Miracle-dz/UniFAR-FTUs huggingface dataset:
Malaria Detection Using ANN

-Malaria is a life-threatening disease so rapid, accurate diagnosis is required to control the disease. The detection of Malaria parasites is done by pathologists manually using microscopes. The manual microscopic examination is still the gold standard for malaria diagnosis, it is tedious, time consuming and requires special training and considerable expertise, where the lack of access to malaria diagnosis is largely due to shortage of expertise. The identification and counting the number of RBCs in the image is very important to diagnose. In this study proposed a system to detects and identification malaria parasites and counting the number of RBCs in the image from microscopic images. The dataset was collected from CDC dataset site. The proposed system began by pre-processing, to remove unwanted objects and noise from the image by morphological reconstruction. After pre-processing the image region of interest (Erythrocyte or RBCs) was segmented from the background by using Marker controlled watershed method applied on green channel color image. Next, the cell which has a plasmodium was extracted by k mean cluster. Then the statistical features were used in all of the cells to show the infected cells, and healthy cells. The ANN classified the normal and infected cells. The framework was tested to classify the RBCs in blood cell images, and the results are; accuracy (99.3%), sensitivity (98.6%), and specificity (94.8%).
Approximate Variational Inference For Mixture Models

Learning truths behind real, relevant data is faced with uncertainty. A probabilistic view on unsupervised learning considers this uncertainty in its learning objectives through probability distributions and inference. The expressiveness of probability distributions is further enhanced by mixture models, a linear combination of such distributions. This thesis discusses the concept of variational inference in Bayesian Gaussian mixture models. We present di erent approaches to modeling the variational posterior of such mixtures with Normalizing Flows and provide proof of concept experimental results. The approaches have been devised as improvements and extensions to one another, ultimately leading to collapsed variational inference, where the assignment variables of the Bayesian Gaussian mixture model have been marginalized. We further derived a decomposable update procedure formixtures of Normalizing Flows based onwork presented in density estimation for Gaussian mixtures.
Observation System Simulation Experiments in the Atlantic Ocean for enhanced surface ocean pCO2 reconstructions

Abstract. To derive an optimal observation system for surface ocean pCO2 in the Atlantic Ocean and the Atlantic sector of the Southern Ocean eleven Observation System Simulation Experiments (OSSEs) were completed. Each OSSE is a Feed-Forward Neural Network (FFNN) that is based on a different data distribution and provides ocean surface pCO2 for the period 2008–2010 with a 5 day time interval. Based on the geographical and time positions from three observational platforms, volunteering observing ships (VOS), Argo floats and OceanSITES moorings, pseudo-observations were constructed using the outputs from an online-coupled physical-biogeochemical global ocean model with 0.25° nominal resolution. The aim of this work was to find an optimal spatial distribution of observations to supplement the widely used Surface Ocean CO2 Atlas (SOCAT) and to improve the accuracy of ocean surface pCO2 reconstructions. OSSEs showed that the additional data from mooring stations and an improved coverage of the Southern Hemisphere with biogeochemical ARGO floats corresponding to least 25 % of the density of active floats (2008–2010) (OSSE 10) would significantly improve the pCO2 reconstruction and reduce the bias of derived estimates of sea-air CO2 fluxes by 74 % compared to ocean model outputs.
What Can We Learn about Neighborhood Effects from the Moving to Opportunity Experiment?

Experimental estimates from Moving to Opportunity (MTO) show no signiﬁcant impacts of moves to lower-poverty neighborhoods on adult economic self-sufﬁciency four to seven years after random assignment. The authors disagree with Clampet-Lundquist and Massey’s claim that MTO was a weak intervention and therefore uninformative about neighborhood effects. MTO produced large changes in neighborhood environments that improved adult mental health and many outcomes for young females. Clampet-Lundquist and Massey’s claim that MTO experimental estimates are plagued by selection bias is erroneous. Their new nonexperimental estimates are uninformative because they add back the selection problems that MTO’s experimental design was intended to overcome.
ApneaDetector

Sleep apnea is a sleep disorder in which breathing is briefly and repeatedly interrupted. Polysomnography (PSG) is the standard clinical test for diagnosing sleep apnea. However, it is expensive and time-consuming which requires hospital visits, specialized wearable sensors, professional installations, and long waiting lists. To address this problem, we design a smartwatch-based system called ApneaDetector, which exploits the built-in sensors in smartwatches to detect sleep apnea. Through a clinical study, we identify features of sleep apnea captured by smartwatch, which can be leveraged by machine learning techniques for sleep apnea detection. However, there are many technical challenges such as how to extract various special patterns from the noisy and multi-axis sensing data. To address these challenges, we propose signal denoising and data calibration techniques to process the noisy data while preserving the peaks and troughs which reflect the possible apnea events. We identify the characteristics of sleep apnea such as signal spikes which can be captured by smartwatch, and propose methods to extract proper features to train machine learning models for apnea detection. Through extensive experimental evaluations, we demonstrate that our system can detect apnea events with high precision (0.9674), recall (0.9625), and F1-score (0.9649).
The Effects of Imagination of One’s Own Future on Facial Recognition

The effects of imagination of one's own future on facial recognition Sub Title Author 日根, 恭子(Hine, Kyoko) Publisher Centre for Advanced Research on Logic and Sensibility The Global Centers of Excellence Program, Keio University Publication year 2010 Jtitle CARLS series of advanced study of logic and sensibility Vol.3, (2009. ) ,p.205210 Abstract Notes Part 3 : Cognition and Language Genre Research Paper URL https://koara.lib. keio.ac. jp/xoonips/modules/xoonips/detail.php? koara_id=KO12002001-2010033 1-0205
Measurement of Customer Perceptions of Logistics Service Quality

Customer perception of the services provided by a company is essential in maintaining service quality [1]. Service quality has to be adjusted to the desired service's expectations to satisfy customers [2]. Service quality determines the advantages of a company from competitors [3]. Along with the development of e-commerce, there is increasingly fierce competition among logistics service providers [4]. Quality of logistics services is recognized as a significant business component, competitiveness, and overall customer satisfaction [5]. The quality of logistics services plays a vital role in customer satisfaction [6]. Several empirical studies prove a relationship between improved logistics services quality with increased customer satisfaction [7]. Logistics service quality issues have attracted the attention of many researchers. One of the methods used in measuring customer satisfaction with the quality of logistics services is the logistics service quality method [8] [9]. The logistics service quality method ARTICLE INFO ABSTRACT
Episodes Meta Sequence S 2 Fast Update Slow Update Fast Update Slow Update

Decomposing knowledge into interchangeable pieces promises a generalization advantage when there are changes in distribution. A learning agent interacting with its environment is likely to be faced with situations requiring novel combinations of existing pieces of knowledge. We hypothesize that such a decomposition of knowledge is particularly relevant for being able to generalize in a systematic manner to out-of-distribution changes. To study these ideas, we propose a particular training framework in which we assume that the pieces of knowledge an agent needs and its reward function are stationary and can be re-used across tasks. An attention mechanism dynamically selects which modules can be adapted to the current task, and the parameters of the selected modules are allowed to change quickly as the learner is confronted with variations in what it experiences, while the parameters of the attention mechanisms act as stable, slowly changing, metaparameters.We focus on pieces of knowledge captured by an ensemble of modules sparsely communicating with each other via a bottleneck of attention. We find that meta-learning the modular aspects of the proposed system greatly helps in achieving faster adaptation in a reinforcement learning setup involving navigation in a partially observed grid world with image-level input. We also find that reversing the role of parameters and meta-parameters does not work nearly as well, suggesting a particular role for fast adaptation of the dynamically selected modules.
Hybrid VLC Communications System for Increased Security Based on Raspberry Pi Microcomputer

VLC (Visible Light Communications) technology represents nowadays a new paradigm that could have a significant impact on future wireless communications. Although this technology has many advantages, one of the most common problem generated by the use of optical communication systems (based on the light in the visible spectrum), is the increased degree of disruption of the communication channel under the direct sunlight influence. The purpose of this article is to present the technological developments specific to the VLC/IR-RF (Visible Light Communication / Infrared - Radio-Frequency) hybrid system developed in the framework of a scientific research project started in 2017, which were recorded during the first half of 2019. This system based on multiple sensory devices such as temperature, motion, light intensity, dust, IR and microbolometer sensors will present the ability of intelligent monitoring and control of indoor environments (houses, office buildings, universities, campuses, etc.). From the point of view of the final purpose of the project, this will result in a hybrid bidirectional optical communication system capable of supporting high transfer rates, increased resistance to the specific sunlight disturbance, and the possibility of transmitting sensory information over long distances. The previous experimentation activities undertaken during the project were based on the use of the Arduino UNO development boards. Currently, it has been chosen to replace them with the development boards based on the ARM Cortex-A53 processor, in order to improve the system’s performance. The Arduino development boards have limited the performance of the communications system from the point of view of the transfer speeds and distances. The new Raspberry Pi development boards, being a complete operating and control system, presents high operational performances that can be used in favor of the final goal of the project.
How to form the leading innovation capability a multi-case study based on Haier and Huawei

This paper analyzes the innovation practices of Haier Group and Huawei Company since the leading innovation. On the basis of the existing research on “innovation leading”, this paper makes full use of the theoretical knowledge of original innovation and meaningful innovation, and tries to explore the formation path of leading innovation ability. In this paper, it is found that: First, the accumulation of original innovation ability supports the formation and the development of leading innovation ability. In the formation and the development of leading innovation ability, it is always accompanied by the accumulation and improvement of the original innovation ability. Second, the realization of leading innovation is always accompanied by the independent and controllable open innovation system. Under the condition of independent and controllable ability, the integration of domestic and foreign high-quality innovation resources for open innovation also plays a certain role in promoting the formation of leading innovation ability. Third, stimulating employees’ innovation behavior can stimulate the enthusiasm and creativity of innovation of all employees, and reserve innovation power for enterprises’ leading innovation, which is an important factor to promote the formation of enterprises’ leading innovation ability. Fourth, the sense of social responsibility conducive to innovation, driven by the entrepreneurial spirit, has formed a culture of innovation among all employees of the enterprise. Innovation and reform have become deeply embedded in the development of the enterprise, providing a value orientation for the formation of the leading innovation ability of the enterprise.
A Survey on Different Attacks in LTE/LTE-A Networks

This paper is about security assaults in LTE/LTE-A Systems. The Long haul Development (LTE)/LTE-Progressed (LTE-An) arrange gives propelled administrations to billions of clients with its higher transfer speeds, better range effectiveness, and lower dormancy than heritage cell systems. Be that as it may, regardless of whether it experiences new security dangers because of its everything IP-based heterogeneous design. Accordingly, there is a basic need to play out a fast and precise system security estimation in LTE/LTE-A system. To accomplish LTE/LTE-A system security estimation, security-applicable information (in short security information) assortment and information examination for assault discovery are required as essentials. Be that as it may, the majority of the current work just spotlights on information assortment and examination for a specific sort of LTE/LTE-An assaults. Little work has been done to exhaustively perform information assortment and examination for identifying different assaults on LTE/LTE-A system. Not quite the same as past work, In this paper we focused on DOS, DDOS Man-in-the-Center (MitM) assaults, rebel base station assaults and the answers for such assaults were broken down to secure LTE and LTE-A systems
Exploring APOE Epsilon4 Genotype to Predict MCI-to-AD Dementia: A Meta- Analysis

2Department of Image, Shanghai Pudong New Area Traditional Medical Hospital, Shanghai, People’s republic of China 3Department of Neurology, Shanghai 10th People Hospital of Tongji University, Shanghai, People’s republic of China 4Department of Image, Huashan Hospital Affiliated to Fudan University, Shanghai, China 5Department of Cardiovascular Medicine, Research Center for Translational Medicine, Shanghai East Hospital of Tongji University, Shanghai, People’s republic of China
VARIABLES SOCIODEMOGRÁFICAS QUE INCIDEN EN LAS COMPETENCIAS DIGITALES DEL PROFESORADO UNIVERSITARIO

La educación en los últimos años ha experimentado cambios sustanciales en lo académico, administrativo y organizacional, debido a la irrupción de las Tecnologías de la Información y Comunicaciones (TIC). Esta situación ha provocado pasar de una sociedad de la información a una sociedad del conocimiento, la cual exige algunas competencias claves para un mejor desempeño profesional. En este sentido, el objetivo de este trabajo es determinar si existe relación entre las variables edad, género y área del conocimiento de los profesores universitarios de Ecuador y sus competencias digitales. La metodología utilizada fue cuantitativa, con un diseño no experimental transversal, y su alcance de tipo descriptivo e inferencial. Se trabajó con una muestra de 657 docentes, a quienes se les aplicó un instrumento de 50 ítems, para identificar las cinco dimensiones abordadas de la competencia digital. Entre los resultados obtenidos, están las diferencias significativas encontradas entre algunas competencias digitales, en relación con la edad y área de conocimiento del profesorado. Como conclusión, se manifiesta la necesidad de desarrollar estrategias para implementar programas de formación orientados al desarrollo de las competencias digitales del profesorado, considerando las diferencias individuales y necesidades de capacitación, con la finalidad de evitar la infrautilización de los recursos tecnológicos.
Neurotoxins from Snake Venom

Found within snake venoms are a variety of toxic and nontoxic proteins. The effects of snake venoms depend on all of the components of that venom. However, the lethal effects are usually related to the most potent toxins found within the venom; the two most toxic proteins found in snake venom are neuro- and cardiotoxins. This article reviews a variety of neurotoxins found in snake venom. The range of neurotoxins present in snake venom is varied and includes: peripheral and noncentral, presynaptic, postsynaptic, potassium-channel inhibiting, muscarinic transmission inhibiting, and anticholinesterase types.
19 Decreasing neonatal jaundice readmission rates through implementation of a jaundice management guide

Background Baylor Scott and White Medical Center at Waxahachie (BSWMCW), a level 1 neonatal designated facility, had rising neonatal jaundice readmission rates for two fiscal years (1.7% - 2.6%). Based off literature review, this was above the average rate for hospitals with similar populations (0.5% - 2.0%). Neonatal jaundice readmissions have several effects on families and the neonate related to increased costs, stress on bonding, and increased risk for hospital acquired infections. Objectives By June 30, 2019, BSWMCW will reduce the rolling neonatal jaundice readmission rate from 2.6% (July 1, 2017-June 30, 2018) to less than 1% (July 1, 2018 – June 30, 2019). Methods A multidisciplinary committee met to identify why excessive neonatal jaundice readmissions occurred. Issues identified were inconsistent practices in starting and stopping phototherapy, timing of discharge, and timing of newborn follow up in infants with jaundice (figure 1). The team prioritized management of jaundice through recognizing plan of care modifications during the initial hospitalization which would impact newborn readmission rates. Initially, clear guidelines were created on when to start or stop phototherapy, including discharge criteria, followed by implementation of new supplementation guidelines. Donor milk was offered as an alternative to formula supplementation. In order to adhere to supplementation guidelines, standardized newborn weights at 24 hours of life was added. Finally, jaundice lab testing was required through BSWMCW inpatient lab prior to admission rather than accepting lab values from other facilities which were often found to be different (figure 2). Results Overall, the rolling percentage of neonatal jaundice readmissions for BSWMCW decreased from 2.6% to 0.8%, meeting the goal of less than 1%. This was sustained through fiscal year 2019 (figure 3). Conclusions Neonatal Jaundice readmission rates can be affected through standardizing jaundice management protocols. In changing the timing of neonatal weights, this improved neonatal care, even for those without jaundice.
Switched capacitor‐based continuous input current high step‐up impedance source DC–DC converter

: The conventional converter needs to be operated at a high duty cycle to achieve maximum possible voltage gain. This leads to severe reverse recovery of switches, increases losses, and reduces efficiency. This study presents a modified switched-capacitor-based high gain continuous input current quasi-Z-source converter (qZSC) for DC microgrid applications. The proposed converter utilises the embedded switched-capacitor techniques and can give a high voltage gain with a low duty ratio compared to the conventional converters. The proposed converter also experiences less capacitor voltage and inductor current stresses compared to the conventional Z-source converters. This facilitates the use of lower-rated capacitors and inductors for higher power applications. Detailed steady-state, small-signal, and power loss analysis of proposed qZSC is discussed in this study. A prototype of 100 W is designed and implemented using TI TMS320F28335 Experimenter Kit to verify the operation of the proposed converter.
Flavor Activity of Sesquiterpene Oxidation Products, Formed upon Lab-Scale Boiling of a Hop Essential Oil–Derived Sesquiterpene Hydrocarbon Fraction (cv. Saaz)

The “kettle hop” aroma, a most complicated flavor characteristic of conventionally hopped lager beers, has been associated with hop essential oil–derived oxygenated sesquiterpenoids. In this study, an oxygenated sesquiterpenoid fraction, mainly consisting of sesquiterpene oxidation products, was obtained by lab-scale boiling of a varietal sesquiterpene hydrocarbon fraction (cv. Saaz), and its volatile fingerprint was characterized analytically via headspace solid-phase microextraction GC-MS. Addition of this fraction to nonaromatized iso-α-acid-bittered beer resulted in a shift of the flavor profile in favor of woody, spicy, and hoppy notes. GC-olfactometry analysis of the sensory-relevant oxygenated sesquiterpenoid fraction revealed two zones that were clearly flavor active, the first zone containing humulene epoxide III, humulenol II, and caryophylla-4(12),8(13)-diene-5-ol, and the second zone comprising (3Z)-caryophylla-3,8(13)-diene-5-ol (α and β) and 14-hydroxy-β-caryophyllene. These compounds are candidate key impact compounds for kettle hop aroma. Although the oxygenated sesquiterpenoid fraction was created offline, the fraction shows potential relevance to brewing practice.
Pathogenic Reaction of Different Isolates of Colletotrichum capsici on Chilli Cultivars

Chilli (Capsicum annuum L.) is one of the most valued spicy vegetable and it has a unique role in human diet. They are nutrient rich with vitamins A, C, E and minerals like pottassium. It is an annual herbaceous vegetable of solanaceae which is cultivated in almost all places. The important chilli growing states are Andhra Pradesh, Karnataka and Tamil Nadu. Inspite of chilli is infected by various biotic and abiotic factors. In biotic several pathogens are causing severe diseases and yield loss. The Chilli anthracnose pathogen C. capsici infects diverse host with a high degree of pathogenic variability (Akhtar and Singh, 2007). The genus Colletotrichum causes anthracnose on wide International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 9 Number 11 (2020) Journal homepage: http://www.ijcmas. com
Identificación de la argumentación en el desarrollo de la modelación en la sala de matemáticas

El objetivo del proyecto es identificar momentos de argumentacion en el desarrollo de la modelacion en la clase de matematicas. Para ello, implementamos una tarea matematica de modelacion en un curso de 2o medio (15-16 anos) en un establecimiento particular subvencionado de Santiago. La clase de 90 minutos fue analizada caracterizando los momentos argumentativos y de modelacion para determinar relaciones entre ambas competencias en el aula de matematica. Con ello, se presenta una planificacion como propuesta para gestionar esta actividad en una clase de matematica. PALABRAS CLAVE. Competencias matematicas; argumentacion; modelacion. Doi: 10.21703/rexe.20201941henriquez22