Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey on: Stratified mapping of Microarray Gene Expression datasets to decision tree algorithm aided through Evolutionary Design

Analyzing gene expression data is a challenging task since the large number of features against the shortage of available examples can be prone to over fitting. In order to avoid this pitfall and achieve high performance, some approaches construct complex classifiers, using new or well-established strategies. In medical decision making (classification, diagnosing) there are many situations where decision must be made effectively and reliably. Decision tree induction is one of the most employed methods to extract knowledge from data, since the representation of knowledge is very intuitive and easily understandable by humans. Conceptual simple decision making models with the possibility of automatic learning are the most appropriate for performing such tasks. Decision trees are a reliable and effective decision making technique that provide high classification accuracy with a simple representation of gathered knowledge and they have been used in different areas of medical decision making. Following recent breakthroughs in the automatic design of machine learning algorithms, a novel approach of hyper-heuristic evolutionary algorithm called HEAD-DT that evolves design components of top-down decision tree induction algorithms can be used to improve the classification accuracy.
A Framework for Video Event Detection Using Weighted SVM Classifiers

Automatic semantic annotation of video events has received a large attention from the scientific community in the latest years. Events can be defined by spatio-temporal relations and properties of objects and entities, which change over time; some events can be described by a set of patterns. Despite this application of dynamic graphical modeling, the performance for event modeling and detection continues to be a challenge in scenarios where a very large number of training samples are not available. It is in situations like these that the need for event models that are built using discriminate classifiers is acute and the need for well designed features that can capture motion information of video shots into a small number of feature dimensions is required. In this paper, we present a framework for semantic video event annotation that exploits global feature, local feature and motion feature. Using these features, video clip can be encoded as a set of feature vectors. Then according to different features, we train SVM classifiers, and a bi-coded chromosome based genetic algorithm is performed to obtain optimal classifiers and relevant optimal weights based on training stage. With the optimal classifiers set and optimal weights, the maximum similarity between video clip in original database and unlabeled video clip is considered to be the final label result.
Designing aural information architectures

Nowadays websites use, above all, the "visual channel" to communicate content, functionality and navigation/interaction capabilities. Users who, permanently or temporarily, cannot use their eyes to interact with an application (not only visuallyimpaired but also people who cannot look at the screen while interacting) need a new paradigm of interaction, based on an "aural" access to information. Current technological approaches for developing "aural hypertexts" (such as speech markup languages, or code optimization techniques for screen-readers) provide technical solutions to transform a visual interaction into an aural one, failing to support adequately the overall design process. This paper presents an overview of critical design issues to consider when conceiving aural hypertexts, namely when designing "aural" information architecture, navigation and interaction features. Examples of possible "aural" design solutions are also discussed to support specific requirements. The work is based upon real-life project experience in both designing web applications and developing applications for visually-impaired users
Growth with Endogenous Direction of Technical Change

By extending the range of admissible factor accumulation and innovation investment elasticities, this paper expands the Acemoglu (2003) model and obtains several results. First, it identifies conditions for the existence of a steady-state equilibrium and shows that Uzawa’s theorem is obtained as a special case of these conditions. Second, it demonstrates that along a steady-state equilibrium path, technological progress can include both labor-augmenting and capital-augmenting elements. Third, it shows that the direction of technological progress is determined by the relative size of price elasticities of material factors, and is biased towards the factor with the relatively smaller price elasticity. Finally, the paper finds that technical change has two effects on factor income shares. On one hand, factor shares change when the direction of technical progress changes. On the other hand, when the direction of technical change remains unchanged, in general the speed of technical progress also affects factor shares, unless technical progress is Hicks neutral.
Mixed H2/H∞ control for time‐varying and linear parametrically‐varying systems

This paper provides a solution of the mixed H 2 =H 1 problem with reduced order controller for time-varying systems in terms of solvability of diierential linear matrix inequalities and rank conditions, including a detailed discussion of how to construct a controller. Immediate specialization lead to a solution of the full order problem and the mixed H 2 =H 1 problem for linear systems whose description depend on an unknown but in real-time measurable time-varying parameter. As known for the H 1 problem, we completely resolve the quadratic mixed H 2 =H 1 problem (under certain hypotheses on the parameter dependence) by reducing it to the solution of nitely many algebraic linear matrix inequalities. However, we also point out directions how to overcome the conservatism introduced by using constant solutions of the diierential inequalities. Finally, we clarify that a simple specialization leads to a linear matrix inequality approach to the pure H 2 problem for general LTI systems, and we reveal how to compute the optimal value. 1 Notation R n is equipped with the Euclidean norm, and R nm with the corresponding induced norm, both denoted as k:k. L p denotes the signal space L n p 0; 1) (for an appropriate n) and is equipped with the standard norm k:k p (deened with the Euclidean spatial norm). Functions are tacitly assumed to be continuous and bounded, and smooth functions are, in addition, continuously diierentiable. Time functions are functions deened on 0; 1). For a symmetric valued function X(s) deened on a set S, X is said to be strictly positive (X 0) if there exists an > 0 such that X(s) I for all s 2 S. For the system or input output mapping _ x = Ax + Bu; y = Cx + Du with x(0) = 0 we use the notation " A B C D #. If A B C D ! is a constant matrix, the system is called LTI, if it is a time function, the system is called LTV. The time function A is exponentially stable if the system _ x = Ax has this property.
Wall-through radar modeling by applying array-factor and GTD near-field

We propose modeling method for the wall through radar by using near-field GTD as a near-region target model and delayed path-length for multi-layered dielectric sheets. Radar image can be constructed by AF (array-factor), which is a kind of synthetic aperture imaging. For near-region target, we apply focusing procedure of optical ray to the AF summation and the wall through pass. Refraction coefficient of N-layered dielectric sheets is exactly derived as boundary wave problem and applied to the wall through radar imaging. Theoretical near-field AF images are compared with far-field model, traditional SAR (synthetic aperture radar) image, and measured data.
Solid-state time-of-flight range camera

The concept of a real-time range camera without moving parts is described, based on the time-of-flight (TOF) principle. It operates with modulated visible and near-infrared radiation, which is detected and demodulated simultaneously by a 2-D array of lock-in pixels employing the charge-coupled device principle. Each pixel individually measures the amplitude, offset and phase of the received radiation. The theoretical resolution limit of this TOF range camera is derived, which depends on the square root of the detected background radiation and the inverse of the modulation amplitude. Actual measurements of 3-D sequences acquired at 10 range images per second show excellent agreement between our theory and the observed results. A range resolution of a few centimeters over a range of 10 m, with an illumination power of a few hundreds of milliwatts is obtained in laboratory scenes for noncooperative, diffusely reflecting objects.
The Integration of Color and the Retention of Text

The following essay will present research that studies the interweaving of color and memory. The purpose of this research is to evaluate the effectiveness of different formats of color within a prose fiction text, and to show how color affects the retention of the information read. To perform the study, one passage made in three different formats – black and white throughout the text, colored font on random words, or highlighted text on random words – will be randomly assigned to Advanced Placement (AP) and College Prep (Regular) English class juniors, followed by a test based on accuracy. The results show that color has a more positive influence than normal black and white text in regards to retaining information. Moreover, women overall were seen to perform significantly better on the text with highlighted text compared to colored font, whereas men overall were seen to be more successful using colored font than highlight. One can conclude from this research that using color to study and remember information for a test or a job-related interview can improve one’s performance. Due to the positive influence of color, students should ask their teachers to promote a more color-coded study plan, present key parts in a slideshow using highlighting or colored font, or more, which could lead to higher student scores and steer attention towards the information being given.
Developing Mammalian Retina Spontaneous Waves in the Ventricular Zone of

[PDF] [Full Text] [Abstract] , August 22, 2007; 27 (34): 9130-9140. J. Neurosci. Fikhman, Shigetada Nakanishi and Marla B. Feller Chih-Tien Wang, Aaron G. Blankenship, Anastasia Anishchenko, Justin Elstrott, Michael Developing Retina Receptor-Mediated Signaling Alters the Structure of Spontaneous Activity in the A GABA [PDF] [Full Text] [Abstract] , January 2, 2008; 28 (1): 249-257. J. Neurosci. Agnieszka Grabska-Barwinska and Christoph von der Malsburg Mammals Establishment of a Scaffold for Orientation Maps in Primary Visual Cortex of Higher [PDF] [Full Text] [Abstract] , August , 2009; 24 (4): 219-230. Physiology Jeremy E. Cook and David L. Becker Gap-Junction Proteins in Retinal Development: New Roles for the ''Nexus'' [PDF] [Full Text] [Abstract] , December 2, 2009; 29 (48): 15232-15244. J. Neurosci. Sheng Wang, Luis Polo-Parada and Lynn T. Landmesser Sources and Effects of Altered Activation of Transmitter Receptors 2+ Ca Transients in Early Embryonic Chick Motoneurons: 2+ Characterization of Rhythmic Ca [PDF] [Full Text] [Abstract] , January 18, 2012; 32 (3): 850-863. J. Neurosci. Kevin J. Ford, Aude L. Félix and Marla B. Feller Cellular Mechanisms Underlying Spatiotemporal Features of Cholinergic Retinal Waves
Challenging Weak Central Coherence: A Brief Exploration of Neurological Evidence from Visual Processing and Linguistic Studies in Autism Spectrum Disorder

Previous theories have attempted to locate the root cause of Autism Spectrum Disorder (ASD) in terms of a typical central cognitive processes. However, the field of neuroscience is increasingly finding structural and functional differences between autistic and neuro-typical individuals using neuro-imaging technology which either support or challenge earlier cognitive theories. One main area upon which this research has focused is in visuospatial processing, with specific attention to the notion of “weak central coherence” (WCC), which refers to the tendency of individuals with ASD to be unable to interpret “global” information while hyper-focusing on local information. The current paper offers a brief review of findings from selected studies in order to explore available research that challenges the “deficit” characterization of a WCC theory as opposed to a “superiority” characterization of a strong local coherence.
A COMPARATIVE STUDY OF LITERARY TRANSLATION FROM ARABIC INTO ENGLISH AND FRENCH

ii ACKNOWLEDGEMENTS It would be impossible for me to complete this work without the sponsorship, edifying supervision, and moral support, which I have been given during my study. I would like to appreciate deeply the Institute of Postgraduate Studies (IPS) of Universiti Sains Malaysia (USM) for the graduate assistance scheme which has supported me financially and has permitted me to have more teaching experience in the university. I have really enjoyed it. I would like to express my heartfelt gratitude and appreciation to my supervisor Dr. Tengku Sepora Binti Tengku Mahadi. You have given your time and attention to my study. You have edified me intellectually, and morally. I have learnt a lot from you. I am profoundly grateful for all the efforts you have done for me to complete my studies. Well-done and thank you very much! Special thanks go to Mrs. Tengku Hamida Tengku Mahadi, and Mr. Tengku Yahaya Tengku Mahadi for their moral support and encouragement. Thanks go also to the staff of the Department of Languages and translation of the Universiti Sains Malaysia for their amity, friendship, dealing, and interaction, which I have enjoyed for the period of my study. I'm grateful to my uncle Youssouf Ibrahim, and my aunt Maria Ibrahim for their moral support and encouragement. I ask forgiveness from my children, Camelia Mohamed Abdou and Housni Mohamed Abdou for living away from them for so long. I have lived away from you in your early ages for the quest for knowledge for the juvenile generation of which you are members. Do understand that I think of you too much. I pray to my late parents, Mbahoua Ibrahim and Abdou Moindjie. May God rest their souls. Finally, I thank God for giving me health and chances in my life. I pray Allah to bless and reward best the above-mentioned persons, and to bless me to contribute the knowledge I have learnt to mankind in general and to my country, Comoros in particular. Amen!
Text Classification Using Word-Based PPM Models

Text classification is one of the most actual among the natural language processing problems. In this paper the application of word-based PPM (Prediction by Partial Matching) model for automatic content-based text classification is described. Our main idea is that words and especially word combinations are more relevant features for many text classification tasks. Key-words for a document in most cases are not just single words but combination of two or three words. The main result of the implemented experiments proved applicability of word-based PPM models for content-based text classification. Although in some cases the entropy dierence which influenced the choice was rather small (several hundredths), most of the documents (up to 97%) were classified correctly.
Sharing RapidMiner Workflows and Experiments with OpenML

OpenML is an online, collaborative environment for machine learning where researchers and practitioners can share datasets, workflows and experiments. While it is integrated in several machine learning environments, it was not yet integrated into environments that offer a graphical interface to easily build and experiment with many data analysis workflows. In this work we introduce an integration into the popular RapidMiner environment, that will allow RapidMiner users to import data directly from OpenML and automatically share all their workflows and experiments. OpenML will then link these results to all other results obtained by other people, possibly with other tools, creating a single connected overview of the best workflows on a large set of machine learning problems. This is useful to learn and build on the results of others, to collaborate with many people online, and it provides a wealth of information to study how to construct workflows for new machine learning problems. We demonstrate the capabilities of this integration and identify several research opportunities.
Enhancing utility via clustering in privacy preservation

When sensitive information needs to be released involved privacy preservation, which has attracted a widely range of research interests. K-anonymity is one of the most important anonymity models that have been Extensively research and many thinking have been presented to improve it. A way to make data anonymous is generalization. Cluster is a collection of data objects, which are similar to the objects in the same cluster, and different from the objects in other clusters. Both of these two methods have the same characteristics: assign the tuples to many small groups. Based on the above problems, we propose a clustering-based k-anonymity algorithm, which achieves k-anonymity through clustering.
Genetic diversity and population structure among six cattle breeds in South Africa using a whole genome SNP panel

Information about genetic diversity and population structure among cattle breeds is essential for genetic improvement, understanding of environmental adaptation as well as utilization and conservation of cattle breeds. This study investigated genetic diversity and the population structure among six cattle breeds in South African (SA) including Afrikaner (n = 44), Nguni (n = 54), Drakensberger (n = 47), Bonsmara (n = 44), Angus (n = 31), and Holstein (n = 29). Genetic diversity within cattle breeds was analyzed using three measures of genetic diversity namely allelic richness (AR), expected heterozygosity (He) and inbreeding coefficient (f). Genetic distances between breed pairs were evaluated using Nei's genetic distance. Population structure was assessed using model-based clustering (ADMIXTURE). Results of this study revealed that the allelic richness ranged from 1.88 (Afrikaner) to 1.73 (Nguni). Afrikaner cattle had the lowest level of genetic diversity (He = 0.24) and the Drakensberger cattle (He = 0.30) had the highest level of genetic variation among indigenous and locally-developed cattle breeds. The level of inbreeding was lower across the studied cattle breeds. As expected the average genetic distance was the greatest between indigenous cattle breeds and Bos taurus cattle breeds but the lowest among indigenous and locally-developed breeds. Model-based clustering revealed some level of admixture among indigenous and locally-developed breeds and supported the clustering of the breeds according to their history of origin. The results of this study provided useful insight regarding genetic structure of SA cattle breeds.
Probabilistic Document Modelling

In this thesis the development and application of probabilistic models of documents is considered. The initial focus is on language models which provide a way of modelling plain text documents. In particular the hierarchical Dirichlet language model, which is derived from simple Bayesian theory, is investigated and is shown to be well approximated by an existing method known as generalised PPM-A. Using this equivalence, generalised PPM-A is extended to produce a language model which while working on the level of individual letter-like symbols is able to make use of the division of the text stream into words. It is shown that the new model can be used in conjunction with a word list to improve performance when very little information from which to learn the statistics of the language is available. The hierarchical Dirichlet model is then applied to the task of information retrieval, producing a new retrieval method which naturally includes document frequency information. This information has traditionally been used in retrieval systems, but previously had either been missing or introduced heuristically in language model based approaches to the problem. The hierarchical approach is also extended to the task of retrieval at the passage level where it is shown to give promising results. Finally, the scope of the investigation is broadened to include documents which contain diagrams as well as plain text. A method is developed to group fragments of digitised ink strokes into perceptually relevant components of a diagram, while at the same time labelling the components with an object class. The approach, which is based on the conditional random field, is shown to work well both in terms of grouping and improving labelling performance when compared to other methods.
Object Transport and Reference Management in the Mobjex Framework

With increasing numbers of more capable mobile devices, and the pervasiveness of more powerful desktop machines, improvements in the design of client server systems may be possible. In a next generation Internet environment, client server systems should be able to take advantage of currently under utilised resources on client devices. The heterogeneous nature of clients means that for an application to take full advantage of all available resources, it must adapt dynamically to suit its environment. From an examination of existing methods, this thesis provides a rationale for mobile objects as a means for efficient adaptation and usage of client resources. We provide an analysis of several existing frameworks attempting to address the issues involved in dynamic adaptation using mobile objects, and develop a solution for object transport and reference management in the recently proposed MobJeX framework.
Rationale for Targeting CD6 as a Treatment for Autoimmune Diseases

CD6 is a 105–130 kDa surface glycoprotein expressed on the majority of T cells and a subset of B cells. The human cd6 gene maps to chromosome 11, and the expression of its protein product is tightly regulated. CD6 mediates cellular adhesion migration across the endothelial and epithelial cells. In addition, it participates in the antigen presentation by B cells and the subsequent proliferation of T cells. CD6 may bind in trans to surface glycoproteins (such as ALCAM and 3A11), or to microbial lipopolysaccharides, and may bind in cis to endogenous ligands (such as CD3 and CD5), and thereby deliver a costimulatory signal. Transinteractions are reinforced during autoimmune diseases (e.g., rheumatoid arthritis (RA), Sjögren's syndrome, and multiple sclerosis) and some cancers. Based on experimental data and on clinical results in RA and psoriasis, we believe that the recent humanized anti-CD6-specific mAb T1h may act as a regulator of the immunological response in addition to its function as an anti-T- and -B cell agent.