Miracle-dz/UniFAR-FTUs huggingface dataset:
LEAN MANUFACTURING BEST PRACTICES IN SMES

Last two decades had witnessed explosion of researches into the area of manufacturing improvement such as lean manufacturing, total quality management, total productive maintenance and their application within various manufacturing companies such as automotives, electronics, plastics components and etc.It was proven that lean manufacturing was considered as the best manufacturing system in the 21st century.A comprehensive literature review was conducted to get necessary lean information.The review is focused on SME definitions and characteristics.This is followed by reviewing the lean practices and discusses them based on SMEs’ capabilities. The aim of this paper is to present feasible lean practices for lean implementation in SMEs.There are seventeen lean practices which could be considered are feasible and relevant to the SME characteristics.The proposed practices were based on three categories; least investment, feasible to apply in SME and recommended by researchers
INTELLIGENT ROBOTS: THE QUESTION OF EMBODIMENT

Embodiment has been perceived by some as one of the fundamental issues in the pursuit of artificial intelligence, a perspective that has only been mainstream in recent years. This paper discusses embodiment, its interpretations, misinterpretations and the role it has played in artificial intelligence to date and specifically in the realisation of the “ intelligent robot” . While some believe that simply placing a controller in a physical environment constitutes a sufficient degree of embodiment, we wish to emphasise that agent-world interaction must develop away from this “ ONWorld” approach and seek to concentrate on “ IN-World” interaction, participation, and adaptation.
Intrusion detection in wireless networks using Genetic Algorithm

It is very important to maintain a high level security to ensure safe and trusted communication of information between various organizations. As the growth of computer networks is increasing day by day in modern society, therefore network security is one of the hottest issue to be solved. This paper proposes application of Genetic Algorithm (GA) for network intrusion detection system. Any action that tries to compromise the confidentially, integrity or availability of resources is termed as intrusion and the detection of such intrusion by the help of a system is called as intrusion detection system (IDS). The proposed GA is a hybrid evolutionary technique specially developed for intrusion detection. The technique developed has been implemented and the experiments have shown the promising results. The evolutionary process of this technique including its parameters and the experimental outcomes are discussed at length in this paper. In this paper we have made the comparison of our technique with the GNN classifier technique and the outcomes from our experiment have given promising results towards applying genetic algorithm for network intrusion detection.
A texton for fast and flexible Gaussian texture synthesis

Gaussian textures can be easily simulated by convolving an image sample with a white noise. However, this procedure is not very flexible (it does not allow for non-uniform grids in particular), and becomes computationally heavy for very large domains. We here propose an algorithm that summarizes a texture sample into a synthesis-oriented texton, that is, a small image for which the discrete spot noise simulation (summed and normalized randomly-shifted copies of the texton) is more efficient than the classical convolution algorithm. Using this synthesis-oriented texture summary, Gaussian textures can be generated on-demand in a faster, simpler, and more flexible way.
Robust time-varying fading channel estimation with risk sensitive filter under parameter and process noise uncertainty

An alternative to Kalman filtering, a risk-sensitive filtering is utilized for a linear time-varying fading channel estimation problem and its robustness against uncertainty parameter is explored. The time-varying channel estimation problem is formulated as time varying Finite Impulse Response (FIR) filter with known rectangular pulse at input and Gaussian noise corrupted signal at output. In time-varying FIR filter, estimation of time varying coefficients with uncertain conditions is an important and crucial task In literature, Kalman filter based fading channel estimation approach has been studied and it has limitations that leads to inaccurate estimation when there is high level of uncertainty in initial conditions and bias in system models and/or noise covariance. To overcome the above limitation, the risk sensitive filter is proposed. In this work only bias model is considered to investigate the effect of risk cost performance. The special feature of risk sensitive filter is, it uses a risk factor/parameter in the exponential cost function. So that the probability density function of variable is reshaped with proper tuning of risk factor, thus robustness again uncertainty can be achieved. In channel estimation with the uncertain conditions, the improved performance of risk sensitive filter over the conventional Kalman filter is shown with numerical simulation results.
Heteroepitaxial Growth of Planar Semipolar ( 10 1̄ 1 ) GaN by Metalorganic Vapor Phase Epitaxy

We report on the growth of planar semipolar (101̄1) GaN on (112̄3) pre-patterned sapphire. This method allows the growth of semipolar oriented (101̄1) GaN on large scale. By x-ray diffaction, only the peaks of the desired (101̄1) plane could be observed. The in-plane orientations could be determined as [0001]GaN ‖ [0001]sapphire and [112̄0]GaN ‖ [101̄0]sapphire. Scanning electron microscopy, transmission electron microscopy and atomic force microscopy measurements show coalesced surfaces with root mean square roughness values below 2 nm (10μm×10μm). Further investigations using photoluminescence spectroscopy show spectra that are dominated by the near band edge emission. The high crystal quality is confirmed by small full width at half maximum values of x-ray rocking curve measurements of less than 400 arcsec.
In vitro and in vivo efficacy of a hydrated sodium calcium aluminosilicate to bind and reduce aflatoxin residues in tissues of broiler chicks fed aflatoxin B 1

The aim of this study was to determine the binding capacity of a hydrated sodium calcium aluminosilicate (HSCAS) for aflatoxin B1 (AFB1), and the efficacy of the HSCAS to reduce the concentrations of residual AFB1 and its metabolites in the liver and kidney of broilers fed AFB1. One hundred 1-d-old male broilers (Ross 708) were maintained in chick batteries and allowed ad libitum access to feed and water. A completely randomized design was used with 5 replicate pens of 5 chicks assigned to each of 4 dietary treatments from hatch to 21 d. Dietary treatments included the following: A) basal diet (BD), with no HSCAS or AFB1, B) BD supplemented with 0.5% HSCAS only, C) BD supplemented with 2.5 mg of AFB1/kg of feed, and D) BD supplemented with 2.5 mg of AFB1/ kg of feed and 0.5% HSCAS. On d 21, 5 chicks from each treatment were anesthetized with carbon dioxide, killed by cervical dislocation, and samples of liver and kidney were collected for analysis of AFB1 residues. The percentage of AFB1 bound for each concentration of adsorbent (100, 10, 1, 0.5, 0.25, and 0.05 mg/10 mL) was 100, 91.1, 81.8, 75.4, 40.1, and 8.8%, respectively. Concentrations of aflatoxin residues (AFB1, aflatoxicol, aflatoxins B2 and G1) were lower (P < 0.05) in livers and kidneys of birds fed AFB1 plus HSCAS (diet D), when compared with birds fed AFB1 alone (diet C). However, histopathology data from the in vivo study indicated that HSCAS did not prevent lesions associated with aflatoxicosis. The decrease in the bioavailability of AFB1 caused by the HSCAS reduced aflatoxin residues in liver and kidney, but not enough to completely prevent the toxic effects of AFB1 in broilers.
The Linguistic Relevance of Tree Adjoining Grammar

5 The Passive in a TAG 49 5.1 The link between raising and the passive . 49 5.2 A TAG analysis of the passive . 52 5.3 Impersonal and raising passives . 55 ∗This work was supported in part by NSF grants MCS8219196-CER, MCS8207294 and a grant from the Alfred P. Sloan Foundation for a Program in Cognitive Science, Grant No. 84-4-15.
Survey of Linked Data Based Exploration Systems

Linked datasets now constitute a valuable background knowledge for supporting exploration and discovery objectives through browsers, recommenders and exploratory search systems in particular. Today there is a need to look at the achievements and tendencies in this rapidly developing field in order to better orient the future research works. In this paper we propose a survey of such systems from the earliest semantic browsers to more recent and innovative ones.
Learning Scale-Free Networks by Dynamic Node Specific Degree Prior

Learning the network structure underlying data is an important problem in machine learning. This paper introduces a novel prior to study the inference of scale-free networks, which are widely used to model social and biological networks. The prior not only favors a desirable global node degree distribution, but also takes into consideration the relative strength of all the possible edges adjacent to the same node and the estimated degree of each individual node. To fulfill this, ranking is incorporated into the prior, which makes the problem challenging to solve. We employ an ADMM (alternating direction method of multipliers) framework to solve the Gaussian Graphical model regularized by this prior. Our experiments on both synthetic and real data show that our prior not only yields a scale-free network, but also produces many more correctly predicted edges than the others such as the scale-free inducing prior, the hub-inducing prior and the $l_1$ norm.
Improving Usability of Web Pages for Blinds

Warranting the access to Web contents to any citizen, even to people with physical disabilities, is a major concern of many government organizations. Although guidelines for Web developers have been proposed by international organisations (such as the W3C) to make Web site contents accessible, the wider part of today's Web sites are not completely usable by peoples with sight disabilities. In this paper, two different approaches for dynamically transforming Web pages into aural Web pages, i.e. pages that are optimised for blind peoples, will be presented. The approaches exploit heuristic techniques for summarising Web pages contents and providing them to blind users in order to improve the usability of Web sites. The techniques have been validated in an experiment where usability metrics have been used to assess the effectiveness of the Web page transformation techniques.
Collaborative Filtering for Book Recommandation

In this paper, we present our contribution in INEX 2014 Social Book Search Track. This track aims to exploit social information (users reviews, ratings, etc.) from LibraryThing and Amazon collections. In our experiments we used di erent methods, one of our submissions which uses INL2 got the second rank w.r. t nDCG@10 measure, the o cial measure for this task. In addition, we tested the combination of the Sequential Dependence Model (SDM) and the use of social information that takes into account ratings,tags and customer reviews, we also tested several query expansion techniques: concept expansion, tag expansion and pseudo relevance feedback.
Combined action observation and motor imagery therapy: a novel method for post-stroke motor rehabilitation

Cerebral vascular accidents (strokes) are a leading cause of motor deficiency in millions of people worldwide. While a complex range of biological systems is affected following a stroke, in this paper we focus primarily on impairments of the motor system and the recovery of motor skills. We briefly review research that has assessed two types of mental practice, which are currently recommended in stroke rehabilitation. Namely, action observation (AO) therapy and motor imagery (MI) training. We highlight the strengths and limitations in both techniques, before making the case for combined action observation and motor imagery (AO + MI) therapy as a potentially more effective method. This is based on a growing body of multimodal brain imaging research showing advantages for combined AO + MI instructions over the two separate methods of AO and MI. Finally, we offer a series of suggestions and considerations for how combined AO + MI therapy could be employed in neurorehabilitation.
Partitioning schemes for quicksort and quickselect

We introduce several modifications of the partitioning schemes used in Hoare’s quicksort and quickselect algorithms, including ternary schemes which identify keys less or greater than the pivot. We give estimates for the numbers of swaps made by each scheme. Our computational experiments indicate that ternary schemes allow quickselect to identify all keys equal to the selected key at little additional cost.
Mobile Platform Self-localization in Partially Unknown Dynamic Environments

Localization methods for mobile platforms are commonly based on an observation model that matches onboard sensors measures and environmental a priori knowledge. However, their effectiveness relies on the reliability of the observation model, which is usually very sensitive to the presence of unmodelled elements in the environment. Mismatches between the navigation map, itself an imperfect representation of the environment, and actual robot’s observations introduce errors that can seriously affect positioning. This article proposes a 2D point-based model for range measurements that works with a new method for 2D point matching and registration. The extended Kalman filter is used in the localization process since it is of the most efficient tool for tracking a robotic platform’s configuration in real time. The method minimizes the impact of measurement noise, mismodelling and skidding on the matching procedure and allows the extended Kalman filter observation model to be robust against skidding and unmodelled obstacles. Its O(n ·m) complexity enables real-time optimal points matching. Simulation and experiments demonstrate the effectiveness and robustness of the proposed algorithm in dynamic and partially unknown environments.
Genome Sequence of Schizochytrium sp. CCTCC M209059, an Effective Producer of Docosahexaenoic Acid-Rich Lipids

ABSTRACT Schizochytrium is an effective species for producing omega-3 docosahexaenoic acid (DHA). Here, we report a genome sequence of Schizochytrium sp. CCTCC M209059, which has a genome size of 39.09 Mb. It will provide the genomic basis for further insights into the metabolic and regulatory mechanisms underlying the DHA formation.
Oxazin-5-Ones as a Novel Class of Penicillin Binding Protein Inhibitors: Design, Synthesis and Structure Activity Relationship

Penicillin binding proteins (PBPs) are normal constituents of bacterial which are absent in mammalian cells. The theoretical binding modes of known oxazin-5-ones toward the protein were used as a guide to synthesis new inhibitors. Structural studies of protein-ligand complexes revealed that conformational discrepancies of the derivatives in the protein’s binding site gave rise to the variation in their inhibition constant which ranged from 68.58 μM to 2.04 mM. Biological assay results further confirmed the antibiotic potencies of the studied compounds. Although the outcome of biological screening does not parallel computational predictions, the results obtained from both methods suggest that the oxazin-5-one derivatives are potential PBP inhibitors, hence interesting antibiotic lead agents.
“Journey, Rest, Gate and Garment”: A Cross-cultural Cognitive Analysis of Metaphors Used in Breaking News of Death

How is death conceptualized in Hausa and Yoruba languages? Are there any linguistic similarities or differences in the ways they break news of death? This paper notes that language is not carelessly used to establish interactional and transactional functions among interactants; rather it is creatively used depending on the context of usage. One such context of usage that involves more caution and wisdom is breaking news of death to the deceased loved ones. This particular context is mostly achieved through the use of some metaphors and idiomatic expressions to present, euphemistically, unpleasant news about the death of a person. There is no contrastive research effort, at present, which has examined conceptualization of death in Hausa and Yoruba languages for possible similarities and differences. In this paper, therefore, an attempt was made to conceptualize death as a domain through the cognitive, cultural and religious windows that are available in these native Nigerian languages. In the course of the investigation, the paper argues Original Research Article Asiru and Batagarawa; ARJASS, 8(1): 1-10, 2019; Article no.ARJASS. 43413 2 that even though metaphors are ubiquitous in every community and are presented in different ways in breaking news of the departed friends and enemies, there abound areas of metaphoric convergence and divergence in the description of death. The convergent and divergent points are results of the universality in the conceptualization of aspects of human body/experience such as death. In particular, we argued, that the similarities in the identified four source domains (journey, rest, garment and gate) and their differences are conditioned by cultural or religious constructs and contacts, and the linguistic variance between the two languages. Finally, the paper lends credence to the claim that primary metaphors are shared by all human languages.
Practical Aspects of Theoretical Bounds for Algebraic Multigrid Performance

Algebraic multigrid methods continue to grow in robustness as effective solvers for the large and sparse linear systems of equations that arise in many applications. Unlike geometric multigrid approaches, however, the theoretical analysis of algebraic multigrid is less predictive of true performance. Multigrid convergence factors naturally depend on the properties of the relaxation, interpolation, and coarse-grid correction routines used; yet, without the tools of Fourier analysis, optimal and practical bounds on algebraic multigrid are not easily quantified. In this paper, we survey bounds from existing literature, with particular focus on the predictive capabilities of the theory, and provide new results relating existing bounds. We highlight the impact of these theoretical observations through several model problems and discuss the role of theoretical bounds on practical performance. Copyright c © 2013 John Wiley & Sons, Ltd.
Object Recognition with Many Local Features

There has been a great deal of attention focused on part-based approaches to object classification in recent research in computer vision, and some approaches have achieved a surprising amount of success. However, learning models with a large number of parts has been a particular challenge. One of the most successful approaches is that of Fergus et al. [5] who have developed a generative model for recognition that achieves excellent results on a variety of datasets. The learning method that they present to learn the parameters for the model, however, requires an exponential amount of time to train as the number of parts increase. The primary contribution of this thesis is the extension of their generative model, and the development of a learning algorithm that can learn a large number of parts in a reasonable amount of time. In particular, we have developed an incremental learning algorithm where the model is initialized intelligently with a small number of parts, and parts are added to the model one at a time. By taking such an approach we are able to learn models with a large number of parts in nearly a linear amount of time in the number of parts. The approach is validated on a number of datasets, including cars, motorbikes, and faces, and demonstrates excellent recognition results along with large models learned in a reasonable amount of time.
A VERSATILE INSTRUMENT FOR ANALYZING AND TESTING THE INTERFACES OF PERIPHERAL DEVICES

This work presents a flexible development and testing environment, created for evaluating the performance and analyzing the characteristics of interfaces used by pe- ripheral devices. The versatility of the presented instrument is due to the integration of the Matlab/Simulink tools with a custom reconfigurable hardware platform using the PCMCIA bus of conventional laptop computers. The hardware platform uses reconfigurable circuits, acts as a host adapter of the peripheral device and transforms the test sequences of the high level software tool into interface specific bit-streams, while it simultaneously collects interface-related data for further processing.
Parametrical Non-Complex Tests to Evaluate Partial Decentralized Linear-Output Feedback Control Stabilization Conditions from Their Centralized Stabilization Counterparts

This paper formulates sufficiency-type linear-output feedback decentralized closed-loop stabilization conditions if the continuous-time linear dynamic system can be stabilized under linear output-feedback centralized stabilization. The provided tests are simple to evaluate, while they are based on the quantification of the sufficiently smallness of the parametrical error norms between the control, output, interconnection and open-loop system dynamics matrices and the corresponding control gains in the decentralized case related to the centralized counterpart. The tolerance amounts of the various parametrical matrix errors are described by the maximum allowed tolerance upper-bound of a small positive real parameter that upper-bounds the various parametrical error norms. Such a tolerance is quantified by considering the first or second powers of such a small parameter. The results are seen to be directly extendable to quantify the allowed parametrical errors that guarantee the closed-loop linear output-feedback stabilization of a current system related to its nominal counterpart. Furthermore, several simulated examples are also discussed.