Reviewerly/exHarmony huggingface dataset:
Optimization of k value and lag parameter of k-nearest neighbor algorithm on the prediction of hotel occupancy rates

Hotel occupancy rates are the most important factor in hotel business management. Prediction of the rates for the next few months determines the manager's decision to arrange and provide all the needed facilities. This study performs the optimization of lag parameters and k values of the k-Nearest Neighbor algorithm on hotel occupancy history data. Historical data were arranged in the form of supervised training data, with the number of columns per row according to the lag parameter and the number of prediction targets. The kNN algorithm was applied using 10-fold cross-validation and k-value variations from 1-30. The optimal lag was obtained at intervals of 14-17 and the optimal k at intervals of 5-13 to predict occupancy rates of 1, 3, 6, 9, and 12 months later. The obtained k-value does not follow the rule at the square root of the number of sample data.
Literation Skill To Improve Higher-Order Thinking Skills In Elementary School Students

Higher-order thinking skill is closely related to literacy skills. However, data from PIRLS 2011 states that the reading ability of elementary school students in Indonesia is relatively low because it is ranked 42 out of 45 countries. Data from PISA 2018, Indonesia ranked 74 out of 76 countries. Though literacy skill influences mindset. The purpose of this study is to explain: a) the basic concepts of literacy, b) the basic concepts of High Order Thinking Skills, and c) the literacy skill to improve high order thinking skills in elementary school students. The approach used in this study is qualitative. The research method used is content analysis. The data sources are journals and books related to literacy and high order thinking skills. The results of this study are: first, literacy is the ability to interpret information critically and can convey knowledge to others accurately. Second, higher-order thinking skills is the process of thinking students at a higher level of knowledge from various cognitive concepts such as analysis, synthesis, evaluation, and creation. Third, literacy skills improve higher-order thinking. The strategies used by schools include conditioning literacy-friendly physical environments, seeking social and affective situations as literate models of communication and interaction, and striving schools as a literate academic environments.
Implementation of the user-centered design (ucd) method for designing web marketplace of qurban cattle sales in indonesia

This study aims to create a user interface design for the designing web marketplace of qurban cattle sales in East Java, Indonesia. The word qurban referred as the qurban animal slaughtered during the Eid al-Adha, especially cow. The qurban web market can help breeders and customers in the process of selling cattle directly without limited territory. This is because the process of selling qurban cows is still done traditionally by ordering directly by phone and coming directly to the cattle pen for the selection of qurban animals desired by consumers. To deal with these problems, an alternative solution is needed that can create a Web Marketplace interface design that is designed using the User-Centered Design (UCD) method, focusing on the user's primary needs. This method was chosen because it focuses on the user's goals, characteristics, and workflow in the design process. How the system can be understood and used by users is a top priority in this web design and involves users in designing the marketplace web interface. Therefore it is very suitable for designing a website that is simple and easy to use. The design of the web marketplace of qurban cattle sales has four main features which are promotion of qurban cattle, online qurban cattle bookigs (direct purchases or livestock care services), payment confirmation, and qurban cattle contributions for collective purchases or in groups. The results of the System Usability Scale (SUS) test distributed to 30 respondents obtained a value of 79.3 which indicates that the qurban web marketplace design can be accepted by users and can be classified as good design.
Dreaming under Locke’s Shadow

In this article I present an outline of the current issue of Filosofija. Sociologija which attempts to discuss the destiny of Man and of individual women and men in the technological society shaped by technological ways of thinking. Also, more general processes of cultural formation and reformation are analysed in the articles. How is identity understood in technological networks? What is identity’s relation to the brain or brainbased models and to cultural environment and its flux? What is the role of language in these processes and what non-analytical ways of philosophical speaking are there? The articles illustrate the trouble of human’s relation to himself in the technological context as a nagging issue for the current discourse.
Application of Machine Learning Classification to Detect Fraudulent E‑wallet Deposit Notification SMSes

Fraudulent e-wallet deposit notification SMSes designed to steal money and goods from m-banking users have become pervasive in Namibia. Motivated by an observed lack of mobile applications to protect users from such deceptions, this study evaluated the ability of machine learning to detect the fraudulent e-wallet deposit notification SMSes. The naïve Bayes (NB) and support vector machine (SVM) classifiers were trained to classify both ham (desired) SMSes and scam (fraudulent) e-wallet deposit notification SMSes. The performances of the two classifier models were then evaluated. The results revealed that the SVM classifier model could detect the fraudulent SMSes more efficiently than the NB classifier.
Energy Consumption Modeling and Prediction in the Cloud Data Centers

Energy efficiency has turned into an undeniably essential worry in data centers as a result of issues related to energy consumption, including capital costs, working costs, and natural effect.While energy wastage, because of imperfect utilization of facilities and IT hardware, has to a great extent been decreased using best-practice advances, tending to energy loss in IT equipment, still requires the plan and usage of energy-aware resource management frameworks.Various methods aimed to enhance the energy efficiency in data centers have been developed in the field related to the development of resource allocation.In fact, researchers and scientists utilize numerous ways to improve effectiveness for optimized power and performance: scaling virtual machine and server preparing abilities to minimize energy consumption, enhancing resource use through exploiting its heterogeneity and consolidating the workload.To accomplish these objectives, there is multiple proposes models, calculations, algorithms, techniques, and procedures that diminish energy use using virtual machine scaling, virtual machine sizing for CPU and memory, CPU frequency adjustment, and also equipment power control for resource allocation in the server-level.The proposed online performance and power models catch framework conduct while adjusting to changes in the fundamental infrastructure.In this context, we present different formulas for calculating energy consumption in cloud data centers and we propose a simplified and completed deduced formula for energy consumption estimation
Analysis of Pre-service Science Teachers' Digital Literacy Through Workshop of Optimization Microsoft Office Software Usage

The present study was carried out to analyze the digital literacy for pre-service natural science teachers through a workshop on optimizing the use of Microsoft office software. This study explored an experimental method with the one-group pretest-posttest design. The current research adopted 25 students as the pre-service natural science teachers in the Natural Sciences Study Program of the Tarbiyah and Teaching Faculty of the Sultan Syarif Kasim Riau State Islamic University. The data were collected through providing instruments of multiple-choice tests on the pretest and posttest, questionnaire, and interview to measure the improvement of digital literacy. To analyze the data, a technique to calculate the mean score of the normalized gain (N-gain) was performed. The findings disclosed that the mean score of N-gain digital literacy for pre-service natural science teachers was 0.70 with the high category. Based on results obtained in this line of research, it is therefore concluded that there was an improvement in the digital literacy for pre-service natural science teachers with high category through the workshop on optimizing the use of Microsoft Office software.
Assessment of Lagos soils for some persistent organic Pollutants

Contamination of Lagos soils with persistent, bioaccumulative and toxic micropollutants (PBTs) may not only affect the non-target species residing in the soil, but also raises the concern of the possibility of the chemicals finding their way into the Lagoon and other water courses via soil run-off and leaching. In this study, soil samples were collected from three busy areas of Lagos (Apapa, Okobaba and Iddo) and analyzed for Polychlorinated Biphenyls (PCBs), Organochlorine pesticides (OCS), and Polycyclic Aromatic Hydrocarbons (PAHs). Gas Chromatography with Mass Selective Detector (GC/MSD) was used for the analyses. Iddo had the highest percentage organic carbon content of 39.39% with highest total PAHs of 2,706.93 ng/g. The highest total PCBs of 23.63 ng/g was found at Apapa 3 which was one of the three sampling points in Apapa. PCB 74 was the onlyPCB found in all the soil samples and ranged between 3.55 ng/g and 23.64 ng/g at Apapa 1 and Apapa 2 respectively. High concentrations of the following organic compounds were also obtained at the following locations- naphthalene (1,625.10 ng/g) at Iddo; dichlorodiphenyldichloroethylene (p,p'DDE ), (117.98 ng/g) at Okobaba, and PCB 74 (23.63 ng/g) at Apapa 1. The results obtained showed that the higher the municipal activity, the higher the percentage organic carbon content.&#x0D; Key words: Bioaccumulative and toxic micropollutants, Gas chromatography/Mass selective detector, Persistent organic carbon, Soil organic pollutants
Community microtoponymy: Proposals to read an oral corpus from Marene (Piedmont, Italy)

Investigating an oral microtoponymy set from a socio-onomastic point of view presents us with the challenge of how to read the variation these data disclose.Starting from the toponyms collected during field research in Marene (Piedmont, Italy), this paper intends to outline an analysis method that allows us to reconstruct the toponym formation process and observe the nodes from which the different paths branch out, causing this variation.The scheme that we follow here takes as its basis the proper name theory of the Italian linguist A. Prosdocimi, that involves splitting the name formation process into three levels: physical, cultural and linguistic "individuation".Some specific examples taken from the corpus collected in Marene -places mentioned just by one informant; places named by most of the informants and their cultural and linguistic interpretation -are presented in order to 16 SARA RACCA show the functionality and versatility of this scheme in analysing variation within a community's toponymic repertoire.
How to Design a Research Data Management Platform? Technical, Organizational and Individual Perspectives and Their Relations

Academic research generates increasing amounts of data that needs to be shared between collaborators, made publicly accessible and/or archived for the long term, all while respecting applicable regulations on topics such as data protection. Good research data management (RDM) is challenging, and despite the growing number of available technical solutions, researchers have been reluctant to use them. We interviewed 64 academic researchers to elicit requirements and explore attitudes towards RDM. Although many funding bodies insist that each project follow published RDM guidelines, only about half the participants considered RDM relevant for their own work, and only one in three reported that they already practiced RDM or were planning to do so. The qualitative analysis of the transcripts revealed three broad categories of requirements for RDM platforms, namely technical, organizational and individual ones. We discuss how these requirements are related to, and sometimes contradict each other.
Survey and Analysis for Achieving the Security of Data in Cloud

Cloud computing is on-demand access to computer system resources through the internet.Among various services provided by the cloud, most prominent is the cloud for storage.Because cloud services are present over the internet, which invites some trust issues among customers regarding integrity and confidentiality about the data, it is the challenge for the cloud to assure customers that their data is safe and can be retrieved whenever they want.This paper presents a survey of various schemes that applied to achieve confidentiality and integrity in the cloud system.Generally, encryption/decryption schemes and hashing techniques are used to obtain privacy and integrity, respectively.This paper also gives a comparative study of some encryption/decryption schemes as well as some hashing schemes.
Implementation And Development Of E-Voting System For Election Of Student Council Chairperson Of SMP Negeri 10 PEKANBARU

Intra-School Student Organization is an organization that is at the school level in Indonesia, starting with junior high schools and senior high schools. The student council is managed and managed by students who are chosen to be student council. Usually this organization has a mentor from the teacher chosen by the school. Student council members are all students who are in one school where the student council is located. In an effort to elect the student council president, the researchers created a web-based information system in selecting the student council president. E-voting is an electoral system where data is recorded, stored and processed in the form of digital information. In the election of the chairman is always a problem in carrying out his election, such as having to prepare space, paper, and others. And after that it takes time in completing the vote count, it also requires a lot of people or committees in carrying out the chairman's election, lack of transparency in vote counting, there are still errors in vote counting.
Research on Navigation and Location System of Inspection Robot for Urban Utility Tunnel

The inspection robot is suitable for the automatic safety inspection of utility tunnel with multiple hazards and complex spatial structure. Based on the principle of three-point location, this paper proposes a location method which combines two-dimensional lidar and reflective stickers. By reading all reflective stickers in the utility tunnel environment, the current position of the robot can be determined in real time, and it can be mapped in the robot map of the utility tunnel. The effectiveness of the method is verified by experiments, and the problem of automatic navigation of the robot in the utility tunnel is well solved. Besides, the robot adopts Christie’s crawler type. Through the design of terrain adaptability and vertical obstacle experiment, it is verified that the robot has good motion performance and can adapt to complex terrain conditions in the utility tunnel.
Machine Learning Berbasis Desktop dan Web dengan Metode Jaringan Syaraf Tiruan Untuk Sistem Pendukung Keputusan

&#x0D; &#x0D; &#x0D; &#x0D; Machine learning application demand is increased massively because it provides good ability in the classification that is needed by decision makers. Machine learning application uses a programming language with strong characteristics in computing, usually the back-end programming language, such as Matlab, Python, R, etc. The obstacle faced by the decision support system developer is preparing an interface that makes it easy for the user. Some back-end programming languages have provided a good interface. Therefore, in this study they were compared by taking the case of a scholarship decision support system. The language used is Python with two web-based applications including Google Interactive Notebook and Flask framework. Both devices have their respective advantages and are worthy of being the first choice in the design of decision support systems.Python has advantages with framework Flask support and Matlab is easy in interface design.&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D;
Finite quantum theory of fields and strings. 1. Consistent quantization in the Stueckelberg-Feynman treatment

In standard quantum field theory, where free quanta have only positive energy, the antiparticle operators were introduced "manually" and this led to the diverging zero-point energy, which meant the inconsistency of the theory.In the Stueckelberg-Feynman (SF) treatment the positive-energy antiparticles are described as the negative energy particles going backward in time and here some Lagrangians do not lead to the zero-point energy.But earlier it was believed that this treatment leads to a negative norm of states and therefore is also inconsistent.In the paper a consecutive method of canonical quantization of fields and strings in the SF treatment is formulated, where a correct choice of the action function makes the norm of states positive and the choice of a minimal Lagrangian makes it free from the zero-point energy.The symmetric chronological product of operators is introduced, turning into ordinary chronological at forward and antichronological at backward in time evolution.This leads to the causal SF propagator and to the standard diagram technique for interacting fields.String theories containing the zero-point energy of modes are inconsistent, since regularization is impossible at Planck distances due to the inevitable presence of gravity.At quantization of strings in SF treatment, there are models without zero-point energy, which are therefore finite and only consistent, but they do not have a conformal anomaly and critical dimension.The effects attributed to the zero-point energy (Lamb shift, Casimir effect) are explained across the contributions of the fields of real sources and confirm the lack of zero-point vacuum energy.This partly solves the cosmological constant problem.From the SF treatment one can turn to the antiparticle picture by means of the charge conjugation or crossing symmetries.The main consequences of the proposed consistent method of quantization of fields and strings are discussed.
What Can We Learn from Almost a Decade of Food Tweets

We present the Latvian Twitter Eater Corpus - a set of tweets in the narrow domain related to food, drinks, eating and drinking. The corpus has been collected over time-span of over 8 years and includes over 2 million tweets entailed with additional useful data. We also separate two sub-corpora of question and answer tweets and sentiment annotated tweets. We analyse the contents of the corpus and demonstrate use-cases for the sub-corpora by training domain-specific question-answering and sentiment-analysis models using the data from the corpus.
Efficient and Modularized Training on FPGA for Real-time Applications

Training of deep Convolution Neural Networks (CNNs) requires a tremendous amount of computation and memory and thus, GPUs are widely used to meet the computation demands of these complex training tasks. However, lacking the flexibility to exploit architectural optimizations, GPUs have poor energy efficiency of GPUs and are hard to be deployed on energy-constrained platforms. FPGAs are highly suitable for training, such as real-time learning at the edge, as they provide higher energy efficiency and better flexibility to support algorithmic evolution. This paper first develops a training accelerator on FPGA, with 16-bit fixed-point computing and various training modules. Furthermore, leveraging model segmentation techniques from Progressive Segmented Training, the newly developed FPGA accelerator is applied to online learning, achieving much lower computation cost. We demonstrate the performance of representative CNNs trained for CIFAR-10 on Intel Stratix-10 MX FPGA, evaluating both the conventional training procedure and the online learning algorithm.
Pengaruh Dukungan Orang Tua, Teman Sebaya dan Motivasi Belajar Terhadap Hasil Belajar Siswa Kelas XI IPS SMA PGRI 2 Kota Jambi

The purpose of this study was to determine the effect of parent support, peers and motivation to learn the results of student learning class XI IPS in SMA PGRI 2 Kota Jambi. The population in the study amounted to 61 students. Based on the results of the study, it can be concluded that in taking the learning process of parent support is very necessary for the growth of children in further education, this is due to the desire of children to attend school is not limited to different school environments or new peers but there is a high desire to continue take knowledge that is beneficial to them
A Tool for N-way Analysis of Programming Exercises.

This work has been funded by the Spanish Ministry of Economy and Competitiveness and FEDER Grant TIN2017-88515-C2-1-R.
Object Detection: Optimization of training Data in Genetic Programming

In this modern world where there is very limited time and a lot of health problems are identified for various age groups and proper intake of food is very essential, we are not taking care of our food intake due to proper lack and suggestions of dieticians.Till now peoples seeing dieticians and fitness trainers are belongs to rich sector, not for the common people.Hence we decided to make a good website which gives diet solutions, help and guidance to all age groups through free online on the basis of their health problems, age or the condition or the exercises.And also with an online diet store which helps everyone to get fresh organic food directly in a prepared way as a programme oriented by a good diet support.This is really essential and helpful for many people of this generation as health and diet are key factor and we cannot approach a specialist or get the prescribed food directly in the required time.
Design and Implementation of Educational Application for Directorate of Traffic Safety, Oman

The world always faces multiple risk factors due to an increase in traffic accidents. This leads to the death of many people. Some of them get seriously injured and get permanent disabilities due to the negligence of persons in following traffic safety procedures. The General Directorate of Traffic in the Sultanate of Oman is responsible for regulating traffic in the country by monitoring the movement of traffic in the streets of inside cities and outside to preserve the safety of traffic in the streets of the Sultanate of Oman. This research paper aims to provide a solution in educating Omani residents about teaching driving laws, especially in Oman. The solution will raise awareness in the society with the rules and laws related to traffic safety. In order to justify and support the requirements of this research, the researchers conducted interviews and surveys among the public. The methods of data collection included questionnaires and interviews.&#x0D; The analysis showed that majority of the audience who participated in surveys strongly agreed that such kind of education system for the residents was really essential so that they could learn about the importance of traffic rules and regulations right from their childhood. Finally, the researchers have proposed to develop a mobile app, which would be one of its kind and exclusive in Oman by Royal Oman Police (ROP) – Traffic Safety Unit. The methodology used in the development of this project would be the spiral model. Relevant literature was reviewed in order to study the existing system and also the similar systems which are existing around the world.