Reviewerly/exHarmony huggingface dataset:
Empirical Evaluation of NoSQL and Relational Database Systems

Aim: To evaluate the performance of Relational and NoSQL databases in terms of execution time and memory consumption during operations involving structured data. Objective: To outline the criteria that decision makers should consider while making a choice of the database most suited to an application. Methods: Extensive experiments were performed on MySQL, MongoDB, Cassandra, Redis using the data for a IMDB movies schema prorated into 4 datasets of 1000, 10000, 25000 and 50000 records. The experiments involved typical database operations of insertion, deletion, update read of records with and without indexing as well as aggregation operations. Databases’ performance has been evaluated by measuring the time taken for operations and computing memory usage. Results: * Redis provides the best performance for write, update and delete operations in terms of time elapsed and memory usage whereas MongoDB gives the worst performance when the size of data increases, due to its locking mechanism. * For the read operations, Redis provides better performance in terms of latency than Cassandra and MongoDB. MySQL shows worst performance due to its relational architecture. On the other hand, MongoDB shows the best performance among all databases in terms of efficient memory usage. * Indexing improves the performance of any database only for covered queries. * Redis and MongoDB give good performance for range based queries and for fetching complete data in terms of elapsed time whereas MySQL gives the worst performance. * MySQL provides better performance for aggregate functions. NoSQL is not suitable for complex queries and aggregate functions. Conclusion: It has been found from the extensive empirical analysis that NoSQL outperforms SQL based systems in terms of basic read and write operations. However, SQL based systems are better if queries on the dataset mainly involves aggregation operations.
Rancangan Aplikasi Sistem Pakar Diagnosa Penyakit Mononukleosis Dengan Metode Naive Bayes

Health is one of the important factors for carrying out daily activities. However, some people do not care about the health of their bodies so that in the end many diseases that are diagnosed late cause the condition at a serious stage. One of the diseases in question is mononucleosis. In general, if the community is exposed to symptoms of mononucleosis, they will go to the nearest hospital or health center to do the examination. But on the other hand they have to sacrifice enough time for that. For this reason, it is necessary to make an application for a disease diagnosis expert system for the community as a means of overcoming these problems. With this design, an expert system of mononucleosis is produced, where this system uses the naive bayes method and the doctor's knowledge into the system. This expert system will produce output / output in the form of the diagnosis of mononucleosis
Microbiological and Physicochemical Assessment of Sediment in Bodo Community, Rivers State, Niger Delta

Crude oil pollution is common place in the Niger Delta despite well known adverse effects on aquatic and terrestrial biodiversities. Triplicate sediment samples were obtained from Bodo community in Ogoni Land, Niger Delta and made into a composite sample. The sample was then evaluated for physicochemical parameters, heavy metals, total petroleum hydrocarbon (TPH), polyaromatic aromatic hydrocarbon (PAH), total heterotrophic bacteria (THBC), and fungi (THFC) using standards methodologies. Concentration profile of heavy metals was iron (Fe) &gt; chromium (Cr) &gt; zinc (Zn) &gt; nickel (Ni) &gt; vanadium (V) in decreasing order. Furthermore, the concentrations of total nitrogen, total phosphorus, nitrate, sulphate were 884.53, 12.32, 34.45, and 26.76 mg/kg, respectively. TPH and PAH concentrations were 30,797 and 52.12 mg/kg, respectively. Nitrate, iron, chromium, nickel, TPH, and PAH all failed to meet regulatory standards. TPH failed to meet Environmental Guidelines and Standards for the Petroleum Industry in Nigeria (EGASPIN) target and intervention values of 50 and 5,000 mg/kg, respectively. Total heterotrophic bacteria and fungi counts were observed to decrease with days of incubation in crude oil. The findings in the study reveal worrisome levels of TPH, PAH, iron, chromium, and nickel, and impact on microbial diversity. Thus, there is a need for periodic monitoring of sediments and water bodies in the Niger Delta.
Self-tunable DBMS Replication with Reinforcement Learning

Fault-tolerance is a core feature in distributed database systems, particularly the ones deployed in cloud environments. The dependability of these systems often relies in middleware components that abstract the DBMS logic from the replication itself. The highly configurable nature of these systems makes their throughput very dependent on the correct tuning for a given workload. Given the high complexity involved, machine learning techniques are often considered to guide the tuning process and decompose the relations established between tuning variables. This paper presents a machine learning mechanism based on reinforcement learning that attaches to a hybrid replication middleware connected to a DBMS to dynamically live-tune the configuration of the middleware according to the workload being processed. Along with the vision for the system, we present a study conducted over a prototype of the self-tuned replication middleware, showcasing the achieved performance improvements and showing that we were able to achieve an improvement of 370.99% on some of the considered metrics.
Database Framework for Nigerian Prison Service, Adamawa State, Command

One of the major challenges facing prisons service especially in the developing countries like Nigeria is how to accurately and efficiently analyze the growing volume of prison inmate data.Nigerian Paramilitaries particularly the Nigerian Prison Service (NPS) Adamawa State command keep volumes of inmate data and information.Despite the enormously volume of data which is on the increase, the recordkeeping process remains manual; this does not assure proper safe keeping of inmate records.This study designed a database framework for the NPS Adamawa State command.The study analyzed the existing system of recordkeeping adopted by NPS which is the manual method of record keeping; developed a prototype database model; and designed a web application that would interact with the database.Before the main design, a comprehensive analysis of the existing system was carried out.16 staff were interviewed for the exercise and the result showed the need for Nigerian Prison Service (NPS) Adamawa State command to have such robust database framework for accurate and efficient tracking of inmate data.The system was designed using Microsoft SQL server, MS Visual Studio.The researcher also used agile software development methodology and accomplished the development by the use of C-sharp, JavaScript, HTML 5 and Bootstrap CSS as tools.The system was tested using a workable prototype, and major recommendations were made.The researcher believes such a database framework should be deployed to Nigerian Prison Service (NPS) Adamawa State Command for full implementation.Findings of this work suggest that similar paramilitaries like the Nigerian Prison Services (NPS) should also incorporate a centralized database system into their process.Though further research needs to be conducted regarding the introduction of bio-metric fingerprinting as a means of tracking prison inmates in such organizations; this work is of the opinion that data warehousing of all prison data for the Nigerian Prison Service (NPS) as a whole is a necessary/vital way forward.
IMPOLITENESS STRATEGIES USED BY GOVERNOR CANDIDATES OF DKI JAKARTA IN GOVERNOR ELECTION DEBATE 2017

This study aimed at exploring the impoliteness strategies in governor election debate 2017. The objectives of the study were to describe, to explain how types of impoliteness strategies used and to expose the reasons. This research applied descriptive qualitative method. The data were the utterances of the governor candidates in two different debate sessions which were analyzed by using Culpeper Impoliteness Theory. The findings revealed that there were three out of five impoliteness strategies found in both debates, namely bald on record impoliteness, positive impoliteness and negative impoliteness. The governor candidates used the bald on record in three realizations, positive impoliteness in seven realizations and negative impoliteness in three realizations. There are some reasons of using the impoliteness strategies, namely to vent negative feelings, to mock others, to show disagreement, to show power, and to clarify something. However, the main reason to use the impoliteness strategies was to show power. Moreover, it is also revealed that both two different types of impoliteness strategies and two different realizations were used at the same moment.Keywords: election debate, governor candidates, impoliteness strategies
Patient Monitoring System using Beacon

In the smart moving world everything becomes easy by using the advanced technology in the smartphone.This paper is about monitoring the patient using beacon through the android developed application.Beacon is a device which can be scanned through the smartphone using BLE (Bluetooth low energy). By using beacon, the patient location can be tracked inside the hospital for visitors and the staff can monitor the humidity and temperature of the patient. In addition pulse rate can be checked using the raspberry pi device. The patient records are maintained in the cloud linking with the application, so the doctors can easily manage the patient records. The health status can be tracked and changed through the application. Doctors can modify the patient records and track their health status with the cloud database. The location will be more accurate than GPS (Global Positioning System), so the location can be viewed from anywhere by the doctors or visitors. In real time beacon scanning is restricted to a shorter range to provide more battery life. Beacon is more secure than the GPS, so patient location can be tracked easily and accurately
Stroke controllable style transfer based on dilated convolutions

Transferring a photo to a stylised image with beautiful texture has become one of the most popular topics in computer vision and the application of image processing. Controlling the stroke size of the texture is one of the challenging problems in this task. Recent representative methods for such problem introduce a pyramid model to regulate receptive fields in the network. Meanwhile, dilated convolutions are proved to be a very efficient way to adjust receptive fields without losing resolution. By combining the advantages of both approaches and making special optimisation for VGG19 model for style transfer tasks, the authors propose to exploit dilated convolutions to extract texture information endowing the network with stroke controllable. Several sets of contrast experiments were conducted and results show that their algorithm can generate more attractive stylisation images and control stroke size flexibly. It demonstrates the superiority of applying dilated convolutions as a texture extraction method for maintaining more texture information and controlling stroke size.
Diagnosa Penyakit Kulit Menggunakan Case Based-Reasoning dan Self Organizing Maps

This study aims to compare the results of the accuracy and speed of the system in diagnosing skin diseases using the case based reasoning (CBR) method with the indexing method and without using indexing. Self-organizing maps (SOM) are used as an indexing method and the process of finding similarity values uses the nearest neighbor method. Testing is done with two scenarios. The first scenario uses CBR without indexing self-organizing maps, the second scenario uses CBR with indexing self-organizing maps. The accuracy of the diagnosis of skin diseases at a threshold ≥80 for CBR without indexing self-organizing maps is 93.46% with an average retrieve time of 0.469 seconds while CBR testing using SOM indexing is 92.52% with an average retrieve time of 0.155 seconds. The results of comparison of CBR methods without using show higher results than using SOM indexing, but the process of retrieving CBR using SOM is faster than not using indexing
How to get the most from your word processor

Each "Communication Corner" essay is self-contained; however, they build on each other. For best results, before reading this essay and doing the exercise, go to the first essay "How an Ugly Duckling Became a Swan," then read each succeeding essay. The personal computer has revolutionized how we work, and that's all because of software development. One of the most important of which is word processing. Since the 1970s word processing has created efficiencies in writing and editing. This article explains how word processors can make you a better thinker.
Collision Avoidance Method for End Effectors of Industrial Robots with Overlapping Workspaces

This paper introduces a method of collision avoidance for end effectors of industrial robots with overlapping workspaces. This method allows for the collision-free movement of end effectors without information about obstacles in the workspaces of the robots and the use of additional sensors. This is provided by analyzing movement programs. During the analysis, the groups of motion program points will be obtained, in which end effectors are located closer than a set distance. Then, during the execution of the programs, end effector locations are controlled in selected groups of points to prevent collisions. The simulation in Fanuc Roboguide environment confirmed the effectiveness of the developed method.
The Role of Entrepreneurship in Economic Growth: The Picture According to Literature

In recent years the theoretical and empirical link between entrepreneurship and economic growth has received massive attention from economists, sociologists, psychologists and many other professionals.Generally, entrepreneurial activity is assumed to be an essential aspect of innovation and competition, it leads to job creation, employment generation and most importantly economic growth and development.This paper investigates the role of entrepreneurship in economic growth, placing emphasis on existing growth theories.In addition to classical and neoclassical growth theories, the article discusses endogenous growth theories.As we will see, entrepreneurship does not appear explicitly in them and can only be discovered implicitly in some of them.The study also looks at some of the theories that try to fill this gap in the literature.The motive of the paper is a simple and straightforward one; to analyse already existing growth theories and further using these theories to understand the role of entrepreneurship in economic growth and development.
Better Parameter-Free Stochastic Optimization with ODE Updates for Coin-Betting

Parameter-free stochastic gradient descent (PFSGD) algorithms do not require setting learning rates while achieving optimal theoretical performance. In practical applications, however, there remains an empirical gap between tuned stochastic gradient descent (SGD) and PFSGD. In this paper, we close the empirical gap with a new parameter-free algorithm based on continuous-time Coin-Betting on truncated models. The new update is derived through the solution of an Ordinary Differential Equation (ODE) and solved in a closed form. We show empirically that this new parameter-free algorithm outperforms algorithms with the ``best default'' learning rates and almost matches the performance of finely tuned baselines without anything to tune.
Face sketch recognition using principal component analysis for forensics application

Recognition of human faces in forensics applications can be identified through the Sketch recognition method by matching sketches and photos. The system gives five criminal candidates who have similarities to the sketch given. This study aims to perform facial recognition on photographs and sketches using Principal Component Analysis (PCA) as feature extraction and Euclidean distance as a calculation of the distance of test images to training images. The PCA method was used to recognize facial images from pencil sketch drawings. The system dataset is in the form of photos and sketches in the CUHK Face Sketch database consists of 93 photos and 93 sketches, and personal documentation consists of five photos and five sketches. The sketch matching application to training data produces an accuracy of 76.14 %, precision of 91.04 %, and recall of 80.26 %, while testing with sketch modifications produces accuracy and recall of 95 % and precision of 100 %.
Expression of Concern: Application of extreme learning machine for prediction of aqueous solubility of carbon dioxide

The Editors-in-Chief of Environmental Earth Sciences are issuing an editorial expression of concern to alert readers that this article [1] shows evidence of substantial text overlap (most notably with the article cited [2]) and authorship manipulation. None of the authors responded to correspondence about this editorial expression of concern.
ANALISIS AIR MINERAL TER HADAP KESEHATANDIHUBUNGKAN DENGAN UU KESEHATAN

Water is one of the basic human needs, especially drinking water. But the availability of eligible drinking water is increasingly difficult to meet demand, even the water absorption areas that have been converted into human settlements and industrial wastes that polluting rivers, make it more difficult for people to get qualified water to drink.Excessive exploitation of groundwater sources that do not consider the carrying capacity of the environment and unbalanced environmental conservation efforts will affect water quality. Besides, the lack of awareness of various parties to dispose of waste will lead to increased water pollution. Experiment research is needed to determine the properties of water so that it can be identifying characteristic of the water is polluted or not.Keywords: water, drinking water, health
Tone Classification Matches Kodàly Handsign with the K-Nearest Neighbor Method at Leap Motion Controller

&lt;p&gt;Hands can produce a variety of poses in which each pose can have a meaning or purpose that can be used as a form of communication determined according to a general agreement or who communicate. Hand pose can be used as human interaction with the computer is faster, intuitive, and in line with the natural function of the human body called Handsign. One of them is Kodàly Handsign, made by a Hungarian composer named Zoltán Kodály, which is a concept in music education in Hungary. This hand sign is used in interactive angklung performances in determining the tone that will be played by the K-Nearest Neighbor (KNN) algorithm classification process based on hand poses. This classification process is performed on the extracted data from Leap Motion Controller, which takes Pitch, Roll, and Yaw values based on basic aircraft principle. The results of the research were conducted five times with the value of k periodically 1,3,5,7,9 with test data consisting pose of 874 Do', 702 Si, 913 La, 612 Sol, 661 Fa, 526 Mi, 891 Re, and 1004 Do punctuation on 21099 training data. The test results can recognize hand poses with the optimal k value k=1 with an accuracy level of 94.87%.&lt;/p&gt;
Word Familiarity Rate and Register Type Estimation Using a Bayesian Linear Mixed Model

This paper presents research on word familiarity rate estimation using the 'Word List by Semantic Principles'.We collected rating information on 96,557 words in the 'Word List by Semantic Principles' via Yahoo!crowdsourcing.We asked 3,392 subject participants to use their introspection to rate the familiarity and register information of words based on the five perspectives of 'KNOW', 'WRITE', 'READ', 'SPEAK', and 'LISTEN', and each word was rated by at least 16 subject participants.We used Bayesian linear mixed models to estimate the word familiarity rates.We also explored the ratings with the semantic labels used in the 'Word List by Semantic Principles'.
Degradative Ability of Silver Particles Synthesized by Gram-negative Bacteria of Some Crops Rhizosphere on Crude Oil Polluted Soil

Aim: To degrade the crude oil polluted soil with silver particles synthesized by some Gram negative rhizosphere bacteria of cocoa, orange and timber obtained from Idanre, Ondo State, Nigeria.&#x0D; Place and Duration of Study: Soil samples were obtained from Idanre, Ondo State while crude oil polluted soil samples were obtained from Zion town in Ese- Odo at Ilaje, Ondo State, between June and September 2018. Also, Bonnylight Crude oil was collected from Warri in Nigeria. This research work was carried out at the Department of Microbiology Laboratory, Federal University of Technology, Akure.&#x0D; Methodology: Soil samples (rhizosphere) were collected in sterile polythene bags and tightly packed and transported for analysis. The types and loads of bacteria present in the soil samples were determined. Identification and characterization of various bacterial isolates were based on Gram staining techniques and different biochemical tests. The physicochemical properties of the crude oil polluted soil were determined. The microbial biomass and the synthesis of silver particles were carried out while the bioremediation of the crude oil polluted soil with the silver particles which were performed in triplicate. Also, bioremediation of crude oil with the bacterial isolates were performed in triplicate. Five millilitres (5 ml) of silver particles produced was inoculated into 50 g of sterilized crude oil polluted soil in a plastic container with 5ml of basal medium and 3 ml of the harvested cells of the isolates was inoculated into 10 ml of the basal medium with 30ml of crude oil in a conical flask. The unsterilized soil without inoculum and silver particles were served as control, also crude oil without inoculum and silver nanoparticles were served as a control.&#x0D; Results: Citrobacter freundii, Yersinia pestis, Edwardsiella tarda, were isolated from rhizosphere of cocoa. Serratia marcescens, Providencia stuatii were isolated from rhizosphere of orange while Enterobacter agglutinate, Moellerella wisconsis were isolated from rhizosphere of timber. The silver particles bioremediation on polluted soil ranges were recorded within 5 days interval for 30 days. It was deduced that Enterobacter sp appeared to be the fastest on polluted soil followed by Citrobacter sp, Providencia sp, Serratia sp and Yersinia sp.&#x0D; Conclusion: Findings from this study revealed the effects of rhizosphere Gram negative bacteria in cleaning up crude oil polluted soil environment and the usefulness of silver particles in remediating hydrocarbon polluted soil.
Autonomous vehicles and in-vehicle data in the context of motor insurance

This paper provides an initial background for further research on how to achieve balance of providing in-vehicle data for the purposes of motor insurance of autonomous vehicles while protecting privacy of individuals at the level presumed by the European legislation. In order to do so, the paper firstly identifies legal challenges in the area of insurance with regard to intelligent technologies. Then the paper clarifies the rationale behind providing in-vehicle data to insurance companies. Next, in order to identify values and principles promoted by the EU with regard to intelligent technologies, the paper provides an overview and a brief summary of the relevant EU policy documents related to access to data, liability and insurance with regard to operation of autonomous vehicles. Lastly, the paper identifies related EU legislation that has a certain impact on provision of in-vehicle data to insurance companies.