Reviewerly/exHarmony huggingface dataset:
Prevalence of Plasmodium Falciparum among Nigerians in Abuja and Central States: A Comparative Analysis of Sensitivity and Specificity Using Rapid Diagnostic Test and Microscopy as Tools in Management of Malaria

Introduction:In Nigeria, malaria is endemic with comorbidities such as dengue, chikungunya, Zika, Tuberculosis and HIV/AIDS which makes malaria a deadly infection.Malaria accounts for 25% of infant Mortality and 30% of childhood mortality [1].The use of laboratory methods has become necessary because health workers cannot identify malaria cases reliably using clinical signs and symptoms alone [2,3]. Methods:A cross-sectional study of 403 consenting healthy individuals who came to National hospital, Abuja and Nasarawa State University hospital, Keffi for medical examination were recruited from April 2017 through July 2017.The socio-demographic charactersitics of each participant was obtained through oral consultation.Information collected included the sex, age, occupation and locality to which they belonged.The gold standard tool (microscopy) and RDTs were used to determine the prevalence of malaria infection, the Sensitivity and specificity of RDT was compared to Microscopy gold standard. Results:The prevalence of malaria infection among the 403 subjects was 54.4% and 44.9%.There was a significant difference between the two methods employed (χ 2 = 52.171,p < 0.001).The preponderance of malaria in relation to age was highest (78.9%; 4.7%) for ages (above 51 years), those under 20 years demonstrated a pervasiveness of (57.4%; 31.9%)through the two techniques.A prevalence of (64%; 20%) was observed in the age group (41-50 years) and to a lesser extend (54.3%; 28.6%) those years 31-40 years and (52.3%; 43.7%) age 21-30 years.There were no significant differences between all age groups (χ 2 = 7.4298, P-value = 0.1148).The detection of malaria infection in relation to diagnostic techniques showed a sensitivity and specificity values of 84.5% and 98.2% compared to Microscopy (standard method) which was 100% for all screened cases. Conclusion:Symptomatic diagnosis is the most common method of clinical presentation among people of poor resource countries.It should be noted, however, that many other diseases have similar symptoms to malaria and symptomatic diagnosis alone can be misleading and even harmful.Microscopy and RDTs are parts of good clinical practice in the field of medicine and malaria diagnosis, both tools should be employed in the management of malaria treatment and prevention. ReseARch ARticleCheck for updates
Accelerate the Detection Frame Rate of YOLO Object Detection Algorithm

YOLO (You-Only-Look-Once) is by far the well-known Deep Neural Networks (DNNs) object detection algorithm with real-time performance on a computer with GPUs. Conceptually, YOLO divides the input image of size $$W \times W$$ into non-overlapping square cells with the final feature of size $$S \times S$$ ; i.e. $$(416 \times 416) \rightarrow (13 \times 13)$$ . Each cell is responsible for predicting a single object whose centre falls into it. In this paper, we propose the algorithm that makes use of our observation mapping relationship which states that while the sizes of square cells are changed from layer to layer, their indices are preserved. The algorithm operates by locating a region of change in an input image and identifies the indices of square cells that cover the region. Only the members of the input features within these cells in all layers along the network are required to be operated. When the algorithm is employed along with the spatio-temporal property within video frames, it is capable of attaining the best relative detection of 1.47 (about 7 fps) with 90% correctness. These are benchmarked with the ordinary YOLO object detection on a personal computer: Intel Core i7 CPU at 3.5 GHz with 16 GB of memory and without any sophisticate GPUs, on the Tiny-YOLO network.
Implementasi Google Speech API Pada Aplikasi Koreksi Hapalan Al-Qur'an Berbasis Android

Muroja’ah is a method of repeating new memorization and old memorization that be heard to other people. This method is very popular in Indonesia. In order to make the learning process isn’t boring, it is required a learning media that can be used anytime, one of them are using Android application. The research describes how to build a Qur’an recitation correction application based on Android and integrate it with Google Speech so that application built more interesting and interactive with users. Google Speech be integrate as voice input media, users requested recite Qur’an verses then Google Speech will convert their voice to text. Text result obtained then matched with text in source code. Result of testing the accuracy of Google Speech implementation on this application it’s 100%, that means it’s been as expected.
Number-resolving photon detectors with atoms coupled to waveguides

Number-resolving single-photon detectors represent a key technology for a host of quantum optics protocols, comprising quantum state preparation, quantum metrology, entanglement distribution, and quantum computing. Despite significant advances over the last few decades, state-of-the-art technology can distinguish only very low photon numbers with high fidelity. We show that (artificial) atoms coupled to photonic waveguides constitute an ideal platform to entirely absorb incident photonic wavepackets, even in the presence of disorder and finite Purcell factors, with a fidelity increasing with the number of atoms. Absorption is achieved through engineering a decay channel to a metastable state, such that readout of the atomic state after absorption yields a number-resolving measurement of photon number.
Experimental demonstration of two-color Einstein–Podolsky–Rosen entanglement in a hot vapor cell

Einstein–Podolsky–Rosen (EPR) entanglement, involving pairs of particles that are entangled in position and momenta, is of special importance for quantum information processing. Practical quantum communication requires a two-color entanglement source: visible-band photons used to excite atoms and the communication band used for signal transmission. In this article, we report on the first experimental demonstration of two-color EPR entanglement based on spontaneous Raman scattering thermal Rb atoms using quantum ghost interference and ghost imaging. This work adopts a fundamental experiment that assists in promoting practical quantum communications and in providing a means to perform quantum imaging.
Optimization of infrastructure planning on waste management in Sragen by using linear programming model

The government as the policy maker has responsiblity to make optimized infrastructure planning on waste management by considering several priorities on the purpose. This research aims to identify to what extent the infrastructure planning on waste management optimization is in accordance with the medium-term goal of Sragen governmental agency. The research method used in this study is descriptive quantitative research by using secondary data. This research applies a linear programming model to meet the optimization of infrastructure planning on waste management in Sragen until the year 2026. The aim of this optimization is to minimize the continual operational and maintenance budgets in accordance to waste management regulation in each sub-district of Sragen. Based on the proposed model of infrastructure planning on waste management, in the year 2026 it is projected that the number of population is 870,221 and the quantity of waste production is 2,393 m3 a day; which means that 450 units of dump carts, 8 units of waste-carrying motorcycles, 18 units of containers with 6 m3 capacity, 31 units of temporal dumps, 46 units of 3R waste handling, 12 units of armroll trucks, and 63 units of dump trucks with 10 m3 capacity are needed. The operational and maintenance budgets cost Rp. 30,300,580,120 a year.
Overcoming Cultural and Educational Conservatism is the Way to New Models of Education

The article is devoted to finding ways to overcome conservatism in cultural and educational practices, analyzing traditional and innovative cultural and educational experiences in modern education. The authors consider education as a phenomenon that has a dual nature, which is closely related to the development of cultural traditions and civilizational innovations. The article shows that in the conditions of social turbulence, unpredictabi­lity and uncertainty, constant acceleration in technological and social processes, the cultural and educa­tional practices are lagging behind the demands of modern society. Rooted in the core of the cultural and educational matrix, they restrain the development of our society, in which new generations, born in the conditions of information and digital revolution, have come. These generations have a different worldview, values, attitudes towards career, free time, environmental and safety issues. Their vital elements are the virtual world and the world of modern gadgets with all the ensuing consequences. Generational rift exacerbates problems in the education system, which is changing very slowly. New generations need to be taught not traditionally but taking into account their needs and new technologies. The article provides a number of concrete examples related to the points of growth of cultural and educatio­nal innovations, suggests a number of actions that can lead to formation of new higher education mo­dels that meet the demands of modern society, new type of universities called digital or universities 4.0. In addition, the authors draw attention to the fact that culture and education have similarities and diffe­rences in their nature and functioning. Culture and education are interdependent, which does not negate significant differences between them. Culture, by its nature, is a self-constructive system, and edu­cation is built in accordance with a specific goal setting. The authors consider that the best option is the one in which in the processes of interaction and, especially, interinfluence of culture and education, priorities will be on the side of culture.
Inferring missing metadata from environmental policy texts

The National Environmental Policy Act (NEPA) provides a trove of data on how environmental policy decisions have been made in the United States over the last 50 years.Unfortunately, there is no central database for this information and it is too voluminous to assess manually.We describe our efforts to enable systematic research over US environmental policy by extracting and organizing metadata from the text of NEPA documents.Our contributions include collecting more than 40,000 NEPA-related documents, and evaluating rule-based baselines that establish the difficulty of three important tasks: identifying lead agencies, aligning document versions, and detecting reused text.
Control a 6DOF Anthropomorphic Robotic Structure with Computer Vision as MEMS Input

The presented paper presents a method to control a 6-degree-of-freedom robot manipulator using computer vision as micro-electro-mechanical systems input. Using this technology, we manage to extract 3D information regarding human hand position and orientation and pass it to the robot. The main advantages are: providing a natural and easy to use interaction manner, fast setup and a simplified usage learning curve for the user.
User Identification Using Real Environmental Human Computer Interaction Behavior

In this paper, a new user identification method is presented using real environmental human-computer-interaction (HCI) behavior data to improve method usability.User behavior data in this paper are collected continuously without setting experimental scenes such as text length, action number, etc.To illustrate the characteristics of real environmental HCI data, probability density distribution and performance of keyboard and mouse data are analyzed through the random sampling method and Support Vector Machine(SVM) algorithm.Based on the analysis of HCI behavior data in a real environment, the Multiple Kernel Learning (MKL) method is first used for user HCI behavior identification due to the heterogeneity of keyboard and mouse data.All possible kernel methods are compared to determine the MKL algorithm's parameters to ensure the robustness of the algorithm.Data analysis results show that keyboard data have a narrower range of probability density distribution than mouse data.Keyboard data have better performance with a 1-min time window, while that of mouse data is achieved with a 10-min time window.Finally, experiments using the MKL algorithm with three global polynomial kernels and ten local Gaussian kernels achieve a user identification accuracy of 83.03% in a real environmental HCI dataset, which demonstrates that the proposed method achieves an encouraging performance.
A Proposed Template Image Matching Algorithm for Face Recognition

Automatic matching of people faces is a demanding issue which has recently received increased attention during the recent ages due to its various uses in different applications such as law implementation, security requirements and video indexing. Face images are exposed to a variety of important influences such as illumination variation, difference in looking view, facial expression, occlusion, age difference between compared face images and some individual changes in field settings. Most current face matching algorithms can be classified into two categories; either geometry feature based, or template image based. In this research, a suggested algorithm is developed based on normalized cross correlation algorithm in order to find the similarity measure between verified face images. Normalized correlation is considered one of the methods based on template matching that can be used for finding a presence of a pattern or a feature within an image. A Graphical User Interface (GUI) is prepared to perform all face matching tasks and is used to test face verification. This GUI has been examined by conducting many case studies. The concluded results indicate that the developed algorithm is so robust in face matching and shows good performance
Joint Processing of Language and Visual Data for Better Automated Understanding (Dagstuhl Seminar 19021)

This report documents the program and the outcomes of Dagstuhl Seminar 19021 Joint Processing of Language and Visual Data for Better Automated Understanding. It includes a discussion of the motivation and overall organization, the abstracts of the talks, and a report of each working group.
Gazing Pattern While Using AR Route-Navigation on Smartphone

Recently, many route-navigation applications that combines AR (augmented reality technology) and a map have appeared, and it is possible to understand the route more intuitively. However, when using the navigation with AR, the vision of the user has been considerably limited because the route needs to be checked by superimposing the smartphone screen on the real street scape. In this research, the user’s gazing pattern while using the conventional smartphone navigation and the AR navigation were compared and analyzed with eye movement tracking technology, for considering an efficient route guidance method that makes comprehensibility and safety compatible.
CLP at SemEval-2019 Task 3: Multi-Encoder in Hierarchical Attention Networks for Contextual Emotion Detection

In this paper, we describe the participation of team ”CLP” in SemEval-2019 Task 3 “Con- textual Emotion Detection in Text” that aims to classify emotion of user utterance in tex- tual conversation. The submitted system is a deep learning architecture based on Hier- archical Attention Networks (HAN) and Em- bedding from Language Model (ELMo). The core of the architecture contains two represen- tation layers. The first one combines the out- puts of ELMo, hand-craft features and Bidi- rectional Long Short-Term Memory with At- tention (Bi-LSTM-Attention) to represent user utterance. The second layer use a Bi-LSTM- Attention encoder to represent the conversa- tion. Our system achieved F1 score of 0.7524 which outperformed the baseline model of the organizers by 0.1656.
High Dimensional Data Clustering using Self-Organized Map

As the population grows and e economic development, houses could be one of basic needs of every family. Therefore, housing investment has promising value in the future. This research implements the Self-Organized Map (SOM) algorithm to cluster house data for providing several house groups based on the various features. K-means is used as the baseline of the proposed approach. SOM has higher silhouette coefficient (0.4367) compared to its comparison (0.236). Thus, this method outperforms k-means in terms of visualizing high-dimensional data cluster. It is also better in the cluster formation and regulating the data distribution.
Smooth Local Planning Incorporating Steering Constraints

Individually controllable and steerable wheels provide vehicles with greater flexibility and efficiency. A key challenge in the context of such vehicles lies in the effective planning of the motion commands in order to properly deal with the potentially large required changes in the steering angles and to properly incorporate the given motion constraints. Especially large vehicles often perform large steering angle changes only while standing to prevent physical damage to the robot. In this paper, we introduce a novel planner for vehicles with individually controllable and steerable wheels and two novel methods to incorporate steering constraints. The latter are designed to provide smooth changes of the instantaneous center of rotation (ICR). Extensive experiments in simulation and on the real robot reveal that our methods allow for an effective planning of steering commands, reduce the travel time by decreasing the time spent standing for wheel reconfigurations, and additionally enable the vehicle to accurately follow a given path.
Area-efficient Radix-32 FFT Processor for Hand Gesture Recognition Radar

We propose an area-efficient fast Fourier transform (FFT) processor for hand gesture recognition (HGR) radar and present its hardware design and implementation results. To estimate finger motion, the FFT processor should support at least 600~720-point operation for three-channel input data streams. Hence, we propose three-channel 729-point FFT processor based on the radix-3SUP2 /SUPalgorithm and a multipath delay commutator (MDC) pipeline architecture, which minimizes the number of nontrivial multiplications. Moreover, the FFT processor was designed using hardware description language (HDL) and synthesized to gate-level circuits using a standard cell library for 65 nm CMOS process. The proposed architecture results in a logic gate count of 219 K with die size of 0.81mm2 and required memory of 18 KB, which can be suitable for compact HGR radar, as it has a smaller area than similar processors.
Cuckoo Search Algorithm Based Feature Selection in Image Retrieval System

Efficiency an d retrieval time are very important issues in any content-based image retrieval system.In this study, an efficient image retrieval system was introduced depending on several features extracted from the database images, namely color moment (Mean, Standard Deviation), GLCM, and DWT( only LL-sub band).To increase the retrieval speed, Cuckoo search algorithm was used to select the important positions that contain full power features from the (LL-sub band).On using the Cuckoo search algorithm, only (50) important positions were chosen out of the total (24576) positions within (LL-sub band).These positions were stored for later use when entering a query image.Thus, the time taken to retrieve images was greatly reduced and this process also increased the efficiency of the system due to the fact that the selected positions gave the lowest distance measures between the query images and the similar images when evaluated using Manhattan distance measure.Two effectual performance measures (precision & recall) were used to calculate the accuracy of the system.The findings proved the system efficiency when compared to other previous works.
Semantic query languages for knowledge-based web services in a construction context

Since the early 2000s, different frameworks were set up to enable web-based collaboration in building projects. Unfortunately, none of these initiatives was granted a long life. Recently, however, the use of web technologies in the building industry has been gaining momentum again, considered some promising technologies for reaching a more interoperable BIM practice. Specifically, this relates to (1) Linked Data and Semantic Web technologies, and (2) cloud-based applications. In order to combine these into a network of interlinked applications and datastores, an agreed-upon mechanism for automatic communication and data retrieval needs to be used. Apart from the W3C standard SPARQL, often considered too high a threshold for developers to implement, there are some recent GraphQL-based solutions that simplify the querying process and its implementation into web services. In this paper, we review two recent open source technologies based on GraphQL, that enable to query Linked Data on the web: GraphQL-LD and HyperGraphQL.
The development of Korean Local Police officers’ Job stress measurement instrument and survey of their Job stress.

본 연구는 한국 지역경찰의 직무스트레스 척도를 개발하는 데에 1차 목적이 있고, 지역경찰 직무 스트레스를 조사하는 데에 2차 목적이 있었다. 연구결과는 다음과 같다. 첫째, 5개 요인 17개 문항으로 구성된 지역 경찰 직무스트레스를 개발 하였으며 비교적 신뢰도가 높고 타당한 것으로 판단되었다. 5개 요인은 조직문 화, 교육 및 훈련, 현장조치, 근무환경, 민원처리로 명명하였다. 둘째, 지역경찰의 직무스트레스 조사 결과 전반적으로 직무스트레스가 다소 높은 편이었다. 5개 요인 중에서 민원처리 요인이 가장 높았고 그 다음은 현장 출동 요인이었다. 셋째, 여성경찰보다 남성 경찰의 직무스트레스가 더 높았다. 넷째, 젊은 경찰보다 연령이 많은 경찰일수록 직무스트레스가 더 높았다. 다섯째, 경위 계급을 가진 경찰이 다른 계급의 경찰에 비하여 직무스트레스가 더 높았다. 여섯째, 순찰 업무나 총괄 업무를 하는 경찰이 관리 업무를 하는 경찰보다 직무스트레스가 더 높았다.The purpose of this study was to develop a job stress scale for local police in Korea and to investigate the job stress of local police. The results of the study are as follows. First, we developed the local police job stress instrument composed of 5 factors, which consist of 17 items in all, and it was judged to be relatively reliable and valid. Five factors were named as organizational culture, education and training, on - the - spot measures, working environment, and complaint handling. Second, as a result of the job stress survey of the local police, the overall job stress was relatively high. Among the five factors, the level of job stress for civil complaint handling factor was the highest followed by on-the-spot measures factor. Third, job stress of male police was higher than female police. Fourth, job stress was higher in police with older age than young police. Fourth, job stress was higher in police with older age than young police. Fifth, the police with the guardian class had higher job stress than the police of the other class. Sixth, police working for patrol or general affairs had higher job stress than police performing administrative work.
Improved direct fitting algorithm for elliptic parameters

Abstract For the ellipse fitting problem often encounter in visual measurement, this paper proposes a method combining algebraic distance fitting method based on least squares and characteristic root method for ellipse fitting. Firstly, the improved hierarchical agglomerative clustering is used to denoise the data. Then the algebraic distance fitting method based on least squares is used to calculate the initial iteration value of the parameters in the characteristic root method. Finally, the Gauss-Newton iteration method is used to solve the elliptic parameters. This algorithm is used to detect the out-of-roundness of the optical fiber and compare the test results with the high-precision optical fiber tester FGM-502. The results prove the validity and accuracy of the ellipse fitting algorithm studied in this paper and show that the algorithm studied in this paper meets the requirements of actual ellipse fitting measurement.