Miracle-dz/UniFAR-FTUs huggingface dataset:
COMBINING MULTIPLE APPROACHES FOR ON-LINE SIGNATURE VERIFICATION

An on-line signature verification system exploitin g temporal, local and global information through score-level fusion is pr esented. Global information is extracted with a feature-based representation and r ecognized by using Mahalanobis distance Classifier. Temporal information is extrac ted as time functions of various dynamic properties and recognized by using Dynamic Time Warping Model. Local information is extracted by using Discrete Radon Tr ansform and recognized by using Dynamic Time Warping Model. Experimental results are given on the SVC2004 database (40 signers, 1600 signatures) for random a nd skilled forgeries. It is shown that the performance of all systems is improved when usi ng more signatures in the enrollment. The three proposed systems are shown to give complementary recognition information which is successfully exploited using s core-level fusion. The combining strategy leads to 0,18 EER for skilled forgeries an d 0,07 for random forgeries in comparison to the individual algorithms. The goal of biometrics is to infer the identity of people based on anatomical or behavioral data (e.g., fingerprint, face, signature , or voice) (2). The current interest in biometrics is due to the increasing number of impor tant applications where an automatic assessment of identity is crucial. Within biometric s, on-line signature verification has been an intense research area because of the social and legal acceptance and widespread use of the written signature as a personal authenti cation method (4), and still is a challenging problem. This is mainly due to the larg e intra-class variations and, when considering forgeries, small inter-class variations . In order to increase the security of biometric syst ems some approaches attempt to reach a better performance by combination of variou s biometric modalities. Such multibiometric systems consist of several biometric subsystems for different modalities (e.g. fingerprint and iris). In general a multibiom etric system is based on one of three fusion levels, feature extraction level, matching s core level or decision level (3). In the feature extraction level the information extracted from the different sensors are stored in separate feature vectors. These feature vectors are combined to a joint feature vector, which is the basis for the matching process. In som e cases this results in a very high dimensional joint feature vector. The fusion on mat ching score level is based on the combination of matching scores after the comparison of reference data and test data. Additionally, matching scores of the different moda lities may be weighted. The fusion results in a new matching score, which is the basis for decision. With the fusion on the decision level, each biometric subsystem involved i s completely processed. Afterwards, the individual decisions are combined to a final de cision, e.g. by Boolean operations (3).
Bolt loosening detection based on audio classification

As the most widely used coupling structure in electromechanical systems, bolt coupling is the important part in these systems. The reliability and strength of bolted joint are affected by pretension force, which is one of the most important factors to ensure the stability of bolt coupling. The inspection personnel hit the bolt with a hammer and judge the state of the bolt based on the sound. Although this method is very simple, the ability of the human ear to distinguish the knocking sound is poor, it can only distinguish the bolt with larger looseness. So a bolt loosening detection method based on audio classification is presented in this article. First, the hammering sound at different levels of bolt loosening was collected by smartphone. Then, the audio data were extracted to form a dataset. Finally, the support vector machine was used to train and test the dataset, and obtain the bolt loosening quantitative detection. A series of experiments were carried on to verify the accuracy and stability of this method. The results show that this method has high recognition accuracy and strong noise immunity. Therefore, this method can effectively reduce the occurrence of disasters.
Performance-Based Instruction: Linking Training to Business Results

This recent addition to the field of performance-based education is a readable how-to manual designed for human resource managers, faculty and students interested in organizational development and "rugged individualists," an artificial category given the general focus of the book but one obviously designed to pick up any stray buyers that might respond to this appellation. The authors, Dale Brethower and Karolyn Smalley--the former a professor of psychology at Western Michigan University and the latter a management consultant and former human resource development administrator--argue that applying the principles of performance-based instruction will improve productivity in both the workplace and the classroom.
Review of the Quantitative Resilience Methods in Water Distribution Networks

Water distribution networks (WDNs) are critical contributors to the social welfare, economic growth, and public health in cities. Under the uncertainties that are introduced owing to climate change, urban development, aging components, and interdependent infrastructure, the WDN performance must be evaluated using continuously innovative methods and data acquisition. Quantitative resilience assessments provide useful information for WDN operators and planners, enabling support systems that can withstand disasters, recover quickly from outages, and adapt to uncertain environments. This study reviews contemporary approaches for quantifying the resilience of WDNs. 1508 journal articles published from 1950 to 2018 are identified under systematic review guidelines. 137 references that focus on the quantitative resilience methods of WDN are classified as surrogate measures, simulation methods, network theory approaches, and fault detection and isolation approaches. This study identifies the resilience capability of the WDNs and describes the related terms of absorptive, restorative, and adaptive capabilities. It also discusses the metrics, research progresses, and limitations associated with each method. Finally, this study indicates the challenges associated with the quantification of WDNs that should be overcome for achieving improved resilience assessments in the future.
Ranking Methods for Global Optimization of Molecular Structures

This work presents heuristics for searching large sets of molecular structures for low-energy, stable systems. The goal is to find the globally optimal structures in less time or by consuming less computational resources. The strategies intermittently evaluate and rank structures during molecular dynamics optimizations, culling possible weaker solutions from evaluations earlier, leaving better solutions to receive more simulation time. Although some imprecision was introduced from not allowing all structures to fully optimize before ranking, the strategies identify metrics that can be used to make these searches more efficient when computational resources are limited.
A field programmable gate array architecture for two-dimensional partial reconfiguration

Reconfigurable machines can accelerate many applications by adapting to their needs through hardware reconfiguration. Partial reconfiguration allows the reconfiguration of a portion of a chip while the rest of the chip is busy working on tasks. Operating system models have been proposed for partially reconfigurable machines to handle the scheduling and placement of tasks. They are called OS4RC in this dissertation. The main goal of this research is to address some problems that come from the gap between OS4RC and existing chip architectures and the gap between OS4RC models and practical applications. Some existing OS4RC models are based on an impractical assumption that there is no data exchange channel between IP (Intellectual Property) circuits residing on a Field Programmable Gate Array (FPGA) chip and between an IP circuit and FPGA I/O pins. For models that do not have such an assumption, their inter-IP communication channels have severe drawbacks. Those channels do not work well with 2-D partial reconfiguration. They are not suitable for intensive data stream processing. And frequently they are very complicated to design and very expensive. To address these problems, a new chip architecture that can better support inter-IP and IP-I/O communication is proposed and a corresponding OS4RC kernel is then specified. The proposed FPGA architecture is based on an array of clusters of configurable logic blocks, with each cluster serving as a partial reconfiguration unit, and a mesh of segmented buses that provides inter-IP and IP-I/O communication channels. The proposed OS4RC kernel takes care of the scheduling, placement, and routing of circuits under the constraints of the proposed architecture. Features of the new architecture in turns reduce the kernel execution times and enable the runtime scheduling, placement and routing. The area cost and the configuration memory size of the new chip architecture are calculated and analyzed. And the efficiency of the OS4RC kernel is evaluated via simulation using three different task models.
Draught risk index tool for building energy simulations

Flow elements combined with a building energy simulation tool can be used to indicate areas and periods when there is a risk of draught in a room. The study tests this concept by making a tool for post-processing of data from building energy simulations. The objective is to show indications of draught risk during a whole year, giving building designers a tool for the design stage of a building. The tool uses simple one-at-a-time calculations of flow elements and assesses the uncertainty of the result by counting the number of overlapping flow elements. The calculation time is low, making it usable in the early design stage to optimise the building layout. The tool provides an overview of the general draught pattern over a period, e.g. a whole year, and of how often there is a draught risk. Flow elements, thermal comfort, environment, design phase Introduction Draught is one of the main causes of complaints about the indoor environment in buildings (1). When people experience draught, they take action to avoid it. This may lead to higher energy consumption, e.g. by turning up the heat to compensate. By predicting the draught risk in the early design stage, the building design can be optimised for both low energy use and low draught risk. In naturally ventilated buildings, this is especially important, as the ventilation is integrated in the building envelope and is closely linked to the current outdoor climate. Draught risk can be simulated by CFD, but this is time consuming and therefore not used. On the other hand, building energy simulation tools are available that are faster but lack information on airflows. The two tools have been linked (2) to supplement each other for thermal comfort simulation, but the CFD is slowing the process down. Another way of estimating draught risk is to use flow elements. Flow elements describe the airflow in a room by equations for velocity distribution and flow patterns. Flow elements are derived for a number of standard situations and can be divided into categories depending on e.g. isothermal / nonisothermal, 2D plane flow / 3D flow, flow close to a wall or ceiling / free flow. Flow elements also describe flow by a cold down draught from a cold wall like a fully glassed wall (3,4). By using flow elements, velocities can be calculated in any affected point in the room and the accuracy in each point is not dependent on a grid or grid density. Using flow elements combined with building energy simulation tools, the draught in the room can be estimated for
Penerapan Academic Controversy Dalam Meningkatkan Aktivitas Belajar

The purpose of this study is to find out student learning activities before applying the Academic Controversy method, then the learning process using the Academic Controversy method, and student learning activities after applying the Academic Controversy method on social studies subjects in each cycle. The method used in this study is Classroom Action Research (CAR) which consists of four stages repeatedly, namely planning, action, observation and reflection. The technique of collecting data was carried out through the evaluation instruments of the pro and contra debates then with observation sheets for student and teacher activities. Based on the results of the study, the percentage of student learning activities before being applied to the academic controversy (academic controversy) method was only 31.2% with the less active category, after the application of the academic controversy (academic controversy) method in the first cycle student learning activities increased to 62 % included in the category is quite active. And student learning activities continue to increase in the second cycle which is at a very active stage which is 86%. From these data it can be concluded that the application of the method of academic controversy (academic controversy) can increase learning activities.
Redescription of Arganasaurus (Metoposaurus) azerouali (Dutuit) comb. nov. from the Upper Triassic of the Argana Basin (Morocco), and the first phylogenetic analysis of the Metoposauridae (Amphibia, Temnospondyli)

A systematic revision of the temnospondyl ‘Metoposaurus’ azerouali Dutuit from the Late Triassic of the Argana Basin (Western High Atlas, Morocco) is presented. The type material is redescribed in detail, and a preliminary phylogenetic analysis – the first one dealing with all metoposaurid species – is also conducted in order to test its position within the Metoposauridae. Our analysis places ‘Metoposaurus’ azerouali as sister‐taxon to Arganasaurus lyazidi in a robust clade supported by two unambiguous synapomorphies (bulge‐like tabular horn and exoccipital process visible in dorsal view) and two ambiguous synapomorphies (cultriform process of uniform width and subtriangular posterior Meckelian fenestra). We therefore propose the new combination Arganasaurus azerouali comb. nov. for the species ‘M. ’ azerouali. Our analysis also confirms that the central Laurasian genus Metoposaurus is monophyletic but not the genus Koskinonodon, which deserves its own systematic revision. By consequent, the Late Triassic rich vertebrate fauna from the Argana Basin comprises the metoposauroid Almasaurus habazzi, the basal metoposaurid Dutuitosaurus ouazzoui, and the genus Arganasaurus which is represented by the type species A. lyazidi and A. azerouali comb. nov. Combined with the stratigraphical and geographical occurrences of the taxa, our phylogenetic analysis suggests that metoposaurids may have appeared during the Longobardian (late Ladinian) in central Pangea. Their diversification may be linked to the Carnian Pluvial Episode. At least, their extinction may have occurred during the Rhaetian because of the aridification of the climate and/or competition with amniotes.
Automated peer-to-peer security-update propagation network

In this project we design and implement a security-update propagation network that employs peer-to-peer model, where computers act as equals and all hosts participate in providing security update services. When a computer node joins the network to download new security updates it is automatically enlisted to serve other computers with older updates. Hence, as network size becomes larger its capability to provide service will increase and performance balances very well. To protect the network against malicious computers that may join in to spread infected files, we employ digital signature to verify the validity of any download and identify infected nodes. In addition, we incorporate other features in our network such as: the support for multiple platforms, automation, new update notification, and software update.
Comparative Analysis of Motion base Image Segmentation using Machine Learning Techniques

Objectives: In the computer vision task, motion based image segmentation is the foremost step which warrants for further research. Several progressive techniques are being created for motion base image segmentation. Machine learning methods are implemented and analyzed in this paper. Methods: Motion is one of the useful characteristics to segment object from the image as it provides a classification of pixel in motion or motionless type. Machine learning methods are giving promising result in classification type problems. Machine learning methods reduce the execution time. In this type of technique a training is required in beginning after that all processes are performed automatically. This paper presents two machine learning technique SVM and LS-SVM. The Segmentation of image can be done by selecting image feature. In proposed method intensity change basis of motion is used as texture feature. Findings: Both of techniques classify pixels of an image between two types, 1. Appropriate to a motion and 2. Not appropriate to motion. Results obtained using this approach shows that machine learning methods are very promising techniques for this type of area. Application/Improvement: LS-SVM method is very promising with enhancement in execution time and segmented object result quality as compared to SVM.
Tomographie par cohérence optique confocale en ligne multimodale pour le diagnostic non invasif des cancers cutanés

Le cancer de la peau est un enjeu majeur de sante publique. Il represente le type de cancer ayant le plus fort taux de prevalence et le nombre de cas semble etre en constante augmentation. Aujourd'hui, la methode de reference pour le diagnostic du cancer cutane necessite un echantillon de tissu suspect, appele biopsie, preleve apres un simple examen visuel de la peau du patient. Par consequent, pres de 60 % des biopsies se revelent etre benignes et environ 20 % des cancers de la peau ne sont pas detectes.Les travaux de recherche presentes dans ce manuscrit de these portent sur le developpement d'un dispositif de tomographie par coherence optique confocale en ligne (LC-OCT) capable de produire des images d'une qualite similaire aux coupes histologiques de maniere non invasive et in vivo. Le prototype concu fonctionne a une longueur d'onde centrale autour de 800 nm avec une largeur spectrale d'environ 150 nm. Il a ete applique a l'imagerie in vivo de la peau avec une resolution spatiale quasi-isotrope d'environ 1 µm et une profondeur de penetration de 400 µm. Ce dispositif pourrait alors etre utilise pour ameliorer l'efficacite du processus de diagnostic du cancer de la peau en limitant le nombre de cas non detectes ainsi que le nombre de biopsies inutiles.Nous presentons ensuite un dispositif de LC-OCT fonctionnant dans deux bandes spectrales centrees autour de 770 nm et 1250 nm. La premiere bande produit des images a haute resolution (1.3 µm x 1.2 µm, lateral x axial) tandis que la seconde offre une profondeur de penetration accrue (700 µm). En fusionnant les images produites dans les deux bandes il a ete possible de produire des images avec une bonne resolution en superficie tout en ayant une profondeur de penetration etendue. De plus, acquerir des images d'un echantillon dans deux bandes spectrales differentes permet dans une certaine mesure d'obtenir des informations sur les proprietes spectrales de l'echantillon.Finalement, nous presentons une preuve de concept d'un dispositif de LC-OCT couple avec un microscope Raman ainsi que quelques exemples d'application. La microscopie Raman est une modalite spectroscopique qui permet d'identifier des molecules et ainsi de mesurer "l'empreinte digitale" d'un echantillon. Cette modalite pourrait alors fournir des informations complementaires aux images morphologiques acquises par LC-OCT a propos de la composition biomoleculaire de l'echantillon.
Directing crossover for reduction of bloat in GP

A method is proposed to reduce the amount of invisible code (or bloat) produced in individuals while searching for a parsimonious solution under tree structured genetic programming. Known as directed crossover this process involves the identification of highly fit nodes to use as crossover points during operator application. Three test problems, including medical data classification, are used to assess the performance of directed crossover when applied at various thresholds. Results, collected over 1260 independent runs, identify conditions under which directed crossover reduces code bloat.
It's time for a semantic engine

A common computational goal is to encapsulate the modeling of a target phenomenon within a unified and comprehensive "engine", which addresses a broad range of the required processing tasks. This goal is followed in common modeling of the morphological and syntactic levels of natural language, where most processing tasks are encapsulated within morphological analyzers and syntactic parsers. In this talk I suggest that computational modeling of the semantic level should also focus on encapsulating the various processing tasks within a unified module (engine). The input/output specification of such engine (API) can be based on the textual entailment paradigm, which will be described in brief and suggested as an attractive framework for applied semantic inference. The talk will illustrate an initial proposal for the engine's API, designed to be embedded within the prominent language processing applications. Finally, I will sketch the entailment formalism and efficient inference algorithm developed at Bar-Ilan University, which illustrates a principled transformational (rather than interpretational) approach towards developing a comprehensive semantic engine.
Toward a French VerbeNet (Vers la création d’un Verbnet français) [in French]

VerbNet is an English lexical resource that has proven useful for NLP due to its high coverage and coherent classification. Such a resource doesn't exist for French, despite some (mostly automatic and unsupervised) at- tempts. We show how to semi-automatically adapt VerbNet using existing lexical resources, namely LVF (Les Verbes Francais) and LG (Lexique-Grammaire).
A robust endmember constrained non-negative matrix factorization method for hyperspectral unmixing

This paper presents a new method based non-negative matrix factorization (NMF) for hyperspectral unmixing, termed robust endmember constrained NMF (RECNMF). The objective function of RECNMF can not only reduce the effect of noise and outliers but also can reduce the size of convex formed by the endmembers and the correlation between the endmembers. The algorithm is solved by the projected gradient method. The effectiveness of RECNMF is illustrated by comparing its performance with the state-of-the-art algorithms in simulated data.
Data Security over Cloud

Data security and Access control is a challenging research work in Cloud Computing. Cloud service users upload there private and confidential data over the cloud. Security must be provided to such outsourced data, so that user are not worried while uploading there confidential data. Recent technologies suffer from computational problem of keys and there exchange. This paper addresses the various problems and issues involved in using cloud services such as key generation, data security, authentication. This paper addresses this problem using access control technique that ensures only valid users will access there outsourced data. This paper proposes a Diffie-Hellman key exchange protocol between cloud service provider and the user for secretly sharing a symmetric key for secure data access that solves the problem of key distribution and management. Authentication will be done using Two Factor Authentication Technique with the help of key generated using Diffie-Hellman key exchange algorithm The proposed work is highly efficient and secure under existing security models.