Miracle-dz/UniFAR-FTUs huggingface dataset:
Cloud Computing with Machine Learning Could Help Us in the Early Diagnosis of Breast Cancer

The purpose of this study is to develop tools which could help the clinicians in the primary care hospitals with the early diagnosis of breast cancer diagnosis. Breast cancer is one of the leading forms of cancer in developing countries and often gets detected at the lateral stages. The detection of cancer at later stages results not only in pain and in agony to the patients but also puts lot of financial burden on the caregivers. In this work, we are presenting the preliminary results of the project code named BCDM (Breast Cancer Diagnosis using Machine Learning) developed using Mat lab. The algorithm developed in this research cancer work based on adaptive resonance theory. In this research work, we concluded how Art 1 network will help in classification of breast. The aim of the project is to eventually run the algorithm on a cloud computer and a clinician at a primary healthcare can use the system for the early diagnosis of the patients using web based interface from anywhere in the world.
ABCD rule based automatic computer-aided skin cancer detection using MATLAB ®

Detection of skin cancer in the earlier stage is very critical and this paper proposes and explains the implementation of automatic detection and analysis Skin Cancer from given photograph of patient’s cancer affected area. The proposed scheme is using Watershed Segmentation for image segmentation, border detection & decision related with structural nature of lesion, Wavelet Transformation and decomposition for image improvement, de-noising, histogram analysis & for calculating diameter of lesion and mamdani based Fuzzy Inference System color based skin classification based on the pixel color severity. We are using worldwide recognized ABCD rule of cancer diagnostic. We are calculating TDS Index for differentiating and making final decision of non-cancerous (benign), suspicious and cancerous (melanoma) image, which will help patients/doctors/dermatologist/clinicians for taking further medical treatment, which will ultimately saves patients valuable time, money and life.
Indices of Abdominal Adiposity and Cardiorespiratory Fitness Test Performance in Middle-School Students

Background. Previous research suggests that use of BMI as a screening tool to assess health in youth has limitations. Valid alternative measures to assess body composition are needed to accurately identify children who are aerobically fit, which is an indicator of health status. The purpose of this study was to examine the associations between select anthropometric measures and cardiorespiratory fitness test performance in middle-school students. Methods. Participants included 134 students (65 boys and 69 girls) recruited from the 6th, 7th, and 8th grades. Anthropometric measures consisted of BMI, waist circumference (WC), waist-to-height ratio (WHtR), and percent body fat estimated from two-site skinfolds (%BF-SKF), as well as the hand-held OMRON BIA device (%BF-BIA). Cardiorespiratory fitness tests included the one-mile run and PACER test. Data were collected on four separate testing days during the students' physical education classes. Results. There were statistically significant moderate correlations between the %BF estimations, WHtR, and cardiorespiratory fitness test scores in both genders (P < .001). BMI at best only displayed weak correlations with the cardiorespiratory fitness test scores. Conclusions. The results suggest that alternative measures such as %BF-SKF, %BF-BIA, and WHtR may be more valid indicators of youth aerobic fitness lending to their preferred use over BMI.
Unmanned marsupial sea-air system for object recovery

This paper presents preliminary results obtained from a cooperative heterogeneous system consisting of an unmanned surface marine vehicle (USV) and an unmanned aerial vehicle (UAV). The envisioned scenario for this marsupial system is unmanned recovery of objects floating at the sea surface. The specific mission that is addressed in this paper includes the following phases: coarse approach where the USV approaches the object area using navigation filter based on GPS measurements; fine approach where the UAV tracking the USV sends relative distances between the USV and the object which is visible in the UAV's field of view; and tugging where the USV takes the object to safety after the initial contact has been achieved. The paper describes the ROS-based control architecture, presents simulation results, and addresses control issues related to obtaining measurements from two sources with different variances.
Counselling For Self-Employment: the Application of Decision Support System

The article considers the provision of decision support opportunities for unemployed people who are seeking for self-employment and opening a new business. The purpose of this paper is to consider the application of decision support system (DSS) for e-counselling of the unemployed, specially focusing on self-employment solutions. The development of DSS is tackling main social challenges of the long-term unemployed: it conveys an experience from previous employment; provides new business opportunities, which are highly related to person’s hobbies; and it connects people by developing complementary groups of same interests and same positive attitudes towards entrepreneurship. From a technical perspective we suggest that it is advisable to place a workflow engine at the core of the Internet based e-decision making system. This will let us generate and manage personalized and adaptable individual recommendation access. The access flow algorithm of DSS consists of three interconnected blocs: the first bloc is constructed for the self- containment as process logic and analysis of consumer objectives; the second one analyses person’s ability for entrepreneurship, it also evaluates individual’s overall motivation to start his own business; and the third bloc provides with potential complementary business partners or business start-up.
The Confluence of Heavy Metal Biooxidation and Heavy Metal Resistance: Implications for Bioleaching by Extreme Thermoacidophiles

Abstract: Extreme thermoacidophiles ( T opt > 65 °C, pH opt < 3.5) inhabit unique environments fraught with challenges, including extremely high temperatures, low pH, as well as high levels of soluble metal species. In fact, certain members of this group thrive by metabolizing heavy metals, creating a dynamic equilibrium between biooxidation to meet bioenergetic needs and mechanisms for tolerating and resisting the toxic effects of solubilized metals. Extremely thermoacidophilic archaea dominate bioleaching operations at elevated temperatures and have been considered for processing certain mineral types (e.g., chalcopyrite), some of which are recalcitrant to their mesophilic counterparts. A key issue to consider, in addition to temperature and pH, is the extent to which solid phase heavy metals are solubilized and the concomitant impact of these mobilized metals on the microorganism’s growth physiology. Here, extreme thermoacidophiles are examined from the perspectives of biodiversity, heavy metal biooxidation, metal resistance mechanisms, microbe-solid interactions, and application of these archaea in biomining operations.
Predicting source gaze fixation duration: A machine learning approach

In this paper an attempt has been made to predict the gaze fixation duration at source text words using supervised learning method, namely Support Vector Machine. The machine learning models used in the present work make use of lexical, syntactic and semantic information for predicting the gaze fixation duration. Different features are extracted from the data and models are built by combining the features. Our best set up achieves close to 50% classification accuracy.
General properties and synthesis of PWM DC-to-DC converters

General properties that interrelate network complexity, attainable conversion ratios, and switch stresses are derived for pulse-width-modulated (PWM) DC-to-DC converters. The emerging synthesis procedure guarantees that complete classes of converters that satisfy a set of prescribed specifications are generated. The input specifications include the desired DC conversion ratio, nonpulsating terminal currents, possible coupling of inductors, the allowed number of switches, and, in particular, the number of active transistor switches. As a result, a number of novel PWM topologies are uncovered. <<ETX>>
Enhancing the network lifetime of cooperative wireless sensor networks using energy harvesting technique

Wireless Sensor Networks (WSN) consists of a large number of miniature size, low-power, smart sensor nodes interfacing with one another and deployed over a certain inaccessible geographical locale having inadequate power and storage space. Energy efficiency is a foremost concern in WSN. To maximize the network lifetime, one possible solution is to harvest energy from the ambient boundless accessible energy sources in the environment nearby to the sensor nodes. The use of energy harvesting (EH) nodes as cooperative relays is a promising and budding solution in WSN. Energy harvest from one source is not sufficient to congregate the power requirement of sensor nodes. In this work, in order to improve the network lifetime electromagnetic radiation energy harvesting (EMR EH) method has been proposed. Communication is carried out by signal cooperation through relays in order to assist the sources to exchange their data for longer time periods. The current slot's transmission is based on transmitter knowledge about the present channel signal to noise ratio (SNR), past harvested energy and present energy stored in the battery. In order to solve the low power problem while maximizing the lifetime of wireless sensor nodes power management schemes like water filling energy harvesting strategies is included. The network performance metrics such as the probability of successful data exchange and the network lifetime gain has been derived and simulated using MATLAB. Simulations results illustrate that proposed technique afford enhanced result compared to existing energy harvesting schemes.
Spectroscopic Characterization of Copper-Chitosan Nanoantimicrobials Prepared by Laser Ablation Synthesis in Aqueous Solutions

Copper-chitosan (Cu-CS) nanoantimicrobials are a novel class of bioactive agents, providing enhanced and synergistic efficiency in the prevention of biocontamination in several application fields, from food packaging to biomedical. Femtosecond laser pulses were here exploited to disrupt a Cu solid target immersed into aqueous acidic solutions containing different CS concentrations. After preparation, Cu-CS colloids were obtained by tuning both Cu/CS molar ratios and laser operating conditions. As prepared Cu-CS colloids were characterized by Fourier transform infrared spectroscopy (FTIR), to study copper complexation with the biopolymer. X-ray photoelectron spectroscopy (XPS) was used to elucidate the nanomaterials’ surface chemical composition and chemical speciation of the most representative elements. Transmission electron microscopy was used to characterize nanocolloids morphology. For all samples, ξ-potential measurements showed highly positive potentials, which could be correlated with the XPS information. The spectroscopic and morphological characterization herein presented outlines the characteristics of a technologically-relevant nanomaterial and provides evidence about the optimal synthesis parameters to produce almost monodisperse and properly-capped Cu nanophases, which combine in the same core-shell structure two renowned antibacterial agents.
Legislation, Case Law and Current Issues in Inclusion: An Analysis of Trends in the United States and Australia

Parent, civil rights, education and advocacy groups initiated a socio-political movement towards inclusive education in the 1960's by challenging education authorities to include students with disabilities in regular school settings. They argued from a 'rights-based platform that reflected the ideals of equity and social justice expressed in a number of international statements including, for example, the Universal Declaration of Human Rights (1948) and the United Nations Convention on the Rights of the Child (1972). It was not until legislative changes were made in the United States, however, that schools were required to educate students with disabilities alongside their non-disabled peers to the maximum extent possible. Since then, special education and the management of inclusion in schools have become public and accountable through the law and the pace of litigation over issues that relate to inclusion, student rights, disability and discrimination significantly increases each year (Osborne, 2000). This article analyses and compares legislation and appeal processes that relate to disability discrimination and the management of inclusion in schools in common law countries including the United States and Australia. Specific laws and rights of appeal against administrative decisions and school actions that relate to inclusion are identified. Finally, the Australian disability discrimination legislation from both State and Commonwealth jurisdictions is described and analysed through the interpretation of case law. In particular the concepts of 'reasonable accommodation' and 'unjustifiable hardship' are discussed in relation to the way that principals manage inclusion in schools.
Stochastic modelling and identification of industrial robots

This paper focuses on identifying the operations of industrial manipulators that are often realised as robots with six degrees of freedom. The identification is based on the measurement of the power consumption of the whole robot without separating it to the individual axes. Such a case corresponds to industrial use cases. The robot is taken as an unobservable system with respect to its internal states. This disadvantage is overcome using hidden time-varying Markov chains. The results are verified on a simple one-axis manipulator and further discussion about the extension of the model is provided.
Support vector machines vs multi-layer perceptrons in particle identification

In this paper we evaluate the performance of Support Vector Machines (SVMs) and Multi-Layer Perceptrons (MLPs) on two di(cid:11)erent problems of Particle Identi(cid:12)cation in High Energy Physics experiments. The obtained results indicate that SVMs and MLPs tend to perform very similarly.
Fluorescence of Photoreceptor Cells Observed in vivo

Most rhabdomeres in the eye of the j y (Musca domestica) are juorescent. One kind ofjuorescent emission emanates from a photoproduct of the visual pigment, other kinds may be ascribed to photostable pigments. These phenomena provide not only a means of spectrally mapping the retina but also a new spectroscopic tool for analyzing the primary visual processes in vivo. Fluorescence is not the most salient property to be expected from a visual pigment. Rather than waste excitation energy in such a "trivial" process, molecules of visual pigment would be expected to have a high efficiency for photoisomerization, as they have (1). When rhodopsin fluorescence was reported (2), it was found to have a low quantum efficiency of less than 1 percent. These considerations may explain why fluorescence methods, despite their selectivity, have not been used extensively for studying the primary steps in the visual process. But now more than a century has passed since Helmholtz first reported fluorescence of the vertebrate retina and subsequent studies have ascribed the various fluorescence colors, in part, to intermediates of visual pigment bleaching (3). Using a technique of ommatidial fundus fluoroscopy applied to an intact animal, we show that retinula cells of flies may exhibit various fluorescence colors closely related to the properties both of visual pigments and of the recently discovered accessory photostable pigments contained in the rhabdomeres. In the compound eye of diurnal insects, the receptor cells are separated from the outside world by transparent components (crystalline cone and cornea) whose total thickness rarely exceeds 0.1 mm. Taking advantage of this situation, which is encountered in no vertebrate eye, we recently devised several techniques for studying photoreceptor cell processes in live animals (4, 5). One of these techniques consists of covering the "waffled" corneal surface with a medium such as nail polish, immersion oil, or even water, whose refractive index approximately matches that of chitin. Optically neutralized in this way, each corneal lenslet becomes a porthole behind which the seven receptor endings of a retinula can be viewed with a micro-
Biased multiobjective optimization for constrained single-objective evolutionary optimization

Constrained optimization problems widely exist in real world applications. A popular method to solve the problems is to transform the constraints to additional objectives and then the transformed problems can be solved by the multiobjective optimization techniques. The original multiobjective optimization techniques, such as Pareto dominance, lack the search bias to the constraints, which may lead to inferior performance of the algorithm. In this paper, first a concept of biased dominance or b-dominance to bias the search directly and explicitly is introduced, and then by combining b-dominance with a differential evolution, a Biased Multiobjective Optimization (BMO) algorithm is proposed for solving the constrained single-objective optimization problems. The BMO algorithm is comprehensively evaluated on 22 well-known benchmark test functions and the experimental results indicate that the BMO algorithm is capable of achieving competitive results compared with other state-of-the-art methods.
Road to Malaysia's Day of Destiny

Prime Minister Najib Razak's decision not to accommodate the concerns of the protesters last week, and even to demonise their actions, now prods Malaysia further along the road to its day of destiny, where the political fate of Malaysia's 54-year government will be determined. So far, the routes chosen are one of confrontation rather than compromise, making resolution to differences even more difficult.
The Stock Market and the Economy

THE STOCK MARKET decline of 1973-74 marked the longest and steepest fall in corporate-stock prices since the depression of the 1930s. The loss of stockholder wealth in market prices amounted to $525 billion, or 43 percent. ' The magnitude of this decline in stock values, in conjunction with the subsequent collapse of aggregate demand in 1974-75, has sparked a renewed discussion of the role of the stock market in business cycles. The debate-as is so frequently the case-is not new to economics. Several significant contributions recently made at both the conceptual and empirical levels seem, however, to justify a reexamination of the issues. The dispute about the import of changes in the stock market revolves around their causal role in economic fluctuation: Are they a source of variation in aggregate demand? Does the causation run solely in the opposite direction? Or do the levels of economic activity and of stock prices simply respond similarly to other, more basic, economic forces, with no direct causal link between the two? This third interpretation is consistent with a view that the stock market reflects investors' attempts to forecast economic trends. The fact that movements in stock prices foretell major
Transparent collaborative haptic simulation

This paper deals with the problem of transparency (or fidelity) in force feedback systems or more particularly for haptics simulation under time delay transmission. The haptics rendering transparency is all the more difficult in distributed collaboration between distant users because it is necessary also to make feel faithfully the mutual interactions. The idea suggested in this article gives an original solution to overcome this lack of transparency in haptic shared collaborations on the network using a principle called the “Latency Envelope” (LE). One advantage of this implementation is the anticipation of the contact between users and virtual objects. The delay can then be partially or completely compensated from the open perception point of view. Also it does not affect at all the stability of haptics simulation (carried out using well known control laws).
Parietal cortex activation predicts memory decline in apolipoprotein E-ϵϵ4 carriers

Apolipoprotein E-ϵ4 is the main known genetic risk factor for Alzheimer's disease. Functional abnormalities in the parietal cortex have been reported for Alzheimer's disease patients and also for those at risk. Hence, a critical question is whether measurements of parietal cortex integrity may predict negative outcome among at-risk persons. We studied nondemented apolipoprotein E-ϵ4 carriers and found a significant relationship between parietal blood-oxygen-level-dependent functional magnetic resonance imaging response during a word categorization task and subsequent episodic memory performance. Thus, the results show that parietal cortex alterations predict memory decline in nondemented apolipoprotein E-ϵ4 carriers, and hence likely progression to Alzheimer's disease.
Comparative Political Studies Giovanni Capoccia and Daniel Ziblatt Agenda for Europe and Beyond The Historical Turn in Democratization Studies : A New Research

This article lays the theoretical and methodological foundations of a new historically minded approach to the comparative study of democratization, centered on the analysis of the creation, development, and interaction of democratic institutions. Historically, democracy did not emerge as a singular coherent whole but rather as a set of different institutions, which resulted from conflicts across multiple lines of social and political cleavage that took place at different moments in time. The theoretical advantage of this approach is illustrated by highlighting the range of new variables that come into focus in explaining democracy’s emergence. Rather than class being the single variable that explains how and why democracy came about, scholars can see how religious conflict, ethnic cleavages, and the diffusion of ideas played a much greater role in Europe’s democratization than has typically been appreciated. Above all, the authors argue that political parties were decisive players in how and why democracy emerged in Europe and should be at the center of future analyses.
Smaller steps for faster algorithms : a new approach to solving linear systems

In this thesis we study iterative algorithms with simple sublinear time update steps, and we show how a mix of of data structures, randomization, and results from numerical analysis allow us to achieve faster algorithms for solving linear systems in a variety of different regimes. First we present a simple combinatorial algorithm for solving symmetric diagonally dominant (SDD) systems of equations that improves upon the best previously known running time for solving such system in the standard unit-cost RAM model. Then we provide a general method for convex optimization that improves this simple algorithm's running time as special case. Our results include the following: * We achieve the best known running time of 0 (m log312 1 log log n log(e 1 log n)) for solving Symmetric Diagonally Dominant (SDD) system of equations in the standard unit-cost RAM model. e We obtain a faster asymptotic running time than conjugate gradient for solving a broad class of symmetric positive definite systems of equations. e We achieve faster asymptotic convergence rates than the best known for Kaczmarz methods for solving overdetermined systems of equations, by accelerating an algorithm of Strohmer and Vershynin [55]. Beyond the independent interest of these solvers, we believe they highlight the versatility of the approach of this thesis and we hope that they will open the door for further algorithmic improvements in the future. This work was done in collaboration with Jonathan Kelner, Yin Tat Lee, Lorenzo Orecchia, and Zeyuan Zhu, and is based on the content of [30] and [35]. Thesis Supervisor: Jonathan Kelner Title: Associate Professor