Reviewerly/exHarmony huggingface dataset:
Evaluating Plasmodium misdiagnosis using microscopy compared with nested polymerase chain reaction technique in Rivers State, Nigeria

Background: The accurate diagnosis of etiologic agents of diseases including Plasmodium species is a major challenge to effective control programs in sub-Saharan Africa. Methods & Materials: A cross-sectional study to evaluate misdiagnosis of Plasmodium species using microscopy compared with nested polymerase chain reaction (PCR) technique using 2000 randomly selected consenting study participants (age and sex were noted) attending tertiary hospitals in Rivers State was conducted. Blood samples were collected intravenously and examined for Plasmodium species using microscopy and nested PCR technique. Data generated were analyzed statistically using analysis of variance (ANOVA) and chi-square test with a P< 0.05 considered significant. Results: The only species of Plasmodium observed in this study was P. falciparum and the overall prevalence in the study was 37.65% and 34.0% for microscopy and PCR respectively (P > 0.05). Microscopy had a 3.5% variation and misdiagnosis of 5.5% in determining the prevalence of P. falciparum when compared with PCR. P. falciparum misdiagnosis was 6.6%, 4.8%, 3.2%, 7.3% and 6.7% for age groups 0–10, 11–20, 21–30, 31–40 and >40 respectively while males and females had 6.9% and 4.5% respectively (P > 0.05). Microscopy had sensitivity, specificity and diagnostic accuracy of 95.8%, 94.3% and 94.9% respectively. Conclusion: Microscopy still remains the gold standard for Plasmodium species diagnosis and suspected malaria cases should be confirmed with an efficient laboratory diagnosis before treatment to prevent misdiagnosis or antimalarial drug resistance.
Improvement of Batik Liquid Waste Quality with IPAL Mini Technology: Case on Flower Tourism Sidomulyo Village in Batu, Indonesia

Sidomulyo Village, a flower tourist village, in Batu city is one tourist destination in East Java Province based on local wisdom as an icon of Agro-industrial and Agro-tourism in the development of regional tourism. The local products from Sidomulyo Tourism Village include ornamental plants, cut flowers and batik. Sidomulyo Batik UKM is a batik producer with a capacity of 20 sheets per month @ 2.25 m2 and uses manual coloring technology. So far, UKM Batik Sidomulyo has been doing the coloring process in partnership with UKM Batik in Banyuwangi and Trenggalek Regencies due to technological limitations in the processing of batik liquid waste which still contains hazardous and toxic materials so if no action is taken it can damage the ecosystem. One of the strategic solutions is the technology transfer of the mini Wastewater Treatment Plant (WWTP) which utilizes biological waste treatment technology by utilizing bacteria and facilities that are Proven Technology. The mini WWTP installation uses 3 processing rooms including (1) separation of wax content from liquid waste, stirring with coagulant treatment to separate liquid waste from B3 waste and (3) purification of liquid waste by treating biofilter media and anaerobic bacteria. The levels of BOD and COD of the waste will be measured before and after the use of the mini WWTP so that it will be environmentally friendly without reducing the quality of batik as a support for souvenir products typical of Sidomulyo Tourism Village.
End-to-end Quantized Training via Log-Barrier Extensions

Quantization of neural network parameters and activations has emerged as a successful approach to reducing the model size and inference time on hardware that sup-ports native low-precision arithmetic. Fully quantized training would facilitate further computational speed-ups as well as enable model training on embedded devices, a feature that would alleviate privacy concerns resulting from the transfer of sensitive data and models that is necessitated by off-device training. Existing approaches to quantization-aware training (QAT) perform “fake” quantization in the forward pass in order to learn model parameters that will perform well when quantized, but rely on higher precision variables to avoid overflow in large matrix multiplications, which is unsuitable for training on fully low-precision (e.g. 8-bit)hardware. To enable fully end-to-end quantized training, we propose Log BarrierTail-bounded Quantization (LogBTQ). LogBTQ introduces a loss term, inspired by the log-barrier for constrained optimization, that enforces soft constraints on the range of values that model parameters can take on. By constraining and sparsifying model parameters, activations and inputs, our approach eliminates over-flow in practice, allowing for fully quantized 8-bit training of deep neural network models. We show that models trained using our approach achieve results competitive with state-of-the-art full-precision networks on the MNIST, CIFAR-10 andImageNet classification benchmarks.
Preventing Crime Using Advanced Artificial Intelligence Techniques

Crime is increasing significantly from day to day. Every crime is associated with a certain pattern. The modern AI techniques can be implemented in crime scenarios to obtain valuable insights. In contrast to the existing works on crime analysis, we used the latest and much more efficient algorithms to handle crime. Our research work is segregated into three independent modules—prevention, detection and investigation. Prevention phase uses AI strategies to predict regions with high probability of crime occurrence in specified time and preventing crime from happening. Detection phase uses Faster RCNN to detect the kind of crime happening in an area through a security camera and alerting the police for instant response. If crime happens, AI Investigation can predict criminals through clues left in the crime spot. Our work also classifies police complaints. Criminal complaints registered by victims are automatically classified as an appropriate type such as robbery or murder. Our work achieved significant performance compared with earlier works. For prevention stage, SAN FRANCISCO crime dataset is considered. For detection stage, crime images dataset is constructed and annotated by extracting frames from UCF crime dataset (1900 videos, 128 hours of videos). Text complaints are manually constructed.
Bursting the Bitcoin Bubble: Assessing the Fundamental Value and Social Costs of Bitcoin

This paper develops a microeconomic model of bitcoin production to analyze the economic effects of the Bitcoin protocol. I view the bitcoin as a tradable commodity that is produced by miners and whose supply is managed by the protocol. The findings show that bitcoin’s volatile price path and inefficiency are related, and that both are a consequence of the protocol’s system of supply management. I characterize the fundamental value of a bitcoin and demonstrate that the return on bitcoin appreciates proportionally to the rate of increase in the level of difficulty. In the model, where the price of a bitcoin is based on marginal production costs, successive positive demand shocks result in a rapidly increasing price path that may be mistaken for a bubble. The generalized supremum augmented Dickey-Fuller (GSADF) test is used to demonstrate that the model is able to account for the explosive behavior in the bitcoin price path, providing strong evidence that bitcoin is not a bubble. I also show that the difficulty adjustment mechanism results in social welfare losses from 17 March 2014 to 13 January 2019 of $323.8 million, which is about 9.3% of the miners’ total electricity costs during this time period.
Research on Voltage Quality Model of Distribution Network Based on Convolution Neural Optimization

Abstract In order to realize the optimization design of distribution network voltage quality monitoring model based on convolution neural optimization, this paper adopts the method of big data fusion scheduling and statistical information mining to monitor the voltage quality of distribution network. Firstly, the prior data of distribution network voltage quality is analyzed, and then the evaluation and decision of distribution network voltage quality are carried out according to the analysis results of distribution network voltage quality prior data analysis and fuzzy parameter fusion method is used to model the voltage quality monitoring of distribution network to realize the optimization of quality monitoring. The experimental results show that the confidence level of this method is high and the error is low.
Truthful Self-Play

We present a general framework for evolutionary learning to emergent unbiased state representation without any supervision. Evolutionary frameworks such as self-play converge to bad local optima in case of multi-agent reinforcement learning in non-cooperative partially observable environments with communication due to information asymmetry. Our proposed framework is a simple modification of self-play inspired by mechanism design, also known as {\em reverse game theory}, to elicit truthful signals and make the agents cooperative. The key idea is to add imaginary rewards using the peer prediction method, i.e., a mechanism for evaluating the validity of information exchanged between agents in a decentralized environment. Numerical experiments with predator prey, traffic junction and StarCraft tasks demonstrate that the state-of-the-art performance of our framework.
APLIKASI REPORTING IMAGE DENGAN METODE LOCATION BASED SERVICES BERBASIS ANDROID

Android is a software platform for mobile devices supported by Google OS. Android uses a modified version of the Linux kernel that is able to be distributed openly (open source). This makes it possible for developers to manage, modify and create their own applications. Mapping application is an application regarding geography that has been developed. This report system application is used to provide reports or information in the form of an image along with the location of the selected object. This encourages the writer to make an Android-based imagereporting application. This ireporting application is made using Android Studio tools that have SDK and JDK installed and then uses a system from Google Cloud to correlate the database to the platform. While the programming languages used are Java, XML, and SQL Lite. The research method used is the SDLC (Software Development Life Cycle) which consists of an identification phase, an analysis phase, a design phase, a trial phase. This application will get information and visualization of objects in the form of maps that can be used as a reference for Android mobile device users in making decisions, especially in giving reports or information objectively and efficiently. In addition, it can find the direction radius at the initial location to the final location, and there is also a favorite menu for storing complex and correct reports, other supporting menus.
Developing Test System in Academic Nursing School

A written test has various goals. The test is a communication tool between the teacher, the course and the student. The test results may indicate lacks in teaching and the need to improve the core or teaching methods. The test has a structure called the test map.
FOREST: Stata module to visualize results from multiple regressions on a single independent variable

visualizes results from multiple regressions on a single independent variable. The resulting forest chart shows the effect of a single treatment variable of interest on a set of independent variables. It can display raw coefficients, standardized effect sizes (Cohen's d), or odds ratios (from logistic regressions). It can also make Bonferroni corrections to the confidence intervals for multiple comparisons.
PAN-Analys av IKEA TRÅDFRI. : En fördjupning av säkerhetsrisker kopplade till OTA-uppdateringar inom IKEA TRÅDFRI:s PAN.

Purpose – The purpose of this study is to elaborate security risks with OTA updates within TRADFRI:s PAN. To ensure that today’s IoT devices maintains a high and robust standard to protect end-user ...
INTEROPERABILITAS APLIKASI BERBASIS WEB SERVICE

Today, the need to fill information as data is increasing rapidly. At the past, fill many forms in the format of papers. But now, the forms are changing to paperless format. This can be achieve by making an application capable of data input, edit the data, and post the data across all computing/technological platform available these days. The need for this application can communicate with each other. Related to this, there are many things needed, to achieve unlimited data transfer in various applications. One of the most important aspect that can make seamless communication/integration across applications is web service.  Keywords: REST API, SOAP , Semantic
Data Mining Sistem Tata Letak Material di PT Batam Cyclect

PT BATAM CYCLECT or better known as Cyclect is a company engaged in the electrical sector in the shipyard. PT BATAM CYCLECT in its material warehouse lacks good material arrangement procedures in the warehouse which results in the warehouse looking cramped and less orderly. So a system is created that helps in processing material layout data based on the type of item, such as material consumables, electric materials, welding materials, electric tools, chemical materials and many other types. Data Mining is a solution in developing a business or a way to use data for future prediction processes. The method used is association rules to find associative rules that are connected with one item and another. The Apriori Algorithm is an algorithm used to generate association rules and is well-known in determining high frequency patterns. The goal is to make it easier for the storeman in the waiter and shorten the time when searching for goods simultaneously with the material layout system. The Apriopri algorithm takes advantage of this process to reduce or narrow the search space for itemset candidate frequency. To test the accuracy of the Apriori algorithm using the Rapid Miner software. The results of the research carried out obtained 10 association rules with a minimum support value of 5% and 50% confidence with 3-itemset results, namely if you order Marking Tape and markers you will order PVC Insulation Tape with a Support value of 15% and a confidence value of 89%.
Penerapan Metode Selft Organizing Maps (SOM) Dalam Rekomendasi Jurusan Calon Mahasiswa Baru (Studi Kasus : Universitas Imelda Medan)

Admission of new students is an administrative process for prospective students in educational institutions. This process is usually carried out every year. Imelda University Medan is one of the universities that still uses manual system procedures in selecting the right majors for prospective new students. This study aims to design a data mining system application for recommendations for new student majors at Imelda University Medan, using the Selft Organizing Maps (SOM) method to make it easier for prospective new students in the process of selecting the right department. For application design, the Visual Basic 2008 programming language is used, this system is made flexible so that if at any time the criteria used can be adjusted according to needs. The results of this study indicate that the SOM method can produce recommendations for the right majors for prospective students at the University of Imelda Medan. . Thus the system is expected to be able to assist in the activities of department recommendations for prospective new students at the University of Imelda Medan. Keywords : New Students, Data mining, Selft Organizing Maps (SOM)
Main Features Of Ore Potential And Statistical Metallogenic Assessment Of The Zeravshan-Alay Belt (South Tian-Shan)

This work reflects the geological structure, history of development and ore content of the Zirabulak-Ziaetda and Kuldzhuktau ore-bearing complexes. The types of placement of structures are considered: focal-zonal, belt, nodal and frame-nodal. In the Zeravshan-Alai metallogenic belt, regularities have been established for the distribution of endogenous mineralization of ore regions and provinces. A metallogenic map was compiled using GIS technology using statistical analyzes to identify promising areas
REDESAIN WORKSTATION COPY CENTER PERPUSTAKAAN UNIVERSITAS SURABAYA

Library facilities that can support the activities of the visitors is Copy Center. The current Copy Center is not yet fully utilized by readers. Not all visitors who come to know the existence of the Copy Center service. Currently, the existing Copy Center is not able to organize all the copying support equipment, it causes the space in the Copy Center to look untidy and messy because of the many equipment and personal items of employees who are scattered. Unwittingly, the display of Copy Center can affect and reduce the beauty and comfort of the library space so the need to be redesigned on existing products. The purpose of this research is to design redesign of workstation copy center of University of Surabaya Library that can organize all photocopy support equipment to improve work efficiency without neglecting aesthetic element in product. Research methods used in data search are interviews, research library, and observation of existing products. The results of research conducted in the form of workstations designed in accordance with the workflow, using a design concept that combines futuristic and modern style. There is storage for storing stationery and photocopying equipment so that it can organize all the equipment to look neat. With this workstation, can improve the efficiency of employees working Copy Center.
3D-3D Self-Calibration of Sensors Using Point Cloud Data

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Self-calibration of sensors has become highly essential in the era of self-driving cars. Reducing the sensors’ errors increases the reliability of the decisions made by the autonomous systems. Various methods are currently under investigation but the traditional methods still prevail which maintain a strong dependency on human experts and expensive equipment that consume significant amounts of labor and time. Recently, various calibration techniques proposed for extrinsic calibration for Autonomous Vehicles (AVs) mostly rely on the camera 2D images and depth map to calibrate the 3D LiDAR points. While most methods work with the whole frame, some methods use the objects in the frame to perform the calibration. To the best of our knowledge, majority of these self-calibration methods rely on using actual or falsified ground truth values.&lt;/div&gt;&lt;div class="htmlview paragraph"&gt;We propose a 3D-3D point cloud based continuous self-calibration approach that uses one or many objects identified in the sensor frames to cross-calibrate sensors without any reliance on initial calibration parameters or ground truth values. Considering the fact that multiple sensors have multiple views of the same scene, the common features or objects within the scene can be used to calibrate one sensor node with respect to the other. Our approach relies on point cloud data (PCD) generated from at least two sensors to cross-calibrate the mis-calibrated sensor with respect to the calibrated sensor. In this paper, we demonstrate that we can apply the method either by extracting the essential feature points of the object PCD (i.e., centroids of the objects) or the whole object PCD. Following which we optimize the cost function to obtain the extrinsic calibration parameters. Our method handles the problem of pose correction similar to calibration without any ground truth value from sensors just by using multiple consecutive frames. In comparison to other methods, our method performs calibration with low margins of errors in rotation and translation. This method has been tested on the publicly available KITTI dataset, which is widely used to assess various problems (object detection, segmentation, tracking, depth prediction etc.) related to self-driving cars. The simplicity of the method lets us do on-the-fly calibration of sensors with a high level of accuracy.&lt;/div&gt;&lt;/div&gt;
THE EFFECTIVENESS OF EXPRESSIVE WRITING AND SOCIAL MEDIA AS EMOTIONAL RELEASE

Everyone has problem to solve. Each problem has positive and negative impacts but it makes someone stronger. This research aims to figure out the effectiveness of expressive writing and social media as media to express thought, ideas, and emotion of the users. The arrangement of research is descriptive studies through the examination a number of social media accounts by employing purposive sampling method. Expressive writing is an activity to direct to communication skill through writing for sharing feelings, thoughts, and anything that is wanted by the user without a feeling of being blamed by somebody else. Expressive writing becomes one of curative alternatives to solve traumatic experience and other psychological matters. Expressive writing helps someone to release emotional expression. Expressive writing in the era of technology is not only performed in conventional ways, handwriting but also performed through modern devices. Social media such as facebook, twitter, and path is a product of technology that is popularly used to share problems (expressive writing). This is phenomenology research. It shows that 150 user accounts of facebook, twitter, and path conduct expressive writing to release their emotional expression on problems that they are facing. Based on the research, it is found the impact of social anxiety on the reliance on social media that is significant and positive.
Penerapan Algoritma Gopala-Hemachandra Code2 (GH-2(n)) Pada Kompresi File Audio

Current technological developments are increasingly advanced which also have an impact on communication lines. The development is based on the emergence of the internet, through the internet, many things have been done, one of which is the exchange of information. However, this development creates new problems, namely due to the relatively large size so that it requires storage media to accommodate all the data received. From these problems, a technique was found in order to solve all the problems previously found. The technique is called the compression technique. is the process of converting the original (raw) data into another data stream with a different format that has a smaller size or the process of converting a set of data into coded form in order to save storage space. In this case, what I use in compression is the Gopala-Hemachandra Code 2 (GH-2 (n)) algorithm for compressing audio files. So from this research we will get what percentage of the data before the compression process is carried out with those that have been demcompressed. So that users can also save more storage space without losing information, besides that the time used in the transmission process will be less. Keywords : Compression 1 , Audio Files 2 , Gopala-Hemachandra Code 2 (GH-2 (n))2