Miracle-dz/UniFAR-FTUs huggingface dataset:
Sparse and low-rank models for image restoration

Image restoration aims to recover the latent high quality image from its degraded observation. As one of the most classical and fundamental topics in image processing and low-level vision, image restoration has been widely studied in the community, and a variety of approaches have been proposed, including filtering-based approaches, transformation-based approaches and variational approaches. The image sparsity priors have been used, either explicitly or implicitly, in many of these approaches, and have been playing a crucial role to improve the image restoration performance. In particular, the sparse representation based methods have achieved a great success in image restoration in the last decade. Based on the representation scheme of a signal vector, sparse representation models can be generally categorized into analysis sparse representation (ASR) models and synthesis sparse representation (SSR) models. Low-rank minimization models have also been proposed to exploit the sparsity (i.e., low-rankness) of a matrix of correlated vectors. Different models will have respectively their merits and drawbacks. The ASR based methods regularize the projection coefficients of a signal over an analysis dictionary, and they are able to supply robust priors for image large scale structures. However, the projective coding mechanism of ASR based methods restrict their capacity of benefiting from highly redundant dictionaries, limiting their flexibility in modeling image complex texture structures. The SSR based methods represent a signal as the linear combination of a few atoms in an over-complete dictionary. To model image local structures, most SSR methods partition an image into overlapped patches to process, which brings the inconsistency issue of over-lapped patches as well as the heavy computation burden. The low-rank methods regularize the number of independent subspaces of a matrix. Since directly minimizing the rank of a matrix is an NP hard problem, many recently developed low-rank methods adopt the nuclear norm (i.e., the
Foundations Of Security Analysis And Design Tutorial Lectures

Thank you for reading foundations of security analysis and design tutorial lectures. As you may know, people have search hundreds times for their favorite novels like this foundations of security analysis and design tutorial lectures, but end up in harmful downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they are facing with some harmful virus inside their computer.
A Preliminary Exergy Analysis of the EU DEMO Fusion Reactor

Received: 20 March 2019 Accepted: 6 May 2019 Purpose of the present study is the exergy analysis of EU DEMO pulsed fusion power plant considering the Primary Heat Transfer Systems, the Intermediate Heat Transfer System (IHTS) including the Energy Storage System (ESS) as a first option to ensure the continuity of electric power released to the grid. A second option here considered is a methane fired auxiliary boiler replacing the ESS. The Power Conversion System (PCS) performance is evaluated as well in the overall balance. The performance analysis is based on the exergy method to specifically assess the amount of exergy destruction determined by irreversible phenomena along the whole cyclic process. The pulse and dwell phases of the reactor operation are evaluated considering the state of the art of the ESS adopting molten salts alternate heating and storage in a hot tank followed by a cooling and recovery of molten salt in a cold tank to ensure the continuity of power release to the electrical grid. The second option of the plant configuration is evaluated on the basis of an auxiliary boiler replacing the ESS with a 10% of the power produced by the reactor during both pulse and dwell modes.
Machine Learning Based Integrated Feature Selection Approach for Improved Electricity Demand Forecasting in Decentralized Energy Systems

Improved performance electricity demand forecast can provide decentralized energy system operators, aggregators, managers, and other stakeholders with essential information for energy resource scheduling, demand response management, and energy market participation. Most previous methodologies have focused on predicting the aggregate amount of electricity demand at national or regional scale and disregarded the electricity demand for small-scale decentralized energy systems (buildings, energy communities, microgrids, local energy internets, etc.), which are emerging in the smart grid context. Furthermore, few research groups have performed attribute selection before training predictive models. This paper proposes a machine learning (ML)-based integrated feature selection approach to obtain the most relevant and nonredundant predictors for accurate short-term electricity demand forecasting in distributed energy systems. In the proposed approach, one of the ML tools– binary genetic algorithm (BGA) is applied for the feature selection process and Gaussian process regression (GPR) is used for measuring the fitness score of the features. In order to validate the effectiveness of the proposed approach, it is applied to various building energy systems located in the Otaniemi area of Espoo, Finland. The findings are compared with those achieved by other feature selection techniques. The proposed approach enhances the quality and efficiency of the predictor selection, with minimal chosen predictors to achieve improved prediction accuracy. It outperforms the other evaluated feature selection methods. Besides, a feedforward artificial neural network (FFANN) model is implemented to evaluate the forecast performance of the selected predictor subset. The model is trained using two-year hourly dataset and tested with another one-year hourly dataset. The obtained results verify that the FFANN forecast model based on the BGA-GPR FS selected training feature subset has achieved an annual MAPE of 1.96%, which is a very acceptable and promising value for electricity demand forecasting in small-scale decentralized energy systems.
Dynamic Reconfiguration for Multi-Context Architectures

Dynamic reconfiguration is possible on both fine-grain and coarse-grain architectures. One of the used methodology used consists in the use of multi-context architectures. Unfortunately, the multiple contexts bring power and area overhead. This paper introduces the Dynamic Unifier and reConfigurable blocK (DUCK) concept, a new structure to perform efficiently dynamic reconfiguration on both custom designed fine-grain and coarse grain architectures. The DUCK allows to separate the configuration path and the configuration registers which facilitates simultaneous configuration and computing steps. The reconfiguration process is presented in detail, and synthesis results are given for different structures. Our solution is finally validated with the implementation of a WCDMA (Wideband Code Division Multiple Access) receiver on a multi-context embedded FPGA and on the dynamically reconfigurable processor DART. This implementation demonstrates the interest and the efficiency of the use of dynamic reconfiguration and the proposed flexible structure.
A Review on Big Data Analytics

In the recent years, many businesses are exploiting big data. Over the last ten years, due to the technological advancement huge amount of data can be stored and is being generated in almost every sector. Actually, it is the collection of unstructured data collected from different sources. Many social media websites like Facebook, Twitter etc. are also generating a huge amount of data. Different techniques are needed to fetch meaningful information, processing and analysis of this data and many have been developed over the years. For example, many organizations may need information on their products so that they can improve the loopholes and can improve their marketing strategy.
Adding forecast support to workflow management system by classical logic formula computing

Workflow technology is a new hotspot in the area of computer application after the 1990s. In order to improve the performance of workflow management system (WfMS), a dynamic neural network based on classical formula computing is proposed to add forecast support to it. On the basis of the requirement of WfMS, neural unit, generation algorithm and computing algorithm for classical logic formula computing are discussed in detail and the experiment results show that this method is effective and universal.
HEPATIC AND RENAL HISTOPATHOLOGICAL AND ULTRASTRUCTURAL ALTERATIONS FOLLOWING EXPOSURE TO DIFFERENT GOLD NANOPARTICLE SIZES IN FEMALE PREGNANT RATS.

Nanoparticles (NPs) not only offer a great possibility for biomedical application, pharmaceutics, but also may be used for novel diagnostic and therapeutic approaches. Currently, there are no data available regarding to what extent the degree of toxicity of gold nanoparticles (AuNSs). This study aimed to investigate the histopathological and ultrastructural effect of AuNSs size on the liver and kidney of female pregnant rats. To achieve that gold nanoparticles of 10 nm, 25nm and 50 nm were Interperitoneally injected in female rats at 48 hr during rat pregnancy. Forty adult female albino rats were divided into four equal groups: The first one served as a control group, the second received 75 mg/kg/day AuNSs as 10 nm in size, the third received 75 mg/kg/day AuNSs as 25 nm in size and the fourth received 75 mg/kg/day AuNSs as 50 nm in size, All groups were scarified after 19days from gestation where liver and kidney specimens were collected at the end of the experiment for histological and ultrastructural examination, AuNSs treated groups revealed wide spread histological and ultrastructural alterations in the liver and kidney structure as dilated and congested hepatic blood vessels, widespread vacuolated and ballooned hepatocytes with early apoptotic changes, pyknotic hyper chromatic irregular nuclei with deteriorated chromatin condensation. The distal convoluted tubule had shrunken pyknotic nuclei and margination of heterochromatin with irregular nuclear envelope. This study conculcated that all size of AuNSs caused side effect in the liver and kidney of pregnant rates.
Secure network coding method merged with timestamp and homomorphic signature

A secure network coding method merged with timestamp and homomorphic signature which can solve security issues in wireless multi-hop networks was proposed.The timestamp into RSA-based homomorphic signature scheme was brought and used to produce random coefficients of network coding,thus made it possible to defend pollution attacks and replay attacks simultaneously while maintaining the homomorphic property of the signature.The analysis that mainly focus on was the influence of random coefficients on decoding probability of network coding and security of the proposed scheme.Results indicate that the proposed scheme can defend pollution attacks and replay attacks simultaneously,and the ratio of overhead between RSA-based homomorphic signature scheme and the proposed scheme is approximates 1.
LEMON GRASS ESSENTIAL OIL (CYMBOPOGUM FLEXUOSUS) IN HIGH-CONCENTRATE DIETS FOR LAMBS

The objective of this study was to evaluate the effect of the inclusion of two doses of monensin and lemon grass essential oil ( Cymbopogum flexuosus ) on nutrient intake and digestibility, ruminal fermentation and ingestive behavior of lambs fed a high-concentrate diet. Four ruminally cannulated ram lambs (44.7 ± 3.72 kg of BW and approximately 5 mo. old) in a 4 x 4 Latin square experimental design were used. The control diet (CONT) contained 15% of oat hay, 85% of concentrate and no additives. In the remaining diets it was included 12.5 (12.5MON) or 25.0 (25MON) mg/kg of monensin (as-fed basis) or 1 mL/kg of DM of lemon grass essential oil (EO). The treatments had no effect on the nutrient intake and digestibility. The lambs that received the EO treatment showed a higher ruminal pH in comparison to those that received the control diet. However, they did not differ from treatments with monensin. A quadratic response was observed for ruminal pH, with the highest value observed in the animals fed the diet 12.5MON. The lambs fed EO had a higher ruminal concentration of acetate than the diet with monensin. There was a quadratic response of monensin on ruminal concentration of acetate, with the lowest value observed for 12.5MON. The acetate:propionate ratio was lower in lambs fed 12.5MON compared to the control. EO decreased the ruminal concentration of butyrate; however, its concentration was higher in lambs fed monensin than EO diets. A lower concentration of total short chain fatty acids (SCFA) was observed in lambs fed 12.5MON. The alanine aminotransferase (ALT) blood concentration was higher in the lambs fed EO compared to the control. EO increased rumen concentration of blood glucose compared to the treatments containing monensin and decreased the number of eggs per gram of feces (EGF). In addition, there was a quadratic response of monensin on the EGF, with a higher value in the lambs fed 12.5MON. In conclusion, half of the daily dose of monensin was more effective at increasing ruminal pH than the full dose, with no negative reflection on nutrient intake and digestibility, as well as on the ingestive behavior and parasitic load of the animals. Thus, 12.5MON may be indicated for lambs feed high concentrate diet. EO proved to be a good natural source to replace ionophores in diets for lambs.
Discovering Semantic Links Between Synonyms, Hyponyms and Hypernyms

—This proposal aims for semantic enrichment between glossaries using the Simple Knowledge Organization System (SKOS) vocabulary to discover synonyms, hyponyms and hyperonyms semiautomatically, in Brazilian Portuguese, generating new semantic relationships based on WordNet. To evaluate the quality of this proposed model, experiments were performed by the use of two sets containing new relations, being one generated automatically and the other manually mapped by the domain expert. The applied evaluation metrics were precision, recall, f-score, and conﬁdence interval. The results obtained demonstrate that the applied method in the ﬁeld of Oil Production and Extraction (E&P) is effective, which suggests that it can be used to improve the quality of terminological mappings. The procedure, although adding complexity in its elaboration, can be reproduced in others domains.
Synthesis of Hollow Flower-Like Fe3O4/MnO2/Mn3O4 Magnetically Separable Microspheres with Valence Heterostructure for Dye Degradation

In this manuscript, hollow flower-like ferric oxide/manganese dioxide/trimanganese tetraoxide (Fe3O4/MnO2/Mn3O4) magnetically separable microspheres were prepared by combining a simple hydrothermal method and reduction method. As the MnO2 nanoflower working as precursor was partially reduced, Mn3O4 nanoparticles were in situ grown from the MnO2 nanosheet. The composite microspheres were characterized in detail by employing scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Brunauer–Emmett–Teller (BET), vibration sample magnetometer (VSM) and UV–visible spectrophotometer (UV–vis). Under visible light conditions, the test for degrading rhodamine B (RhB) was used to verify the photocatalytic activity of the photocatalyst. The results showed that the efficiency of the Fe3O4/MnO2/Mn3O4 photocatalyst in visible light for 130 min is 94.5%. The catalytic activity of photocatalyst far exceeded that of the Fe3O4/MnO2 component, and after four cycles, the catalytic performance of the catalyst remained at 78.4%. The superior properties of the photocatalyst came from improved surface area, enhanced light absorption, and efficient charge separation of the MnO2/Mn3O4 heterostructure. This study constructed a green and efficient valence heterostructure composite that created a promising photocatalyst for degrading organic contaminants in aqueous environments.
The physiological effects of dietary boron on growth performance and bone strength in female rats

The trace element boron (B) is essential for animals and humans as well as plants. It is required for bone, mineral metabolism and has a physiological role in animal nutrition. The extent and nature of possible physiological effects or potential risks of boron in animals and humans are still at primary stage and require further investigations. The aim of this study was to evaluate the effect of dietary boron supplementation as sodium tetraborate (0, 5, 10,15,20,25.30, and 35 mgB/100 g diet) on growth performance, bone ash content, and bone strength in adult female albino rats. The results indicated that, boron supplementation affected body weight gain, femur and tibia bone weight, density, mechanical properties ( moment of inertia and stress) , total lipids, and minerals ash content (calcium, inorganic phosphorous, magnesium, and copper). On the other hand, different experimental doses of boron did not have any effect on food intake, femur and tibia bone length, mineral ash content of zinc, and bending moment of tibia bone. In addition, the results revealed that, a statistical significant increase was observed in mean values of femur bending moment in the experimental rat groups fed on diets containing high doses of boron as sodium borate. These results suggest that physiologic amounts of boron may have beneficial effects upon bone minerals metabolism and, consequently, bone characteristics.
DESAIN DAN IMPLEMENTASI MESIN QUERY UNTUK XML

Salah satu kekuatan XML ( Extensible Markup Languange ) adalah pada fleksibilitasnya dalam menyatakan beragam jenis informasi dari beragam sumber. Untuk mengoptimalkan memanfaatkan kemampuan XML, diperlukan mekanisme yang memungkinkan ekstraksi, seleksi, integrasi, dan transformasi dari informasi yang disimpan dalam bentuk XML. Kemampuan dalam melakukan query pada sumber data XML menjadi semakin penting seiring dengan semakin populernya XML, dimana akan semakin banyak informasi yang akan disimpan, dipertukarkan, dan disediakan dalam bentuk tersebut. XQuery [2] adalah suatu bahasa query untuk XML yang dikembangkan oleh World Wide Web Consortium (W3C). Bahasa ini diharapkan dapat menjadi bahasa query standar untuk XML. Penelitian ini bertujuan membuat suatu mesin query bernama XQEngine yang mampu memproses dan mengeksekusi bahasa XQuery. Tidak semua fitur bahasa XQuery akan didukung. Ada beberapa bagian dari bahasa XQuery yang tidak diimplementasikan. Ada pula bagian yang diimplementasikan dengan mengalami penyesuaian. Walaupun XQEngine tidak mendukung semua fitur bahasa XQuery, namun dari uji analisa kasus penggunaan, dapat dilihat bahwa XQEngine mampu menangani jenis-jenis query yang esensial. XQEngine dibangun menggunakan C++Builder® dengan platform Windows™. Versi awal dibangun pada platform Linux dengan bahasa pemrograman Java™
Model-based fault diagnosis and tolerant control: the ESA's e.Deorbit mission

The ESA (European Space Agency) is currently pursuing the development of the e.Deorbit mission that will remove a large defunct satellite from Earth orbit: ENVISAT. To fulfil the mission autonomy requirements, ESA has decided to embed in the GNC (Guidance, Navigation, Control) software, fault tolerance capacities against actuator faults. The aim of this paper is to present the development and validation of a model-based fault diagnosis and tolerant control solution for such faults. The proposed solution is based on a new class of nonlinear unknown input observers, optimal in the $L_{2}$-gain sense, and a modified version of the nonlinear inverse pseudo control allocation technique. An intensive simulation campaign conducted within a high-fidelity nonlinear industrial simulator, demonstrates the efficiency of the approach.
A Review: use of Facial Marks For Twins Face Identification and Image Retrieval

In recent years, with the development of digital image techniques, the use of digital image retrieval process has increased dramatically. This paper provides the review to the detection and identification of twin faces by first recognizing the face of individual twins by matching some of the basic features of identical twins like nose, lips, eyes, ears, forehead, and face features. After that, the system will retrieves all those images relevant to the given query image from the image database. But, there is a problem, by retrieving such images because it results in large amount of images of identical twins when require only the images of one out of the identical twins, as there is high degree of similarity in facial appearance in identical twins. It also requires large amount of space and processing. So, this paper presents the new approach called the retrieval of twin’s images using their facial marks. Keywords: Facial Marks; Facial Recognition; Identical Twins; Image Retrieval
Comet Assay: Quantification of Damaged DNA in Catla catla Exposed to Endosulfan+Chlorpyrifos

| In an acute toxicity trail, LC50 and LC100value (96 hr) of endosulfan (END)+chlorpyrifos (CPF) mixture for Catla catla was computed. The genotoxicity of END+CPF mixture in RBCs of fish was also evaluated by comet assay. To check the genotoxicity of END+CPF mixture, blood of fish was sampled after 24-hr of intervals. Some fishes were also kept in clean water known as negative control (NC) and for positive control (PC) cyclophosphamide was injected into fish. The tolerance limits of C. catla against END+CPF was computed as 1.35±0. 01μgL(LC50) and 2.25±0. 02μgL(LC100). Genotoxic results showed that END+CPF mixture caused significant damage to nuclei (22.58±5.37%) and GDI (0.73±0.15%) in RBCs of fish as compare to control. Aduration-specific damage to DNA was observed in RBCs of C. catla. Article History Received: September 04, 2018 Revised: June 03, 2019 Accepted: June 08, 2019 Published: June 21, 2019 Authors’ Contributions HN performed the research and wrote the article. SA planned and supervised the study. KA provided lab facilities for research. MAT and LS helped in writing the article. GN helped in statistical anlyses.
Dynamic Coverage Problems in Sensor Networks

One of the fundamental issues in sensor networks is related to analyzing the coverage, or how well a network of sensors monitors the physical space for an intrusion. The coverage is a measure of the quality of service (QoS) of the sensor network and has been the subject of various studies. The concept of coverage was introduced by Gage in 1992, who studied it in relation to multi-robot systems. He defined three classes of coverage problems: blanket coverage (also known as area coverage), where the goal is to achieve a static arrangement of sensing elements that maximizes the detection rate of targets appearing in the region, sweep coverage, where the goal is to move a number of sensors across the region as to maximize the probability of detecting a target, and barrier coverage, where the objective is to protect the region from unauthorized penetration. While blanket coverage is relatively well researched, the other two types of coverage have been less studied and offer much greater technical challenges. In this survey we concentrate on the two dynamic types of coverage problems, barrier and sweep coverage. We review recent results, proof techniques, analyses, and open problems and challenges. We focus on methods that allow the performance of the algorithms, i.e.