.
An Unsupervised Method of Exploring Ontologies from Folksonomies

Ontology is the basis component of the Semantic Web. Since constructing ontologies is a time consuming job for domain experts, many researches are conducted on automatic extraction of ontologies from texts. As the development of folksonomy, more and more researchers have realized that folksonomy is a better knowledge source for constructing ontologies than texts. Although some works have already been proposed to extract ontologies from folksonomies, these works have little consideration on what a more acceptable and applicable ontology for users should be, and lack an principle to supervise the ontology extraction from a human’s perspective. According to the study in cognitive psychology, there is a family of concepts named basic level concepts, which are frequently used by people in daily life, and most human knowledge is expressed using basic level concepts. In this paper, inspired by studies in cognitive psychology, we try to extract ontologies with basic level concepts from folksonomies. To the best of our knowledge, it is the first work on discovering basic level concepts in folksonomies and using them to construct ontologies.
Complete and incomplete spin transitions in 1D chain iron(II) compounds

The synthesis and characterisation of two new octahedral iron(II) SCO coordination polymers [FeL1(bimm)] (1) and [FeL2(bppa)](MeOH)0.5 (2) (L1 = [3,3′]-[1,2-phenylenebis(iminomethylidyne)bis(4-phenyl-2,4-butanedionato)(2-)-N,N′,O2,O2′], L2 = [E,E]-[{diethyl 2,2′-1,2-phenylenebis(iminomethylidyne)bis(3-oxo-3-phenylpropanato)}(2-)-N,N′,O3,O3′], bimm = bis(1H-imidazol-1-yl)methane and bppa = 1,3-bis(pyridine-4-yl)propane) is presented. Results from X-ray structure analysis at different temperatures revealed in the case of 1 that the transition from a gradual to a cooperative SCO with a 5 K wide hysteresis is due to an increase of the short intermolecular contacts, which exceed a certain threshold for the cooperative effect. In the case of compound 2 an incomplete spin transition with a 4 K wide hysteresis was observed. The low temperature χMT product remains constant at a value typical for a mixed HS/LS state in stepwise spin transitions. A quantitative correlation between the cooperative effects of 12 monomer and polymer iron(II) SCO complexes and their structural properties derived from X-ray structure analysis, the so-called crystal contact index, CCI, is introduced.
Double-sided low-temperature joining technique for power cycling capability at high temperature

There is a demand for higher junction temperatures in power devices, but the existing packaging technology is limiting the power cycling capability if the junction temperature is increased. Limiting factors are solder interconnections and bond wires. With Replacing the chip-substrate soldering by low temperature joining technique, the power cycling capability of power modules can be increased widely. Replacing also the bond wires and using a double-sided low temperature joining technique, a further significant increase in the life-time of power devices is achieved
CELL SEGMENTATION USING LEVEL SET METHOD

In this thesis, the level set method and its application in cell segmentation are investigated. The main task is to segment images with clustered cells provided by FLLL-Hagenberg. Starting with the traditional level set method, the formulation of the level set function and its property are introduced in Chapter 1. The traditional method appears suitable for segmenting cells that don’t stick together. In Chapter 2, a multiphase level set method is set up to segment images with clustered cells. Combined with the iterative voting method, the multiphase level set method can separate clustered cells into individual cells and calculate the area of each cell. In Chapter 3, the Chan-Vese Model is introduced. Instead of solving n PDEs (Partial Differential Equations) as in the previous method, this model only needs two PDEs. All models introduced in the thesis are implemented and tested with real cell images. Based on these tests, we draw the conclusion: the multiphase level set method combined with iterative voting method is best suited for segmenting given images with clustered cells. The drawbacks of this method are the time complexity and the space complexity. The Chan-Vese model reduces the operation time and can deal with images that do and do not contain edges. However, it has some limitations in cell segmentation because of the sub-structures present inside cells. A preprocessing method is proposed in this work; better suited preprocessing methods are still under research.
Scalable rate control for MPEG-4 video

This paper presents a scalable rate control (SRC) scheme based on a more accurate second-order rate-distortion model. A sliding-window method for data selection is used to mitigate the impact of a scene change. The data points for updating a model are adaptively selected such that the statistical behavior is improved. For video object (VO) shape coding, we use an adaptive threshold method to remove shape-coding artifacts for MPEG-4 applications. A dynamic bit allocation among VOs is implemented according to the coding complexities for each VO. SRC achieves more accurate bit allocation with low latency and limited buffer size. In a single framework, SRC offers multiple layers of controls for objects, frames, and macroblocks (MBs). At MB level, SRC provides finer bit rate and buffer control. At multiple VO level, SRC offers superior VO presentation for multimedia applications. The proposed SRC scheme has been adopted as part of the International Standard of the emerging ISO MPEG-4 standard.
A Visual Inspection System for Rail Detection & Tracking in Real Time Railway Maintenance

Rail inspection is an essential task in railway maintenance and is periodically needed. Inspection is manually operated by trained human operator walking along the track searching for visual anomalies. This monitoring is unaccept- able for slowness and lack of objectivity. This paper deals with a patented Visual Inspection System for Railway mainte- nance, devoted to different tasks. Here, its Rail Detection & Tracking Block (RD&TB) is presented. RD&TB detects and tracks, into the acquired video sequence the rail head, by this way, notably reducing the area to be analyzed and inspected by other modules of VISyR. Thanks to its hardware implementation, RD&TB performs its task in 5.71 μs with an accuracy of 98.5%, allowing an on-the-fly analysis of a video sequence acquired up at 190 km/h. RD&TB is highly flexible and configurable, since it is based on classifiers that can be easily reconfigured in function of different type of rails.
Advantages of Advanced Active Clamping

Power semiconductor manufacturers are offering IGBT modules with ever greater power densities. The limit is represented by the maximum power loss that can be dissipated; optimisation criteria are the packaging technology as well as the conduction and switching losses of the semiconductor chips. The high current density of the modules together with high switching speeds place increased demands on the driving circuits, both in normal switching operation and under overload conditions. Advanced Active Clamping switching technology offers a solution showing how modern high-power IGBTs can be better utilised. Heinz Rüedi, Jan Thalheim and Olivier Garcia, CT-Concept Technologie AG, Switzerland
3D modeling of indoor environments by a mobile robot with a laser scanner and panoramic camera

We present a method to acquire a realistic, visually convincing 3D model of indoor office environments based on a mobile robot that is equipped with a laser range scanner and a panoramic camera. The data of the 2D laser scans are used to solve the SLAM problem and to extract walls. Textures for walls and floor are built from the images of a calibrated panoramic camera. Multiresolution blending is used to hide seams in the generated textures.
The Changing Patterns of MOOC Discourse

There is an emerging trend in higher education for the adoption of massive open online courses (MOOCs). However, despite this interest in learning at scale, there has been limited work investigating how MOOC participants have changed over time. In this study, we explore the temporal changes in MOOC learners' language and discourse characteristics. In particular, we demonstrate that there is a clear trend within a course for language in discussion forums to be of both more on-topic and reflective of deep learning in subsequent offerings of a course. We measure this in two ways, and demonstrate this trend through several repeated analyses of different courses in different domains. While not all courses show an increase beyond statistical significance, the majority do, providing evidence that MOOC learner populations are changing as the educational phenomena matures.
Saliency-based depth-of-field rendering with flash and non-flash pairs

Depth of Field is an important factor to synthesize realistic photography effects. In our paper, we discuss a new image-based approach that can synthesize DoF effects without user iterations. Our approach can produce the based saliency maps with realtime performance. In particular, there is not depth information needed to capture from cameras. The depth information is approximated by using saliency maps. In particular, we take advantages of the flash non-flash image pairs to refine the DoF synthesis quality. The focused regions can be segmented using GrabCut. The experimental results show that the our image based DoF synthesis can simulate high-quality DoF effects efficiently.
NetAffx Gene Ontology Mining Tool: a visual approach for microarray data analysis.

SUMMARY The NetAffx Gene Ontology (GO) Mining Tool is a web-based, interactive tool that permits traversal of the GO graph in the context of microarray data. It accepts a list of Affymetrix probe sets and renders a GO graph as a heat map colored according to significance measurements. The rendered graph is interactive, with nodes linked to public web sites and to lists of the relevant probe sets. The GO Mining Tool provides visualization combining biological annotation with expression data, encompassing thousands of genes in one interactive view. AVAILABILITY GO Mining Tool is freely available at http://www.affymetrix. com/analysis/query/go_analysis. affx
Distributed multi static sonar tracking in clutter

Multi static underwater surveillance must conserve energy by communicating between nodes as sparsely as possible. On the other hand, signal to clutter ratio is usually very low, resulting in large number of clutter measurements per ping. When the local target tracking is performed in each receiver node, the false measurements are largely eliminated and communications are used (almost) exclusively to report targets to the fusion center.
Interpersonal interactions within couples: Convergences and divergences between self-description and partner’s perception

Abstract Conjugality refers to the shared experience between partners characterized by an enduring bond. It is related to a high degree of intimacy, affective involvement, and different interpersonal strategies, and it is seen by partners as their most significant relationship. Such intensity makes couple interaction different from any other type of relationship. The objective of this study was to verify how interpersonal attitude of the participants toward their spouses are associated with their partners and the independent interviewer’s perception of their attitudes. The results showed that the participants had a perception of themselves that was, in general, congruent with their partners’ and the interviewer’s perception. However, the spouses agreed more about their relationship roles (dominant or submissive) and disagreed on the dedicated affection (friendly or hostile) between them. In contrast, the interviewer overestimated the subjects’ attempts to control but confirmed the presence of statements of affection. The results obtained also provided a realistic portrait of marital interactions, increasing the application spectrum of the Checklist de Relações Interpessoais (Check list of Interpersonal Transactions).
a r einforcement l earning: Great- deluge h yper- h euristic for examination t imetabling

Hyper-heuristics can be identified as methodologies that search the space generated by a finite set of low level heuristics for solving search problems. An iterative hyper-heuristic framework can be thought of as requiring a single candidate solution and multiple perturbation low level heuristics. An initially generated complete solu-tion goes through two successive processes (heuristic selection and move acceptance) until a set of termination criteria is satisfied. A motivating goal of hyper-heuristic research is to create automated techniques that are applicable to a wide range of problems with different characteristics. Some previous studies show that different combinations of heuristic selection and move acceptance as hyper-heuristic components might yield different performances. This study investigates whether learning heuristic selection can improve the performance of a great deluge based hyper-heuristic using an examination timetabling problem as a case study.
AppMark: A Picture-Based Watermark for Android Apps

Smartphones have become common tools in people's daily life. Lots of popular applications (e.g., social network applications) have immigrated from traditional computers to smartphones. With the growth of the apps, attacks on these apps are also increasing. One serious attack adds malicious payloads or advertisements to legitimate apps. These modified apps, called repackaged apps, share similar functionalities with the original apps, which makes them easily spread. To mitigate this attack, we embed watermarks into Android apps. Specially, to make the watermarks robust, we embed a new kind of watermarks called picture-based watermarks into Android apps. By making the inherent characteristics of pictures, it is resilient to obfuscation. We implemented a prototype call AppMark. We evaluated its effectiveness and performance overhead. According to the results, the picture-based watermark is both effective and efficient.
An Evolutionary Based Examination Of Sexting Behavior Among College Students

Previous research has viewed the sending and receiving of sexually natured text and picture messages as risky and dangerous behavior. It is through this lens that previous research has examined the reason individuals choose to engage in sexting, and the possible effects of the behavior. The current study is the first to examine the possible adaptive reasons that individuals may choose to engage in sexting. A total of 218 participants from Fort Hays State University completed measures of their sexting behaviors, attitudes towards sexual activity, and risk tolerance. It was hypothesized that an individual participants’ endorsement of a sex consistent mating strategy would be positively related to engagement in sexting behavior. Additionally it was thought that men with greater risk tolerance in the domain of mate attraction would engage in sexting more, and that women with greater risk tolerance in the domain of mate retention would engage in sexting more. It was also thought that participant expectancies regarding the outcome of sexting would interact with risk tolerance and mating strategy so that those with higher expectancies would sext more. Results indicate that both men and women who endorse a short term mating strategy sext more. Also, results suggested that individual risk tolerance in the domain of mate attraction were significant in the decision to engage in sexting. Additionally results showed that participants expectancies regarding the effects of sexting were significant in the decision to engage in sexting. The implications for these findings, the limitations of the current study and the need for further research in these areas are discussed.
for the Degree of Master Efficient Detection Algorithms for MMSE-SIC in MIMO Systems

In this thesis, computationally efficient detection algorithms for the minimum mean square error (MMSE) estimation with successive interference cancellation (SIC), or with generalized decision feedback equalizer (GDFE) are considered in spatial multiplexing multiple-input multipleoutput (MIMO) systems. The MMSE-SIC and the MMSE-GDFE architectures are known to achieve the ergodic capacity of MIMO fading channels. This thesis presents a new understanding of SIC and GDFE to provide further insights. This perspective shows that 1) SIC and GDFE are a special case of the two-dimensional estimation with side information (or decision feedback), and 2) SIC can be expressed in terms of the Cholesky decomposition, as GDFE is. Inspired by the latter, we propose fast algorithms based on the Cholesky decomposition for SIC and GDFE in multiple antenna systems. Although existing detection algorithms can provide an impressive reduction of computational complexity for a large M , the reduction is relatively small for a moderate M of practical interest (i.e. M ≤ 16). The Cholesky decomposition is computationally more efficient than the
Comparison of 2 D and 3 D Local Binary Pattern in Lung Cancer Diagnosis

Comparative study between 2D and 3D Local Binary Patter (LBP) methods for extraction from Computed Tomography (CT) imagery data in lung cancer diagnosis is conducted. The lung image classification is performed using probabilistic neural network (PNN) with histogram similarity as distance measure. The technique is evaluated on a set of CT lung images from Japan Society of Computer Aided Diagnosis of Medical Images. Experimental results show that 3D LBP has superior performance in accuracy compare to 2D LBP. The 2D LBP and 3D LBP achieved a classification accuracy of 43% and 78% respectively. Keywordslung cancer detection; local binary pattern; probabilistic neural network.
A Novel Vital-Sign Sensor Based on a Self-Injection-Locked Oscillator

A novel vital-sign sensor with a self-injection-locked oscillator and a frequency demodulator to reduce system complexity and improve sensitivity is proposed. The theory provides a delta-sigma model to account for the excellent signal-to-noise spectral density ratio in a parametric study of the sensitivity performance. Then, the experiments verify the sensing principle and the predicted performance. Accordingly, a prototype sensor with high sensitivity is realized for noncontact cardiopulmonary monitoring, achieving a long sensing distance without the need for a low-noise amplifier. The sensing distance can grow four times longer by doubling the operating frequency. Furthermore, the sensor using a swept frequency can eliminate the null detection points and the external radio interference. As an experimental result, the sensor, which is placed 4 m away from the subject, can reliably detect the heartbeat signal an the operating frequency of 3.6 GHz and an output power level of 0 dBm.
English-persian text retrieval using concept graph

Cross-language information retrieval (CLIR) is the retrieval process where the user presents queries in one language to retrieve documents in another language. In this field the resolution of lexical ambiguity in translating queries is a key challenge. In this paper, we propose a technique for calculating translation probabilities based on creating query terms' concept graphs for selecting the right translation sense of query terms for English-Persian text retrieval. We present an efficient statistical method for creating this graph. We test the effectiveness of the proposed disambiguation method on Hamshahri collection1 that is standardized according to CLEF standards. Evaluation using this data collection shows great effectiveness of the proposed method.
The global dispreference for posterior voiced obstruents: A quantitative assessment of word-list data

Abstract:This work explores the effect of ease of articulation on speech by examining the rates at which various consonants occur in word lists representing thousands of languages. The data reveal that obstruents produced with oral obstruction closer to the glottis are less likely to be voiced when contrasted with their counterparts produced in the anterior region of the vocal tract. While this finding is explainable via previously documented aerodynamic factors, these new data suggest that such factors may have a more powerful influence on speech than typically assumed. The pattern in question is evident even after controlling for the relatedness and areal proximity of language varieties. This study isolates and quantifies the decrease in consonant voicing associated with the reduction in size of the supralaryngeal cavity.
Teoría y metodología de investigación sobre libros de texto: análisis didáctico de las actividades, las imágenes y los recursos digitales en la enseñanza de las Ciencias Sociales

Didactic materials in any format, especially Social Sciences textbooks — Geography and History —, have been historically constituted as a central resource in the classroom for this discipline. In this study we propose its theoretical evolution as a research problem in Social Sciences (in the Spanish context) in terms of content, use and diffusion, to propose a methodology of textbooks analysis based on the study of activities and pictures linked to the cognitive complexity demanded in them. The conclusions insist on the role of textbooks as a central component of school culture in Spain and Ibero-America that requires a specific research methodology for its necessary transformation into a useful element for teaching.