Miracle-dz/UniFAR-FTUs huggingface dataset:
An Improved Median Filtering Image De-noising Algorithm

Noise will occur in the image acquisition. These noises deteriorate the image quality, blur the image and even submerge and change the features, which will bring difficulties to image analysis and recognition. Therefore, filtering methods are usually used to eliminate these noises. Median filtering is quite effective in image de-noising. This paper proposes an improved median filtering algorithm. This algorithm uses the characteristic of the motion of the filtering window and the data relevance, which will reduce the time of image de-noising. Based on the median filtering algorithm, it improves the method to seek the median value, gives the optimal weight coefficient to the pixel point according to the relevance between the signal pixel and the central pixel in the filtering window, and improves the de-noising effect accuracy. This improved median filtering algorithm can preserve the image details and achieve better de-noising effect. The simulation experiment proves that the algorithm of this paper can reduce the time the median filtering requires and enhances the signal to noise ratio of the image so that it can improve the efficiency while guarantee the de-noising effect, which is of great practical significance to eliminate noises.
Robust Video Stabilization and Quality Evaluation for Amateur Videos

Robust Video Stabilization and Quality Evaluation for Amateur Videos by Usha Kalyani Alluri Amateur videos captured by consumer-level devices (e.g., mobile phones, tablets, camcorders etc.) are often shaky, undirected and difficult to watch. Video stabilization techniques attempt to improve the video quality by filtering out unwanted jittering camera motions. Currently there are two key challenges in the field of video stabilization: robustness (e.g., in the presence of sophisticated camera motion including panning and rotation) and quality evaluation. Therefore the main contributions of this thesis are two-fold. First, we present a robust video stabilization algorithm, which post-processes shaky video data and addresses the challenges of rapid camera panning and motion blur. Our algorithm is based on a robust 2-D motion estimation method using Random Sample Consensus (RANSAC) and Mestimator Sample Consensus (MSAC). Additionally, K-Nearest Neighbor based feature replacement was developed to further improve the robustness of feature tracking. It is experimentally demonstrated that the proposed video stabilization algorithm can handle video with low feature count and motion blur. Second, we present a Total–Variation (TV) based quality evaluation metric, which objectively quantifies the shakiness in amateur video. The proposed stabilization technique is compared against existing online video stabilization software (e.g., Deshaker and YouTube) using the newly-developed quality metric. Experimental results demonstrate that the developed algorithm is performing both subjectively and objectively at least as well as benchmark methods.
Digital kaleidoscope, artistic rendering with fractal image encoding

The technology of Fractal Image Compression (FIC) has been applied almost for the image compression, but the important benefit of FIC is the ability of the geometrical analysis of the image. This point can be worthy of the area for the artistic image effects. Color-Stealing algorithm is highly compatible with FIC in the point of using IFS, then the combination of them work as the new artistic image filter. In this method, the user simply prepare two images to have the artistic effect.
Implementation of Optimal Monetary Policy in a New Keynesian Model under Heterogeneous Expectations

This thesis derives an optimal interest rate reaction function from a New Keynesian model with heterogeneous expectations and a fully model-consistent welfare criterion under discretion. The reaction function incorporates the heterogeneity in expectations and a consumption inequality dimension implied by the model-consistent welfare criterion. However, a monetary policy derived from a microfounded objective that only recognizes variations in inflation and the output gap might yield slightly lower welfare losses. Nevertheless, consumption inequality is lower across all considered parameter values in case of the model-consistent objective.
Non-parametric mixture model with TV spatial regularisation and its dual expectation maximisation algorithm

An image segmentation method based on a non-parametric mixture model together with total variation (TV) regularisation is proposed. The authors use a kernel density estimator as a basic mixture model, which can better separate the non-central distributed data. To enforce its robustness, they integrate the well-known TV regularisation into the statistical method. They use the dual method to efficiently solve the TV-related energy and get a new dual expectation maximisation algorithm. Experiments on both synthetic images and real images show that the proposed algorithm can achieve good segmentation results. Compared with the parametric models and hidden Markov random field-based method, the proposed method can produce better result in some cases.
Challenges to diabetes self-mangement in developing countries

In developing countries, financial and human resources are limited despite serious needs and multiple health challenges. More than three-quarters of the people with diabetes worldwide live in developing countries. Between 2000 and 2025, the rise in the number of people with the condition in these countries will be around 170%. In the developing world, diabetes, like other chronic diseases, is often ignored in terms of healthcare priorities; the focus remains largely on immediate and acute care rather than on prevention. The challenges involved in providing education to enable people to self-manage their chronic condition exist at three levels: patients, healthcare providers, healthcare systems.
Genetics characterization of fresh water clam Spathopsis rubens using ISSR-PCR markers

Spathopsis rubens is a fresh water bivalves distributed in Nile River and its main canals all over Egypt. Four populations of S. rubens on Al- Mahmoudia irrigation canal at Damnhour, Egypt were collected and investigated for morphometric characters and genetic diversity by using inter simple sequence repeats (ISSR). The results declared that both of the length and height measurements of the collected samples from the different locations showed slight significant differences, however, no significant differences between the total weight and the width of the samples has found. High degree of correlation between temperature and total weight, height and length were reported in samples collected from the 3rd location. Genomic DNA from the selected samples of each population was extracted and amplified using ten ISSR primers. The primers (M2, M3, M8, M12, M17, F2, F4, and F9) showed 100% polymorphism. Unweighted pair group method with arithmetic mean (UPGMA) dendrogram characterized the samples of S. rubens into two main definite clusters. The cluster of genotypes 2 and 3 recorded the highest similarity and distance indices at distance of 0.60859, while genotypes 1 and 3 recorded the lowest similarity and distance indices at distance of 0.1716.
GANGLIONEUROMA OF RETROPERITOEAN: A CASE REPORT

Ganglioneuromas presented as a retroperitoneal tumor around the vital organs is a rare entity. A case with unusual presentation is reported. Young woman of 44 years old presented without any complaint ,that known during incidental abdominopelvic ultrasonography. It was treated with partial resection for debulking surgery. Debulking surgery with preservation of organ functions is feasible in these slow growing tumors for better quality of life.
Pixel-wise Semantic Segmentation Algorithm Based on Deconvolution Network

The performance of semantic segmentation will directly affect the precision of the following image analysis, recognition and etc. To deal with the issued existed in semantic segmentation, such as the edge discontinuities, inaccurate region segmentation, this paper proposed a pixel-wise semantic segmentation algorithm based on deconvolution network. The proposed approach detects the edge with a structured method and generates a pixelwise probability map with the spatial information, which indicates the probability of each pixel that belongs to one of the predefined classes. Based on this probability map, edge search and pixel-wise region partition is applied to get a fine segmentation. Experiments showed that the proposed method outperforms the semantic segmentation approach based on the existing deconvolution network with higher accuracy and more edge details. And meantime the algorithm has good robustness and real-time performance.
Efficient Processing of Aggregates in Probabilistic Databases

Computing expectations of aggregates over probabilistic databases is believed to be a hard problem. Moreover, since providing confidence intervals for aggregation is strictly necessary, the problem is even harder. At least the expectation and variance need to be evaluated to provide usable confidence intervals. In this paper, we present efficient algorithms for computing moments of SUM-like aggregates over non-correlated multi-relation queries on databases with tuple-uncertainty. The core idea in our work is to statistically analyze moments of the aggregates by making extensive use of linearity of expectation. The theoretical formulas can be expressed in SQL and evaluated using a traditional DBMS. Our experiments indicate that only a small overhead – usually below 10% – is needed to evaluate probabilistic aggregations using a traditional DBMS. Furthermore, the distribution of probabilistic aggregates tends to be normal and well approximated by the normal distribution with the mean and variance computed using our method. This means good quality confidence bounds based on normality can be readily computed. When the normal approximation is not appropriate, conservative Chebychev bounds can be used instead, bounds that are based on mean and variance as well.
Implementing Pedagogy Technology Integration In Teacher Education

Paradigm shifts in education in recent years envisions a new type of learning culture that demands ICT integration with pedagogy in Teacher Education Programme. Implementing the pedagogy-technology integration in teacher education and managing the changes are highly complex and possibly one of the most challenging tasks for any teacher education institution. ICT has to be infused into pedagogy in such a way that its uses can improve learning. The proposed model is derived from international and national studies on ICT development that has identified a series of broad stages that educational system and institutions typically proceed through in the adoption and the use of ICT. These broad stages have been termed as Emerging, Applying, Infusing and Transforming stages of ICT development (UNESCO, 2005). The model is then mapped on the basis of: (a) stages of ICT usage and (b) pedagogical usages of ICT. At the heart of good teaching with technology there are three core components: content, pedagogy, and technology, along with the relationships among and between them. The interactions among the three components, account for the wide variations seen in the extent and quality of pedagogy technology integration. These three knowledge bases (content, pedagogy, and technology) form the core of the technology, pedagogy, and content knowledge (TPACK) framework (Koehler & Mishra, 2008; Mishra & Koehler, 2006). The framework describes how teachers’ understandings of technology, pedagogy, and content can interact with one another to produce effective discipline-based teaching with educational technologies. In this framework, there are three interdependent components of teachers’ knowledge: Content Knowledge (CK), Pedagogical Knowledge (PK), and Technological Knowledge (TK). In view of this, here an attempt has been made to discuss various issues and strategies for implementation of pedagogytechnology integration in teacher education for teacher development. Information and communication technologies have revolutionized our society. In last two decades, technology has dramatically penetrated into every area of society and, every aspect of social and cultural lives. Television was the initiator. Television rediscovered and recast the world as a direct experience. Computers made it possible for vast amount of information to be made instantly available and modified with a keystroke. The very nature of work has changed, with an increasing demand for workers who could master the new technologies and use them to
Genetic Evidence of Dispersal Limitation and Local Adaptation in Samoan Reef Corals: Report on Ongoing Research: March, 2006

In August of 2004 we collected samples of two species of staghorn corals, Acropora hyacinthus and Acropora cytherea, at three sites in American Samoa: Vatia Bay (43 samples), Fagamalo Bay (18 samples) and Ofu Island (37 samples). In two of these sites, Vatia and Ofu, samples were taken in two distinct habitats: the warmer, less exposed back reef, represented in Ofu by intertidal pools, and the cooler, more exposed fore reef. Samples were PCR amplified and direct sequenced at a mitochondrial locus for the coral and a mitochondrial and nuclear locus for its Symbiodinium partner.
Optimal Control of Quadrotor Unmanned Aerial Vehicles on Time Scales

In this paper, an optimal controller is developed for quadrotor unmanned aerial vehicles (UAVs) on time scales. The UAVs are assumed to have desired positions and orientations and the proposed controller is used to bring the UAVs to the desired positions and orientations by minimizing a cost function on time scales. The proposed controller will be able to work for general time scales such as the discrete time intervals with time varying sampling interval and the bounded graininess. This will provide several benefits such as computational cost reduction in real time applications. The effectiveness of our optimal controller of quadrotor UAVs is demonstrated in a simulation, which validates our theoretical claims. AMS Subject Classifications: 34N05, 37N35, 37N40, 39A13, 39A60, 93B05, 93C05, 93C10, 93C15.
N ov 2 01 9 A CHEVALLEY FORMULA FOR SEMI-INFINITE FLAG MANIFOLDS AND QUANTUM K-THEORY EXTENDED

We give a combinatorial Chevalley formula for an arbitrary weight, in the torusequivariant K-theory of semi-infinite flag manifolds, which is expressed in terms of the quantum alcove model. As an application, we prove the Chevalley formula for anti-dominant fundamental weights in the (small) torus-equivariant quantum K-theory QKT (G/B) of the flag manifold G/B; this has been a longstanding conjecture about the multiplicative structure of QKT (G/B). Moreover, in type Ar, we prove that the so-called quantum Grothendieck polynomials indeed represent Schubert classes in the (non-equivariant) quantum K-theory QK(SLr+1/B).
Discontinuous Boundary Elements for Fluid Flow Problems in Discrete Fracture Networks

1Department of Petroleum Engineering, University of Louisiana at Lafayette, Lafayette, Louisiana, USA 2Craft &Hawkins Department of Petroleum Engineering, Louisiana State University, Baton Rouge, LA, USA 3Dipartimento di IngegneriaMeccanica e Aerospaziale, Politecnico di Torino, Torino, Italy 4Dipartimento di ScienzeMatematiche, Politecnico di Torino, Torino, Italy 5Dipartimento di Ingegneria dell’Innovazione, Università del Salento, Lecce, Italy 6Member of INdAM-GNCS research group
An Insulating Constriction Dielectrophoresis Based Microfluidic Device for Protein Biomolecules Concentration

An insulating constriction dielectrophoresis based microfluidic device for protein biomolecules concentration Peng Zhang Sample enrichment or molecules concentration has been considered as an essential step for sample processing and biomarker detection recently in many applications involving miniaturized devices aiming at biosensing and bioanalysis, including the development of specialized tests for the detection of specific proteins and antibodies in human blood with the help of microfluidic and lab-on-a-chip devices. Among all the means involved to achieve this aim, dielectrophoresis (DEP) is increasingly employed in molecule manipulation and concentration because it is nondestructive and ensures high efficiency. However, there are still constraints on implementing the required functions using the dielectrophoresis technique in the devised micro-scale structures with high throughput, as well as the technical challenge in integration of sensors and concentration units for low-abundance molecular detection. In the present work, we demonstrated a methodology to achieve protein concentration utilizing the combination effects of electrokinetics and low frequency insulator-based dielectrophoresis (iDEP) generated within a microfluidic device, in which a submicron constricted channel was fabricated using DNA molecular combing and replica molding. This fabrication technique, avoids using e-beam lithography or other complicated nanochannel fabrication methods, provides an easy and low cost approach with the flexibility in controlling channel dimensions to create highly constricted channels embedded in a microfluidic device. With theoretical analysis and experiments, we demonstrated that albumin–fluorescein isothiocyanate conjugate (FITC-BSA) protein molecules can be significantly concentrated to form an arc-shaped band near the constricted channel under the effects of negative dielectrophoretic force and DC electrokinetic forces within 2-3 minutes. It was also observed that the amplitudes of the applied DC and AC electric fields, AC frequencies, as well as suspending medium conductivities had strong effects on the concentration responses of the FITC-BSA molecules, including the concentrated area and position, intensities of the focused molecules, and concentration speed. Our method demonstrated in the thesis provides a simple and flexible approach for quickly concentrating protein molecules by controlling the applied electric field parameters. The iDEP device reported in this thesis can be used as a stand-alone sensor or worked as a preconcentration module integrated with biosensors for protein biomarker detections. Furthermore, low frequency dielectrophoresis provides practical uses for integrating the concentration module with a portable biosensing system.
Vocational and technical education in Nigeria

——. 2001. Science education for all Nigerians in the twentyfirst century: implications for Universal Basic Education (UBE) Scheme. (Paper presented at the Lagos State STAN annual conference.) Otuka, J.O. E. , et al. 1993. Teachers’ views on effective primary science in Nigeria schools. Science education (London), vol. 4, p. 23–25. ——. 2000. Think & Do activity-based science for Nigerian primary schools. Kaduna, Nigeria, Osibina Nigeria Enterprises. Putsoa, B. 1999. Bridging school science and technology with that of the community and workplace. In: Naidoo, P.; Savage, M. , eds. Using the local resource base to teach science and technology. Westville, South Africa, University of Durban. (AFCLIST Publication.) Shymansky, J.A. ; Kyle, W.K. , Jr. 1992. Overview: science curriculum reform. Journal of research in science teaching (New York, NY), vol. 29, p. 743–44.
EagleView: Design of People and Devices Visualizations for Analysing Interactions in Tracked Space

Data related to physical space such as location of people, devices, and objects can be used to implement novel interactions in ubiquitous computing. It is common that the studies of these interactions involve a group of people doing different activities at the same time, requiring a video to be recorded for later analysis. However, video analysis process is time-consuming due to the need for repeated video playback to search for interesting activities. To aid researchers to quicken analysis of videos, we developed two types of web-based visualization tools. In particular, the real-time visualization showed information about people’s movement and actions based on five proxemic dimensions (distance, orientation, movement, identity, location) and another indicator for people’s attention. Overview visualization described activities over a time period in a single image. The visualizations were implemented using user-centred design method. An evaluation with seven expert users revealed that most visualization components were easy to understand and beneficial for video analysis. Real-time visualization provided a clean and objective representation of data, while overview visualization added a time dimension which transformed the data to reveal new meaningful information, for instance; a position heat map used a collection of people’s movement data to show the location where people stayed for the longest period; a movement trajectory created a continuous line which showed the patterns of how people navigated around the space. Through our study, we proposed an overview visualization on the timeline which would allow users to quickly search for interesting events without the need for video playback.
Headspace Oxygen Concentration Measurement for Pharmaceutical Glass Bottles in Open-Path Optical Environment Using TDLAS/WMS

Accurate measurement of oxygen concentration for pharmaceutical glass bottles is of great significance to ensure the asepsis of medicine and stability of ingredients. With merits of high sensitivity, low cost, noncontact, and real-time response, the wavelength-modulation-based tunable diode laser absorption spectroscopy (TDLAS/WMS) technology shows great potential to achieve in-site oxygen concentration detection by the single-line spectrum measurement. This article focuses on headspace oxygen concentration measurement in the open-path optical environment, which is extremely challenging due to the short light path length and random ambient noises. First, a signal reconstruction method is established based on the discrete wavelet packet transform (DWPT), where random noise suppression is implicitly achieved. Then, oxygen concentration is inversed among the data between two adjacent valley values of the demodulated second-harmonic signal by multiple linear regression (MLR), and the linear discriminant analysis (LDA) is imported to enhance the information sparsity of second-harmonic signal matrix and to address the multicollinearity problem. Simulation results prove that our proposed method achieved considerable detection accuracy with the average absolute error of 0.05%. This article also designed a TDLAS/WMS prototype, and the experimental results aiming at glass bottles with different oxygen concentration of 0%, 5%, 10%, and 21% in open-path optical environment indicate our method has achieved an encouraging average absolute error of 0.54% and can survive well when the normalized signal-to-noise ratio (SNR) is within 0.85–1. These results promise that the proposed methodology can be widely applied in in-site automatic optic inspection (AOI) instrumentation of headspace oxygen concentration measurement for glass vials.