Miracle-dz/UniFAR-FTUs huggingface dataset:
Signed bits and fast exponentiation

Nous donnons une analyse precise du gain obtenu en utilisant la representation des entiers sous la forme non-adjacente, plutot que la representation binaire, lorsqu'il s'agit de calculer les puissances d'elements dans un groupe dans lequel l'inversion est facile. En comptant le nombre de multiplications pour un exposant aleatoire ayant un nombre donne de bits dans son ecriture binaire, nous obtenons une version precise du resultat asymptotique connu, selon lequel en moyenne, un parmi trois bits signes de la forme non-adjacente n'est pas nul. Cela montre que l'utilisation des bits signes reduit le cout de l'exponentiation d'un neuvieme, par rapport a la methode ordinaire consistant a des elevations au carre et a des multiplications repetees.
THEORETICAL MODELLING OF THERMAL CONDUCTIVITY OF DEEP EUTECTIC SOLVENT BASED NANOFLUID

In this research, the thermal conductivities of graphene oxide nano-particles (GO) dispersed in deep eutectic solvents (DESs) composed of ethylene glycol (EG) as a hydrogen bond donor (HBD) and methyl tri-phenyl phosphonium bromide (MTPB) as a salt, at weight fractions of 0.01%, 0.02% and 0.05%, were studied and quantitatively analysed. The molar ratios of DES (HBD:Salt) used in this study are 3:1 and 5:1.The thermal conductivity data of the nano-fluid samples were measured at temperatures of 25-70 °C and the results were compared with theoretical models. Rashmi and Kumar’ models showed conflicting prediction performance. While, Rashmi’s model can predict thermal conductivity with error as low as 0.1%, Kumar’s model error varied from 3-55%. Thus, in this work, a simple empirical modification to Kumar’s model is presented which improves the predictions accuracy compared to that of Rashmi’s model.
Automatic Pipeline Generation by the Sequential Segmentation and Skelton Construction of Point Cloud

Point clouds are the main output of automatic data collection using laser-scanner technologies. The large numbers of points scanned from pipeline plants make the plant reconstruct very difficult. We have developed a system based on the Point cloud Library (PCL), to find, recognize and reconstruct 3D pipes within point-clouds fully automatically. The proposed approach consists of pre-processing point cloud data, segmentation, skeleton extraction and automatic cylinder fitting for pipeline. The presented results shows that the proposed method enables reliable 3D models of pipelines, which could be successfully incorporated into the reconstruction of a plant information modelling method and utilized for, assist maintenance and expansion of existing plants.
Supporting the Industrial Design Process With Spatial Augmented Reality

Our research involves using Spatial Augmented Reality (SAR) for industrial design. SAR allows us to project onto physical objects to give them a different appearance. This is beneficial for industrial design because we can project a design for a device directly onto a physical prototype. This projected design can be interactive which also means it can be modified in real time. An example of this method of prototyping is shown in Figure 1. We constructed a low-fidelity prototype of a car dashboard out of medium-density fibreboard (MDF) and painted it with a matte white paint. We then project a design onto the prototype. The use of AR for design has been investigated in the past. Car manufacturers have used AR for evaluating a car interior design [2]. Our design evaluation system differs in the display technology used. Our SAR implementation is based on Shader Lamps [1] which uses calibrated projectors to change the appearance of objects.
Intellectual Property Rights, Quality of Institutions, and Foreign Direct Investment into Developing Asia

Developing Asian countries are strengthening their intellectual property rights (IPR) regime as they themselves become producers of intellectual property. At the same time, developing Asia has attracted large amounts of foreign direct investment (FDI) and this trend is expected to continue in light of the region’s strong growth prospects. In this paper, we explore the relationship between IPR and FDI in developing Asia. To do so, we develop a theoretical model which predicts that stronger IPR protection attracts more FDI in countries with small informal economies—i.e., strong institutions—but not in countries with large informal economies—i.e., weak institutions. Our empirical analysis, based on a threshold effect model, yields some evidence which supports our theoretical model.
Review of Studies on Agility in Knowledge Management

 Abstract— Agility in Knowledge Management (AKM) tries to capture agility requirements and their respective answers within the framework of knowledge and learning for organizations. Since it is rather a new construct, it is difficult to claim that it has been sufficiently discussed and analyzed in practical and theoretical realms. Like the term ‘agile learning’, it is also commonly addressed in the software development and information technology fields and across the related areas where those technologies can be applied. The organizational perspective towards AKM, seems to need some more time to become scholarly mature. Nevertheless, in the literature one can come across some implicit usages of this term occasionally. This research is aimed to explore the conceptual background of agility in KM, re-conceptualize it and extend it to business applications with a special focus on e-business.
Towards bladder function modeling: FES induced detrusor activity modelling

We present a smooth muscle model which enables the simulation of its contraction under functional electrical stimulation (FES). The model takes into account chemical and microscopic mechanics of the contraction. In order to illustrate the model performances, we simulate a well known example: the behaviour of the bladder under electrical stimulation using a Finetech / Brindley implant. This approach allows to compare our qualitative results with experimental data available in the literature. Simulated output (pressure, volume and urine ux) show good consistency both in shape and time course. With the objective to obtain quantitative simulations, we propose a setup for animal in-vivo experiments which should allow us to perform the identication of the model parameters. Preliminary experimental data is presented.
Pulse-based Features for Face Presentation Attack Detection

In this contribution, we propose to tackle the face presentation attack detection (PAD) problem by using features derived from a pulse signal obtained through remote photoplesthymography (rPPG). Recent studies show that the pulse signal provides information on the liveness of a subject; hence it can be used to identify whether a recorded video sequence originates from a genuine user or is an attack. Inspired by work made for speaker presentation attack detection, we propose to use long-term spectral statistical features of the pulse signal to discriminate real accesses from attack attempts. Experiments are performed on different, publicly available databases and following associated protocols. Obtained results suggest that the proposed features are effective for this task, and we empirically show that our approach performs better than state-of-the-art rPPG-based presentation attack detection algorithms.
Statistical Analysis of Short-time Option Prices Based on a Levy Model

OF THE THESIS Statistical Analysis of Short-time Option Prices Based on a Lévy Model by Wang, Weiliang Master of Arts in Mathematics, Washington University in St. Louis, 2018. Professor José E. Figueroa-López, Research Advisor The Black-Scholes model has been widely used to find the prices of option, while several generalizations have been made due to its limitation. In this thesis, we consider one of the generalizations—the exponential Lévy model with a mixture of CGMY process and Brownian motion. We state the main results of the first-, secondand third-order expansions for close-to-the-money call option prices under this model. Using importance sampling based on Monte Carlo method, a dataset of call option prices can be simulated. Comparing the simulated true prices with the three different order approximations, we find that the higher-order approximation is more accurate than the lower-order in most cases, which can be used for calibrating the parameters in the model. In order to verify these results, we use call option prices obtained from the Standard & Poor’s 500 index options. The third-order approximation of this real dataset is not as accurate as before.
Characterizing California-specific cattle feed rations and improve modeling of enteric fermentation for California's Greenhouse Gas Inventory

7 Executive Summary . 9 Introduction. 11 Materials and Methods. 12 Data Sources . 12 Dairy cattle diets . 12 Beef cattle diets. 13 Methane emissions. 13 Model Development. 14 Lactating cows . 14 Feedlot cattle. 15 Model Evaluation. 15 Estimate of Emissions from Cattle Groups in California. 16 Cattle population statistics . 16 Estimating emission factors and population emissions. 17 Results and Discussion. 17 Feed intake and dietary characteristics of California cattle . 17 Lactating dairy cows. 17 Dairy heifers and dry cows . 19 Beef cattle groups . 21 Model Development . 22 Model Evaluation . 25 Lactating dairy cows. 25 Non-lactating dairy cows . 28 Feedlot cattle. 28 Replacement beef and stockers. 29 Beef cows and bulls . 30 Enteric CH4 emission estimates for California cattle groups . 35 Dairy cows . 35 Dairy heifers . 35 Feedlot cattle. 36
Family systems and mental health issues: a resilience approach

In many cases the consumers of mental health information and support are the families of mental health sufferers. The aim of the project was to understand resilience in people who live with or support a family member with a diagnosed or undiagnosed mental illness. Participants were 15 carers (one male, 14 female). Semi-structured interviews were transcribed and analysed using content analysis. Eight recurring themes emerged which indicated the challenges the carers faced and provided indications of the positive and negative personal, family and social factors that impacted on their lives. These themes were ‘Getting to CLAN WA’, ‘Accessing help including CLAN WA’, ‘Impact of living with a person who has a mental illness or problematic behaviour’, ‘Family and cultural issues’, ‘Communication within the family’,‘Coping strategies and evidence of resilience’, ‘Social support’ and ‘Notion of sacrifice’. There is still considerable work to do in supporting people who live with or support a family member in these circumstances. The findings demonstrate that individuals living with adversity can do more than just survive the process.
Laser Welding of Aluminium-Steel Clad Materials for Naval Applications

Several electronic, naval, aeronautic and automotive components are made by different materials joined together in order to improve mechanical and functional properties. Functionalities provided by clad metals can be grouped into structural, thermal expansion management, thermo-mechanical control, electrical, magnetic, corrosion resistant, joining and cosmetic applications to cite as few (Chen et al., 2005). The demand for dissimilar material joints continuously grows because one material can provide only a small spectrum of chemical, physical and mechanical characteristics required for the investigated application respect to the bior multi-layer material joints. Moreover considerable weight savings can be achieved by using lightweight materials clad to strength ones directly. For these reasons, researchers and manufacturers continuously evaluate the application of traditional and/or advanced joining processes to clad dissimilar materials and obtain transition joints optimally. Focusing the attention on steel/aluminium joints and shipbuilding industry, the development of lightweight and fast-speed vessels requires a great number of aluminium/steel structural transition joints (STJs) in order to connect aluminium superstructures to the steel hull (Chao et al., 1997). Using this solution, the total weight of a ship is reduced due to the lighter aluminium superstructure. However, problems in service may occurred by relations at the atomic level between iron and aluminium and differences existing in physical and chemical properties of the base metals. One of the most undesired effect derives from the large electrochemical difference of 1.22 volts between iron and aluminium that causes a high susceptibility to both inter-crystalline and galvanic corrosion along the STJ interface. Fusion welding processes, initially used to produce the aluminium/steel STJs with desired physical and mechanical features, are narrowly applied because the subsidiary precipitates and brittle Al/Fe inter-metallic phases, created during fusion and solidification and located along the interface, are severely exposed to corrosion, troubling joint cohesion (Durgutlu et al., 2005). The high heat input affects the different thermal properties of the two materials— thermal expansion, heat capacity and thermal conductivity—and may lead to very complex stress fields. Moreover, the heat input causes the lattice transformation and the formation of inter-metallic phases. In iron (cubic body-centred up to 911 °C) and aluminium (cubic facecentred) joints, the inter-metallic phases present a high hardness and low ductility. The 4
A REVIEW OF IMAGE FUSION TECHNIQUES AND PERFORMANCE EVALUATION FOR MEDICAL APPLICATIONS

Multimodality medical image fusion is utilized to improve the imaging quality and reduce randomness and redundancy in order to increment the clinical applicability of medical images for diagnosis and assessment of medical problems. Image fusion process can b e defined as the integration of information from a multiple of registered images without the introduction of distortion. It is often not possible to get an image that contains all relevant objects in focus. One way to surmount this problem is image fusion, in which one can acquire a series of pictures with different focus settings and fuse them to produce an image with elongated depth of field. Image fusion techniques can improve the quality and increment the application of these data. The importance of information offered by the medical images for diagnosis support can b e incremented by combining images from different compactable medical devices. Medical image fusion has been used to derive useful information from multimodality medical image data. Fused image will be represented in format capable for computer processing. Image fusion can be performed by means of wavelet transform, complex wavelet transform, non sub sampled contourlet transform etc. The resulting image contains more information compared to individual images. This paper describes different techniques and aspects of image fusion for multimodal medical imaging.
Managing the duality of IHRM: unravelling the strategy and perceptions of key actors in South Korean MNCs

This research aims to extend our understanding of the duality between global integration and local responsiveness in multinational corporations (MNCs) by exploring the perceptions of corporate HR actors regarding the intra-organisational factors that alter the balance between these pressures. It examines the perceptions and actions of key actors in the context of two Korean MNCs. The study shows the importance attributed to a range of socio-procedural factors by corporate actors and which, therefore, inform the practical management of the dual forces, notably: HR expertise, social ties, trustworthy relationships and co-involvement in decision processes.
State-Trait Anxiety and Co-morbid Depression among Anxiety Disorder Patients

Anxiety is an appropriate response to threats, but it can be abnormal when its level is out of proportion to a threat. In extreme forms, anxiety can impair our daily functioning. Anxiety disorders are basically related to stress, reactions to stress (usually maladaptive) and individual proneness to anxiety. An important aspect of anxiety disorders is the issue of co-morbidity. Even apart from the considerable co-morbidity figures between anxiety disorders themselves, co-morbidity rates between anxiety disorders and depressive disorders are very high. This study focused on state-trait anxiety and co-morbid depression among anxiety disorder patients. The results revealed that anxiety patients have significantly higher mean score for different dimensions of state-trait anxiety and co-morbid depression than healthy normals. There were moderate to high positive correlations between co-morbid depression and all the dimensions of state-trait anxiety except suspiciousness. © 2013 Guru Journal of Behavioral and Social Sciences Anxiety is a normal human emotion. But in excess, it destabilizes the individual. Anxiety is often a diffuse, unpleasant and uncomfortable feeling of apprehension, accompanied by one or more bodily sensations that characteristically recur in the same manner in the person. Anxiety is considered excessive or pathological when it arises in the absence of challenge or stress, when it is out of proportion to the challenge or stress in duration or severity, when it results in significant distress, and when it results in psychological, social, occupational, biological or other impairments. Anxiety encompasses behavioral, affective and cognitive responses to the perception of danger. Anxiety disorders are basically related to stress, reactions to stress (usually maladaptive) and individual proneness to anxiety. Anxiety disorders are one of the most prevalent of all psychiatric disorders in the general population. The DSM IV-TR recognizes the following specific types of anxiety disorders: phobic disorders, such as specific phobia, social phobia and agoraphobia; panic disorder with agoraphobia and without agoraphobia; generalized anxiety disorder; obsessive compulsive disorder; and acute and posttraumatic stress disorder.
PCNN: Environment Adaptive Model Without Finetuning

Convolutional Neural Networks (CNNs) have achieved tremendous success for many computer vision tasks, which shows a promising perspective of deploying CNNs on mobile platforms. An obstacle to this promising perspective is the tension between intensive resource consumption of CNNs and limited resource budget on mobile platforms. Existing works generally utilize a simpler architecture with lower accuracy for a higher energy-efficiency, i.e., trading accuracy for resource consumption. An emerging opportunity to both increasing accuracy and decreasing resource consumption is class skew, i.e., the strong temporal and spatial locality of the appearance of classes. However, it is challenging to efficiently utilize the class skew due to both the frequent switches and the huge number of class skews. Existing works use transfer learning to adapt the model towards the class skew during runtime, which consumes resource intensively. In this paper, we propose probability layer, an easily-implemented and highly flexible add-on module to adapt the model efficiently during runtime without any fine-tuning and achieving an equivalent or better performance than transfer learning. Further, both increasing accuracy and decreasing resource consumption can be achieved during runtime through the combination of probability layer and pruning methods.
AMBERBOA SOSNOVSKYI ILJIN IN VITRO CULTURE OBTAINING

The in vitro cultivation conditions for obtaining the isolated culture of A. sosnovskyi were firstly developed. Callus culture was obtained on MS (Murashige and Skoog) basal medium, supplemented with 2.0 mg/L indole 3 acetic acid (IAA), 0.2 mg/L kinetin, but further growth was supported on both MS medium and its modified variant with approximately same concentrations of auxins and cytokinins (0.5 mg/L IAA, 0.2 mg/L kinetin and 0.2 mg/L 6-benzylaminopurine (BAP)). Obtained tissues were possess direct and undirect regeneration ability. The influence of nutrient media composition on growth parameters as well as regeneration ability of callus cultures was studied. On the modified medium the content of dry substances of callus culture was 7% in comparison with MS medium where this parameter was estimated as 5%.
THE REMOTE MEMORY REFERENCE COMPLEXITY OF THE DISK PAXOS ALGORITHM

As proven by [5], this problem is insolvable in an asynchronous system, even in the presence of a single failure. In order to achieve some basic consensus in such a system several solutions were proposed. One of the most useful algorithms is the Paxos algorithm, rst presented by [1]. In this algorithm, consistency is promised, but the system is not guaranteed to stop. Yet, under some stability assumptions a consensus in guaranteed. In the latter case, in order to guarantee success the Paxos algorithm may use a leader election algorithm. In modern networks the use of commodity disks as independent units has become more and more popular. Yet, some thought needs to be done in order to adapt existing algorithms to this model. This so called Disk Model was introduced by [3], where an adaptation of the classic Paxos algorithm to this model was also made. In the Disk Model, it seems rather natural that one of the complexity measures will be counting how many remote references were made by processes to the independent disks. Such a measure is known as RMR complexity (RMRC). In this paper, we will analyze the RMRC of the disk paxos, as presented in [3]. Moreover, the overall RMRC of [3] is strongly dependent on the way in which we choose to elect the leader, if in fact we choose to do so. An e cient algorithm (regarding RMRC) for that purpose was introduces by [4] in a di erent model. Our challenge will be to adapt this algorithm to the Disk Model in order to use it in the Disk Paxos algorithm. Our results considering the RMRC analysis of Disk Paxos relays on the stability of the system, which allows also to use the leader election algorithm. In the natural Disk model our results were mediocre. For that reason we tried to extend our perception of the algorithm through the use of other known models. A more successful result was achieved in the CC model. In addition, The adaptation of the algorithm in [4] to the disk model required additional assumptions on the system besides stability, such as restricted communication between processes. This may be useful for systems in which process-to-disk communication is much cheaper than process-to-process communication. This article is organized as follows Section 2 consists of article summaries. Section 3 will explain how do derive the Disk Paxos algorithm from the classic paxos algorithm. In section 4 we will analyze the RMRC of the Disk Paxos algorithm in various models. Finally, Section 5 will explain how the algorithm from [4] can be implemented in the Disk model.
Robotic Grasping of Unknown Objects

This work describes the development of a novel vision-based grasping system for unknown objects based on laser range and stereo data. The work presented here is based on 2.5D point clouds, where every object is scanned from the same view point of the laser range and camera position. We tested our grasping point detection algorithm separately on laser range and single stereo images with the goal to show that both procedures have their own advantages and that combining the point clouds reaches better results than the single modalities. The presented algorithm automatically filters, smoothes and segments a 2.5D point cloud, calculates grasping points, and finds the hand pose to grasp the desired object.