Reviewerly/exHarmony huggingface dataset:
RankAxis: Towards a Systematic Combination of Projection and Ranking in Multi-Attribute Data Exploration

Projection and ranking are frequently used analysis techniques in multi-attribute data exploration. Both families of techniques help analysts with tasks such as identifying similarities between observations and determining ordered subgroups, and have shown good performances in multi-attribute data exploration. However, they often exhibit problems such as distorted projection layouts, obscure semantic interpretations, and non-intuitive effects produced by selecting a subset of (weighted) attributes. Moreover, few studies have attempted to combine projection and ranking into the same exploration space to complement each other's strengths and weaknesses. For this reason, we propose <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RankAxis</i> , a visual analytics system that systematically combines projection and ranking to facilitate the mutual interpretation of these two techniques and jointly support multi-attribute data exploration. A real-world case study, expert feedback, and a user study demonstrate the efficacy of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RankAxis</i> .
Intelligent international marketing system and marketing method based on big data

New type of intelligent international marketing system and marketing method. It is the combination of traditional intelligent international marketing system and traditional market research. It can effectively realize the development of global brand strategy in the Internet, mobile phones, social networks and other times. Its main advantage lies in the integration of all aspects related to product promotion; From product promotion (including advertising), sales promotion (including retail), customer service (including aftersales service) to online shopping experience. Smart systems based on big data and international marketing methods are also related to cost reduction.
Preliminary construction of intelligent operation and maintenance system for key equipment of Urban Rail Transit

Diagnosis and intelligence management system of the central equipment of the urban orbit traffic can provide the whole technical support to the construction of the predictive repair system of the vital facilities of the urban orbit traffic and the construction of the power supply repair system. This paper analyzes the demand and construction direction of the intelligent operation system which is an important facility of urban rail traffic. As a result of the analysis, the application of this system showed that the important equipment of the track traffic can guarantee the reliability and safety level of the whole life cycle.
Research and Realization of Online English Education Learning Results in the Era of Big Data

In the development of social economy and scientific and technological innovation, the traditional teaching mode based on school curriculum has been unable to meet the needs of professional talent cultivation in various fields, and the education field has begun to build and promote the network teaching system. From the perspective of long-term development in the field of education, it is the main topic of online education in the era of big data to use data analysis technology to manage the data information of online learning education in China, discover the latent development rules, and provide effective basis for the optimization of teaching and management process of online academic education. Therefore, after understanding the different stages of the development of Online English education in the era of big data, this paper comprehensively predicts the learning results of online English education in the era of big data according to the intelligent English education teaching system and the overall teaching content, thus putting forward effective measures to optimize the English learning level of college students.
Assessment of Network &amp; Processor Virtualization in Cloud Computing

Cloud Computing is an emerging field in applied computer science. Cloud computing depends on virtualization, where a sole physical resource is virtualized into numerous virtual resources. Resources that are being virtualized include physical storage, processing units, volatile memories, network, and further physical resources. Processor and network virtualization offer several advantages like lessening hardware cost, energy consumption, and the human struggle for administration and management of resources. In this article, the primary concentration was on the evaluation and assessment of network virtualization between different cloud computing hypervisors and to contrast their evaluated results. This comparison is based on a few experiments performed on Citrix XenServer, Microsoft Hyper-V, and VMware vSphere hypervisors. XenServer uses Open vSwitch for its network virtualization whereas Hyper-V and vSphere use Microsoft network virtualization and vSphere switch for managing their network virtualization respectively. We have found that virtual networks are further scalable and secure than physical networks. We can assign multiple virtual interfaces or connections to a single virtual machine. In light of various experiments, in which we have compared non-virtualized with virtualized scenarios, for all these above-mentioned hypervisors, we found out that we can use virtual networks with and without VLAN Tags or VLAN Ids. Hyper-V provides further flexibility and options regarding VLAN Tag in comparison with XenServer or vSphere. We have also found that XenServer and vSphere give us extra network throughput in comparison with Hyper-V in terms of TCP and UDP whereas Round Trip Time (RTT) in the virtual network of all hypervisors are high in comparison with the non-virtual environment. Network CPU usage is also measured and found that vSphere and XenServer together consume more CPU during network activity in comparison with Hyper-V. We also found that processor virtualization did not majorly result from the average schedule time in comparison with a non-virtualized machine. We consequently conclude that in general a small reduction in the performance, in the case of virtualization is insignificant as compared with the advantages we get from virtualization when using cloud hypervisors. For the application of virtualization, this work will motivate to set up of data centers using a virtualized environment.
Integration of Healthcare Services of Specialized Healthcare &amp; Medical Education Department, Government of Punjab in Cloud-based System

To know about the emergent technology in the world is cloud computing, which may utilize in the health sector to improve the mechanism for the delivery of healthcare services of Specialized Healthcare &amp; Medical Education Department, Govt. of the Punjab, Lahore, human resources management system, budget and expenditure, pharmaceutical services, waste management, and patient treatment plan, in a cloud-based integrated system with the motive to change the storage mode of data from manually into digitally computing mod with accessing it efficiently through the cloud. Today, the major issue is to integrate the real-time patient data into cloud-based system information through the architectural design of data canal and formal models/ methods. Data privacy &amp; data integrity are the major concerns from the security point of view. Data may protect from loss and theft to mitigate the number of attacks whichever hits from the end-user/ client, network, and cloud service providers.
DirectAR: Marketing an Educative AR Experience in 2019

In this paper we will be analyzing how to advertise and market a tool that uses augmented reality to teach the basics of videography to students. Our product is aimed at people that don’t have the accessibility or the financial resources to get a video camera but want to learn. Our market is 12- 17 year-old users, we will be trying to market to schools directly for access to this demographic. We have chosen this demographic to correlate our product to a real problem. This problem is the exclusivity of Videography, the cost of a standard camera is proven to be too expensive for people that want to learn at a young age. Since there is a higher demand for videography skills in the workplace, we see this as an economic solution for those who want to learn the basics and see if they like it enough to invest in this artform. How do we get this tool into as many classrooms as possible? Since there are no products like this in schools, we will base our assumptions on research into how new technologies are selected in schools or in households. We will explore three different approaches: advertise to the kids themselves, advertising to the parents but our analysis concludes that the most effective way to solve this problem is to advertise this product to school associations and school boards.
Didactic bases for the use of learning technologies in biology lessons in VIII–IX grades

The article notes that in the modern world the future of any country is measured by the level of education in this country.The development of education is an integral part of the development concept of each country, that is, education is one of the main priorities of the state.At present, the education system of the independent Azerbaijan Republic is based, along with other principles, on democratic and humanistic principles.Thanks to interactive teaching methods, students develop the ability to think independently, express their attitude to the opinions of others, and be able to justify their own judgments.This lays the foundation for independence and flexibility of thought.The use of modern teaching technologies in biology lessons not only equips students with biological knowledge, but also allows them to independently extract and assimilate more information, acquire new abilities and qualities through the development of logical, creative and critical types of thinking.Interactive teaching methods increase the interest and motivation of students in the lesson, and even the weakest student is stimulated to learn and act with the help of such teaching.Mastering teaching technologies is the basis of pedagogical excellence.In the modern period, the use of new technologies and teaching methods requires a fundamental change in the activities of the teacher, his pedagogical work, work style and, as a result, the style of work of students.The main purpose of this article is to study the application of teaching technologies, which occupy a leading position in the global education system and are considered the most optimal learning experience, and to study the didactic foundations for their use in teaching biology in secondary schools in Azerbaijan.The author notes that the
Secure Cloud Based Approach for Mobile Devices User Data

In this era characterized by rapid technological innovations, mobile devices such as tablets and smartphones have become inevitable due to the variety of services they offer.These devices are susceptible to loss due to their small portable sizes.The personal identification numbers (PIN) and patterns used as security controls have minimal encryption.One of the main challenges of using mobile devices is the risk of private and/or confidential data stored in the device's internal memory being exposed to unauthorized persons and the risk of permanent loss and/or damage of that data.The objective of the study is to analyze existing security solutions for mobile devices user data storage and propose a secure approach to address possible security threats and vulnerabilities to these solutions.The solution provides mobile device users with the ability to securely store/retrieve their data anytime and from anywhere even in the event of device loss.Furthermore, mobile device manufacturers are able to leverage on the solution and patch their systems in order to improve on mobile device data storage security.The research highlights existing threats and vulnerabilities to existing mobile data storage devices.This helps in creating awareness to mobile device users who as a result are expected to be more vigilant and can also utilize proposed precautionary measures.
A Feature Fusion Based Hybrid Approach for Breast Cancer Classification

A detected type of cancer is breast cancer commonly in women. According to some estimate one in nine women is diagnosed with breast cancer. It is unfortunate that due to a lack of proper facilities, the diagnosis of breast cancer in patients is being delayed, which is leading to an increase in the possible death rate. Many different statistical methods and Machine Learning algorithms are often employed in the study to make breast cancer detection more accurate. Machine learning (ML) has allowed doctors to achieve remarkable results, and healthcare is using ML-based models to detect breast cancer in women. This allows analyzing the healthcare data and uses the traditional computer-aided detection (CAD) to assess breast cancer. Machine learning has become an accepted clinical practice and allows doctors to evaluate the ML model to detect breasts at an early stage. A major aim is to diagnose patients with breast cancer by analyzing the data of patients and classifying them into two categories, having diagnosis results as Benign "B" or Malignant “M”. In this study different machine learning algorithms are used to classify cancer as either its malignant or benign. The Kaggle data set was used for applying these algorithms to get the best accuracy. MLP is more efficient and accurate algorithm to classify the breast tumor. And here also fitted the matthews_corrcoef for MLP is 0.89% and accuracy score for the random forest is 0.94%.
THE USE OF MICROSOFT TEAMS AS AN ONLINE PLATFORM IN ELT CLASSROOM DURING THE PANDEMIC: STUDENTS’ PERCEPTION

During the COVID-19 pandemic, Indonesia is currently implementing a new policy that is teaching and learning activities from a distance, or we can call it learning from home or online learning. All education institutions require teachers and students to use online platforms to continue the learning process. The research aimed to find out the students’ perception of using Microsoft Teams as an online platform during the pandemic. This research was categorized as an explanatory-sequence approach. This study involved 8th-grade students (N=18) from the public junior high school in Surabaya. Eighteen items of questionnaires have been distributed. The findings revealed that the majority of the students involved in this study have a good perspective on using Microsoft Teams as an online platform; because of the ease of the use of Microsoft Teams, the students feel that the features of Microsoft Teams are pretty useful for them as the students, but even though most of them enjoy using Microsoft Teams, they prefer to choose to do classical learning which can be known as traditional learning.
Predictors and Components in the Academic Motivation of Nursing Students during the Covid-19 Pandemic in Jordan

Abstract&#x0D; Background: Nursing is a noble profession that aims to care for individuals, families, and communities to achieve optimum health and quality of life. Nurses are the largest constituent of the healthcare team and nursing students’ motivation towards their field of inquiry affects their satisfaction and academic performance.&#x0D; Aim: To examine the academic motivation among nursing students in public universities in Jordan in the context of COVID-19.&#x0D; Materials and Methods: A descriptive cross-sectional study conducted in three public universities in Jordan. A total of 437 nursing students in their second, third, or fourth year of study answered a self-administered online questionnaire. Descriptive and multivariant analysis was conducted using SPSS 24. &#x0D; Results: Academic motivation among students from three public universities was below the averages reported in the international literature. Students’ mean scores on the academic motivation scale knowledge was 90.25 out of 196, and the average mean scores for all subscales were just above the midpoint, except for the extrinsic regulation scale, which was 14.57 out of 30. Students reported higher levels of extrinsic motivation.&#x0D; Conclusions: Educators must focus on nursing students’ need for support and consider the development of a curriculum that strengthens student learning and nurtures their internal and external motivation needs.
Development of Photovoltaic Power Generation Prediction Model using ANFIS

Prediction of photovoltaic (PV) performance is important for energy management practices. The power produced from renewable energy sources is uncertain in nature as it is subjected to continuous changing weather conditions. Hence accurate prediction of output power from these sources is difficult task. In this paper Adaptive Neuro-Fuzzy Inference System (ANFIS) based forecast model for predicting the PV power generation is developed. The proposed model is based on back propagation hybrid learning algorithm of ANFIS with four inputs and one output. Experimentally measured input data of 20 KW. PV system installed at Nashik, Maharashtra, India is used for developing prediction model. The inputs are solar radiation (Rad), ambient temperature (Temp), relative humidity (Hum) and day of year for measurement. Photovoltaic power generation is the output of the model. This data is utilized in the training and testing of the proposed model. Results obtained confirm the ability of the developed ANFIS model for assessing the power produced with reasonable accuracy. A comparative study has done between regression analysis and ANFIS. This shows that the ANFIS-model performs much better than regression. The advantage of the ANFIS model is that they do not need more parameters or complicate calculations unlike implicit models. The developed model could be used to forecast the profile of the produced power in uncertain whether conditions. The error due to ANFIS prediction model for energy produced from the given system considered in this research is 6.14 % which is much better when compared with regression analysis whose error is 16 %. The results indicate that this model can potentially be used to estimate and predict PV solar output power.
Applications of Bayesian Skyline Plots and Approximate Bayesian Computation for Human Demography

Bayesian methods have been adopted by anthropologists for their utility in resolving complex questions about human history based on genetic data. The main advantages of Bayesian methods include simple model comparison, presenting results as a summary of probability distributions, and the explicit inclusion of prior information into analyses. In the fĳield of anthropological genetics, for example, implementing Bayesian skyline plots and approximate Bayesian computation is becoming ubiquitous as means to analyze genetic data for the purpose of demographic or historic inference. Correspondingly, there is a critical need for better understanding of the underlying assumptions, proper applications, and limitations of these two methods by the larger anthropological community. Here we review Bayesian skyline plots and approximate Bayesian computation as applied to human demography and provide examples of the application of these methods to anthropological research questions. We also review the two core components of Bayesian demographic analysis: the coalescent and Bayesian inference. Our goal is to describe their basic mechanics in an attempt to demystify them
Image-guided Localisation of Nonpalpable Breast Lesions: a Comparative Analysis of Magnetic Seeds and Hookwires in an Asian Population

Objectives: To compare the procedural outcomes of magnetic seed localisation and hookwire localisation (HWL) of nonpalpable breast lesions in an Asian population.Methods: We performed a retrospective review of 91 nonrandomised female patients who underwent breast surgery after image-guided magnetic seed localisation or HWL from July 2019 to June 2021.Rates of placement success (defined as marker-lesion distance <10 mm), lesion detection, marker retrieval, and complications, were compared.Results: A total of 48 patients received magnetic seeds, and 43 patients received hookwires for preoperative localisation; a total of 100 lesions (50/100, 50.0%Magseed vs. 50/100, 50.0%hookwire) were marked and excised.Magnetic seeds were placed 0 to 126 days before surgery (median=14); of the 50 lesions marked, 22 were removed on the same day and 28 on a later day.Placement success was identical between the two groups, 98.0% magnetic seeds versus 98.0% hookwire.All lesions were detected at the first operation and successfully excised; all markers were removed intact without complications.Conclusion: Magnetic seed localisation demonstrated comparable procedural success and safety to conventional HWL in Asian patients with thinner and denser breasts.It could be an effective alternative to HWL, with the additional advantage of decoupling localisation and surgery dates.
Effect of Class-Wide Peer Tutoring on Students’ Performance in Physics in Dekina, Nigeria

The study investigated the effect of Class-wide Peer Tutoring (CWPT) on students’ performance in physics in Dekina, Nigeria. Two co-education public secondary schools were purposively selected. A total of 64 (male = 31, female = 33) senior school two (SSII) students were randomly selected from the sampled school. A quasi-experimental design was adopted for the study. The instrument used for this research was a 20-multiple-choice projective Motion Test (PMT) developed by the researcher. The treatment in the experimental group was the teaching of Projectile Motion using the CWPT strategy. Mean, standard deviation, and ANCOVA was used to analyze the data collected. The findings revealed that there was a significant difference between the performance of the experimental group and the control group in the favour of the experimental group and no significant difference in the performance of male and female students when both are taught Projectile Motion using CWPT. It is recommended among others that teachers should be trained to adopt classwide peer-tutoring in schools since it facilitates the academic performance of students in physics.
In situ Concentration and Adsorption Characteristics of Cu(II) and Pb(II) in Bed Sediments of River Niger in Lokoja Area, Nigeria

In this present study, concentrations of copper and lead were investigated in natural sediment at three locations along the Niger River in Lokoja, Nigeria. In addition, the ability of bed sediment to control metal ion contamination in aquatic systems through absorption as a sink process was also evaluated. Parameters and models that control the behaviour of metals in solution, such as pHzpc, pH of the sediment, kinetics, and equilibrium isotherms were interpreted. The pH value of sediment in water and calcium chloride (CaCl2) was in 4.6-7.2 range, indicating that the sediment is moderately acidic and indicating the slow movement of metal ions to overlying water column. The tolerance of River Niger to metal adsorption in the sediment was in the order of Cu&lt;Pb. According to thermodynamic adsorption data, equilibrium isotherms and kinetic studies, the adsorption behaviour of Cu(II) and Pb(II) ions in aqueous solutions occurs spontaneously, and follows Langmuir and Freundlich isotherms, and has a pseudo-first-kinetic order. The current copper (18.81-34.68 mg/kg) and Lead (14.81-38.36 mg/kg) content in Niger River sediment samples are relatively low compared to other river sediments an indication of low anthropogenic activities in the study area.