Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiple Description Based on JPEG 2000

A novel multiple description (MD) scheme based on JPEG2000 (J2K) is presented in this paper. In the scheme, the coefficients of each subband in the wavelet domain are divided into blocks, called codeblocks. These codeblocks are then partitioned into different groups. Each group is a description of the original image, and is independently encoded using the J2K technique. The decoders of the MD scheme can reconstruct the image by collecting the J2K-encoded bitstreams from any wavelet coefficients group. The algorithm is simple to implement. It attains comparable performance to that of the basic J2K not capable of realizing MD for lossless channels. Moreover, when the channels become lossy, it effectively retains the rate-distortion performance for image reconstruction. Key-Words: Image Transmission, Image Coding, Wavelet Transform.
Two-Channel Muscle Recruitment ( λ )-Control using the Evoked-EMG

This contribution is concerned with the use of the Electromyogram (EMG) evoked by Functional Electrical Stimulation (FES) as a feedback variable for controlling muscular recruitment. Feedback controlled FES has shown to be difficult in the past, mainly due to the non-linear recruitment process and fast progression of muscle fatigue. Hence, in previous works we proposed a method for controlling the muscle recruitment that compensates these effects by a fast feedback loop. (λcontrol) In this contribution, the recruitment control method is extended to two-channel operation, which has been difficult in the past because of cross talk effects between closely placed surface EMG-electrodes. Instead of following a decoupling strategy of the electrical signals, we introduce a robust timemultiplexing strategy to separate the responses of the individual muscle parts. In the proposed approach, M-wave overlapping must be avoided limiting the maximal stimulation frequency. Hence, in a study including five healthy subjects and one stroke patient the maximum was determined for each subject. A stimulation frequency of 26 Hz was possible for all subjects. Then, the proposed two-channel λ-control was successfully tested in one healthy subject showing the feasibility of the proposed concept. To show the applicability of recruitment control to clinical environments, control results for a stroke patient are additionally shown.
A Novel Approach for Sequential Rule Mining

Sequential rule mining has been applied in several domains such as stock market analysis [3], weather observation and drought management [4]. The most famous approach for sequential rule mining is that of Mannila et al. [3] and other researchers afterward that aim at discovering partially ordered sets of events appearing frequently within a time window in a sequence of events.
Security of Geographic Information System

With the development of information technology, the value and usability of Geographic Information Systems (GIS) are becoming highly crucial. GIS are more and more being applied not only to geography and information acquisition, but also to every field of society and decision making. Nowadays, people make analysis and decisions based on the GIS information, which is desirable, convenient and effective. However, the security problems of GIS are becoming increasingly prominent with the development of GIS and the enlargement of GIS users’ community. Considering the characteristics and the volumes of available GIS data, these are likely to contain various attributes regarding individual information so needing protection of sensitivity and confidentiality in GIS. In this thesis, we summarize the GIS security research status. Then, we describe the concept of context analysis that can be performed by accessing spatial objects of a GIS for decision making e.g. in public administrations or at stakeholders repositories. This idea of context analysis is the basis for making our security considerations. Moreover, we are concerned with confidentiality only, while integrity is not tackled in our assumptions. We consider that GIS data are clustered in terms of their similar context attributes and that they are inspected (read) for analysis purposes. On these premises, we propose an authorization model allowing GIS users to gain specifically-required GIS information from large volumes of information for decision making. The authorization model useful for context analysis is given in terms of GIS data structures and of operations that can be performed for context analysis, such as zooming an object, observing some of its spatial attributes, selecting a detail of the object and analyzing it. The authorization model is based on role-based access control (RBAC), in which a role and permission should be distributed before users are allowed to access a specific object. It considers also hierarchical privileges in that objects in a GIS are considered here as organized at various vertical levels and can be inspected moving along a vertical dimension: privileges to access vertical dimensions are taken into account in our model by proposing inheritance of privileges along the vertical dimension. The model at work is specified using Unified Modeling Language (UML) and by proposing a security architecture of authorization components to be included in commercial GIS products.
Analysis of Attacks Using a Honeypot

A Honeypot is a software based security device, deployed to attract hackers by displaying services and open ports which are potentially vulnerable. While the attackers are diverted, their activities can then be monitored and analysed to identify current attack methods and trends. A low-interaction Honeypot called Dionaea was chosen for this project because it can simulate services while preventing an attacker from gaining full control. Results were collected over the six week period of the experiment. The logged information of the observed attacks was analysed and compared with current vulnerabilities, the locations where the attacks were originating from and the time of day at the originating site. A profile of individual attackers can then be built to gain an insight into the current attack trends in order to improve network defences.
Expression And Characterization Of Mycobacterium Paratuberculosis 19 kda With Posttranslational Modification 2006

Despite the fact that E. coli supports limited posttranslational modification, this bacterium has been universally used as the expression system of choice. Expression of modified proteins in E. coli may lead to expression of recombinant proteins that lack essential immunomodulatory or catalytic components essentials for infectious processes. Previously in our laboratory, pMptb#28 plasmid containing a 4.8 kb insert from M. paratuberculosis has been identified which expressed 16 kDa recombinant protein in E. coli and 19 kDa recombinant protein in Mycobacterium smegmatis. The objective of this study is to identify the ORF sequence, investigate possible posttranslational modification and characterize the protein forms in the two hosts. Earlier in the study, the genome sequence for M. paratuberculosis was not available and therefore sequencing both the 5’ and 3’ ends of the 4.8 kb insert did not help in the identification of the ORF. However, unidirectional Exonuclease deletion resulted in identification of subclones containing possible ORF sequence. Later on, the publication of the M. paratuberculosis genome sequence along with BLAST analysis of sequences from the subclones resulted in the identification of 486 bp ORF with significant identity to that from M. tuberculosis and M. leprae. Cloning of the 486 ORF coding sequence in E. coli resulted in the expression of 16 kDa protein similar to the calculated predicted size of translated peptide. Cloning of the 486 bp ORF coding sequence in M. smegmatis resulted in the expression of 19 kDa protein similar to that from M. paratuberculosis. The 16/19 kDa forms of the same protein were verified using rabbit anti-M. paratuberculosis antibodies adsorbed in E. coli and M. smegmatis lysates. The size of the 19 kDa proteins was not reduced following
1 Functional and Pharmacological Analyses of the Role 2 of Penicillium digitatum Proteases on Virulence 3

Penicillium digitatum is the major postharvest pathogen of citrus fruit under Mediterranean 15 climate conditions. In the present work, we have addressed the study of the role of P. digitatum’s 16 proteases in virulence following two complementary approaches. In a first approach, we have 17 undertaken the functional characterization of the P. digitatum prtT gene, which codes for a 18 transcription factor previously shown to regulate extracellular proteases in other filamentous fungi. 19 Deletion of prtT caused a significant loss in secreted protease activity during in vitro growth assays. 20 However, there was no effect on virulence. Gene expression of the two major secreted acid proteases 21 was barely affected in the ΔprtT deletant during infection of citrus fruit. Hence, no conclusion could 22 be drawn on the role of these secreted acidic proteases on the virulence of P. digitatum. In a second 23 approach, we have studied the effect of different protease inhibitors and chelators on virulence. Co24 inoculation of citrus fruit with P. digitatum conidia and a cocktail of protease inhibitors resulted in 25 almost a complete absence of disease development. Analysis of individual inhibitors revealed that 26 the metalloprotease inhibitor 1,10-phenanthroline was responsible for the observed effect. The 27 application of metal ions reverted the protective effect caused by the metallopeptidase inhibitor. 28 These results may set the basis for the development of new alternative treatments to combat this 29 important postharvest pathogen. 30
Post-Processing NPR Effects for Video Games : a Case Study

Figure 1: Example effects. Upper row: (A) Comic-style rendering with edge detection, depth-based edge thickness and black shadows, (B) Edge detection, edge color is set by the color buffer, (C) Colored shadows. Middle row: (A) Abstraction level varying by depth in the Unity Bootcamp demo, (B) Desaturation with smooth transition, (C) Focusing on a specific depth level using color saturation in the Unity Bootcamp demo. Lower row: color stylization by example in the Unity Car Tutorial.
MultiVAC Sharding Yellowpaper The All-Dimensional Sharded Blockchain

S calability is the major bottleneck preventing blockchains from reaching industrial capacity. Systems tackling themost promising scaling solutions thus far, blockchain sharding, have produced progress in parallelizing transaction processing but have not achieved full sharding needed for total scalability. MultiVAC was completely designed to serve as a solution: the world’s first fast, efficient, and all-dimensional sharded blockchain designed for total scalability, performing sharding parallelization not only for computation but also transmission and storage. In this paper, we present an overview of MultiVAC’s sharding and storage solution. MultiVAC uses the Proof of Stake mechanism to prevent Sybil attacks and uses Verifiable Random Functions to divide the network into fragments called shards. Each shard processes transactions in parallel. MultiVAC provides an elegant distributed storage solution for the blockchain, producing a robust architecture that divides storage and transmission across shards. In this fashion, MultiVAC provides a blockchain throughput that can serve the real economy while maintaining blockchain’s core values of decentralization, equality, and security.
Heterogeneous Ensemble Classifier Model for Early Alzheimer ’ s Disease Diagnosis

Alzheimer disease (AD) is the most common form dementia that severely affects elderly population worldwide. The early diagnosis of Alzheimer disease in association with treatment still remains challenging. This research aims in exploring the power of ensemble classifier for early diagnosis of Alzheimer disease. In this context. Heterogeneous votingbased ensemble classifier was designed selecting diverse set of base classifiers such as Naïve Bayes(NB), K-nearest neighbour (KNN) and Support Vector Machine (SVM). Designed Ensemble model was evaluated on Cerebrospinal Fluid (CSF) AD biomarker datasets to investigate the potential of designed ensemble classifier against its individual base classifier. Our ensemble model exhibited better results in classifying AD in terms of accuracy, specificity and sensitivity. Thus the outcome of this study strongly suggests to apply ensemble of classifiers to enhance the classification accuracy in AD diagnosis. Keywords—Alzheimer’s disease diagnosis, Ensemble Classifier, K-Nearest Neighbour, Support Vector Machine,
Pogamut 3 – Virtual Humans Made Simple

Virtual humans, or intelligent virtual agents, born from the mould of academic, industrial, and science-fiction communities, have been surrounding us for more then a decade. Theoretical knowledge allowing many practitioners and enthusiasts to build their own agents is now available. However, the initial learning curve imposed by this specialized knowledge is quite steep. Even more fundamentally, there is a lack of freely available software assisting in the actual building of these agents. In this chapter, we introduce the Pogamut 3 toolkit. Pogamut 3 is a freeware software platform for building the behaviour of virtual humans embodied in a 3D virtual world. It is designed for two purposes; first, to help newcomers to build their first virtual agents; second, to support them as they advance in their understanding of the topic. On the one hand, Pogamut 3 allows for rapid building of simple reactive agents, and on the other hand, it facilitates development of challenging agents exploiting advanced artificial intelligence techniques. Pogamut 3 is primarily tailored to the environment of the Unreal Tournament 2004 videogame, but it can be connected to other virtual world as well. It is suitable both for research and educational projects.
Comparison of Nine level and Eleven level Inverter for Induction Motor Drives

Multi-level inverter technology has emerged recently as a very important alternative in the area of high-power mediumvoltage energy control. However, output current of the inverter as well as the time duration of the redundant switching states have been neglected. Moreover the advantages like high quality power output, low switching losses, low electro-magnetic interference (EMI) and high output voltage made multilevel inverter as a powerful solution in converter topology. In this project, the impacts of connected load to the cascaded H-bridge converter as well as the switching angles on the voltage regulation of the capacitors are studied. This study proves that voltage regulation is only attainable in a much limited operating conditions that it was originally reported. At large multilevel inverters are classified into diode clamped, flying capacitor, and cascaded H-bridge. Among those types CHBMLI offers enhanced output voltage waveform with lesser THD when increasing the levels of inverter. in addition to that the preferred output values are controlled by modulating the width of the pulses by Pulse Width Modulation(PWM) technique. The results reveal that the CHBMLI is more appropriate for induction motor drive. The proposed topology developed by using Matlab/simulink software.
Risk-Adjusted SPIVA Scorecard: Evaluation of Active Managers’ Performance Through a Risk Lens; Year-End 2017

The Risk-Adjusted SPIVA Scorecard measures the performance of actively managed funds against their benchmarks on a risk-adjusted basis, using net-of-fees and gross-of-fees returns. We use return/volatility ratios to evaluate performance. Volatility is computed by taking the standard deviation of monthly returns. Our goal is to establish whether actively managed funds are better at risk management than passive indices, using net-of-fees and gross-of-fees returns.
A Novel Machine Learning Algorithm to Analyze the Interaction on Social Networks

The use of social network for information sharing has increased in the day-to-day life. Social Networks have enormously affected the utilization example of Internet by normal man. It has cleared route for the colossal multiplication of Internet into the life of even the standard individuals. Such an exponential ascent in the utilization of the internet because of informal organizations began to get enormous volume of information crosswise over different areas in brief timeframe. In this paper we exhibit a framework which gathers messages traded from Social Networking destinations, we'll have the capacity to do investigation on those messages and in this way give some expectation of business knowledge. Consequences of pattern investigation will be shown as messages with various areas exhibiting positive, Negative and unbiased. We introduce the consequences of machine learning calculations for ordering the slant of Social Network messages utilizing different supervised learning algorithm.
Basic laws of turbulent mixing in the surface layer of the atmosphere

The article contains an analysis of the processes of mixing in a turbulent atmosphere, based on systematic application of the methods of the theory of similitude. Empirical data on the distribution of wind velocity under various conditions of temperature stratification are generalized and a method is proposed for computing the austausch characteristics on the basis of measuring wind velocity and temperature gradient.
omparison of microbial quality of irrigation water delivered in luminum and PVC pipes

Microbial quality of irrigation water attracts substantial attention due to the increased incidence of gastrointestinal illness caused by contaminated produce. Little is known about the changes in microbial quality of water during its delivery to crops. Studies were conducted to compare the biofilm formation and changes in microbial water quality in aluminum and PVC irrigation pipes. Irrigation events were conducted weekly and sections of irrigation pipe (coupons) analyzed for total protein, for total and fecal coliform bacteria, and for Escherichia coli. Coliform and E. coli concentrations along with nitrate, orthophosphate, and total organic carbon were monitored in the intake surface water, output irrigation water, and measured in residual standing water in pipes just prior to each irrigation event. Proteins accumulated to a greater extent in aluminum-associated biofilms than in plastic-associated biofilms. Numbers of total coliforms associated with aluminum coupons increased with time while numbers of total coliforms associated with plastic coupons fluctuated. Nitrates disappeared in standing water after one week in aluminum pipes and remained present in plastic. No detectable E. coli remained in standing water in both types of pipe. There was a high probability that coliform concentrations in output irrigation water were different from the intake concentrations in plastic pipes but not in aluminum pipes. Further research is required to evaluate how pipe material may affect the potential of biofilms in irrigation distribution systems to serve as reservoirs of pathogens that can be disseminated to crops during irrigation.
Modern Hardware Margins: CPUs, GPUs, FPGAs Recent System-Level Studies

Modern large-scale computing systems (data centers, supercomputers, cloud and edge setups and high-end cyber-physical systems) employ heterogeneous architectures that consist of multicore CPUs, general-purpose many-core GPUs, and programmable FPGAs. The effective utilization of these architectures poses several challenges, among which a primary one is power consumption. Voltage reduction is one of the most efficient methods to reduce power consumption of a chip. With the galloping adoption of hardware accelerators (i.e., GPUs and FPGAs) in large datacenters and other large-scale computing infrastructures, a comprehensive evaluation of the safe voltage reduction levels for each different chip can be employed for efficient reduction of the total power. We present a survey of recent studies in voltage margins reduction at the system level for modern CPUs, GPUs and FPGAs. The pessimistic voltage guardbands inserted by the silicon vendors can be exploited in all devices for significant power savings. Voltage reduction can reach 12% in multicore CPUs, 20% in manycore GPUs and 39% in FPGAs.
Partially Observable Stochastic Reference Games

We present a model of the production and interpretation of referring expressions as a partially observable stochastic game (POSG), a multi-agent probabilistic decision-making model. Agents acting in POSGs maintain a model of the interlocutor’s beliefs and intentions, capturing several pragmatic effects on the semantics of referring expressions: audience design, conversational grounding, and underspecification.We present the theory of POSGs and discuss algorithms for tracking the beliefs of interlocutors, decision making, and learning.
Eco-services Evaluation Model (EEM): a decision-support tool for sustainable new urban development

This paper is motivated by environmental degradation which happens in China due to the intensive new urban development. Although more planning and design proposals are titled with “sustainable”, few have yet, it appears succeeded. “Design for Eco-services” is an emerging theory about sustainable urban development, in which Janis Birkeland argues that, “net positive development” can be achieved through the antidote from vicious circles to virtuous cycles by designing development to provide eco-services initially. Despite the theoretical soundness of such claims, the local and international literature shows limited understanding of how to provide eco-services through the planning and design practices of actual physical forms. Accordingly, the aim of this paper is to explore a tool, supporting the decision-making of appropriate physical forms in new urban development, which can provide eco-services. Since the existing evaluation models are not suitable for urban eco-services, which are studied as per the situations of non-urban areas, a new tool, Eco-services Evaluation Model (EEM), is proposed, involving Material Flow Analysis (MFA) for abiotic eco-services, Patch-CorridorMatrix analysis (PCM) for biotic eco-services, and Ecological Footprint Analysis (EF) for overall performance and preventing “rebound effect”. It can cover the evaluation of individual key eco-service and the entire performance of all of those. Conference theme: Urban / Regional
Search : Combining Language Modeling and Link Analysis

As a result of its recent rapid development, Wikipedia is likely the largest resource of organized content, manually edited through a collaborative effort by millions of “wikipedians”. The complex structure of Wikipedia with many features that normal corpora do not have, such as semantically rich inter-document links, allows for successful application of new approaches to information retrieval. The contribution of this paper is twofold. First we analyze Wikipedia’s usefulness as a research corpus for modern IR techniques. The second contribution is that we present a novel Wikipedia retrieval method which combines link analysis and language modeling with different weights for better ranking of the result set. The experimental results demonstrate statistically significant improvements in both precision (5%) and recall (8%) when compared to language modeling or link analysis based techniques separately.