Reviewerly/exHarmony huggingface dataset:
Trade in Personal Data:

The transnational trade in personal data, while emerging as a valuable economic activity, poses many challenges for regulators and organizations. One of the major challenges is the fragmented and ad hoc approach taken by countries, and the European Union, in their data protection laws. This has led to data protection laws varying greatly from jurisdiction to jurisdiction. This paper will explore alternative legal mechanisms that might be available in the international arena to assist in the control and regulation of trade in personal data. The starting point is to review the use of different approaches that are adopted in intellectual property and copyright law to address this issue. Another vantage point is to espouse a contractual approach, which arguably is most achievable because the general principles governing contractual obligations are similar in most jurisdictions. This paper will argue that the Convention on the International Sale of Goods (CISG), can provide an alternative legal mechanism that can effectively help to regulate the cross-border trade in personal data. The paper will highlight how the CISG can be attractive as a practical legal mechanism for managing the sale of personal data through transnational contracts and by relying on copyright law. Applying the CISG provides individuals and entities with another legal mechanism that they can use effectively, not only to provide a level of control over personal data, but more importantly, to help facilitate trade in personal data. However, before concluding that the CISG is an effective legal mechanism, it will be important to determine whether personal data can be categorized as a good. It is our view that, in response to this challenge, personal data can be the subject of a sale of goods, and therefore can be subject to the application of the CISG. Keywords: CISG, copyright, intellectual property, personal data
MENINGKATKAN MINAT MEMBACA MELALUI IMPLEMENTASI PROSEDUR MEMBACA TERBIMBING (GUIDED READING PROCEDURE)

Reading is one of the activities out in the learning process. Reading is also an ongoing communication skill. After the researchers used the implementation of the guiding reading approach (Guilded Reading Procedure) students’ interest in reading had increased very well with an average value of 88.6. This research used action research as much as 2 cycles. Clycle I consisted of 6 stages: Plannging, observation, questionnaire, interview, reflection and revision. While the second cycle consists consisted of 6 stages: Plannging, observation, questionnaire, interview and reflection. The target of study is students of class III A MIN 3 Langsa City. The conclusion of study was learning to read trought the implementation of reading procedure guide can have a positive influence on learning outcomes and can increase student motivation in reading.
Governance, Entrepreneurship and Employment Growth in Africa: Does Resource Richness Matter?

Economic retardation in resource rich economies continues to elicit concerns among economists and development experts. This retardation has been linked to resource endowments and the neglect for institutions of governance in resource rich economies. This paper investigates the effects of governance, financial market development, labor market freedom and human capital on economic performance in resource rich countries in Africa. Using micro level employment growth as a proxy for economic performance and based on OLS model, the study shows that governance and financial market development have a positive and statistically significant relationship with employment growth. Labor market freedom and human capital development exert a negative impact on employment growth. These results imply that good governance, measured by political stability and government integrity provides assurance to investors and entrepreneurs, thus fostering private sector investment in the economy. When the economy is characterized by higher degree of uncertainty as a result of poor governance, investors perceive of higher risk of investment. Consequently, risk-averse investors may hesitate to take economically productive initiatives or may exit the economy altogether. Financial market development encourages growth by enhancing allocative efficiency and flow of finance to productive and nascent entrepreneurs who often rely on external financing. The negative relationship between labor market freedom and employment growth in resource rich countries is counterintuitive. This result could imply that when employers have more freedom to hire and fire due to less government control of the labor market, they become less committed to employees since they find it easy to dismiss them without incurring significant costs. Human capital development could exert a negative influence on employment growth by delaying the joining of and participation in the labor market as potential employees delay seeking jobs to pursue education.
A NOVEL TECHNOLOGY FOR MACHINE TO MACHINE COMMUNICATION USING ETHEREUM SMART CONTRACTS

In the emerging world of IoT applications, machines are going to be at the endpoints of the Internet engaging in complex Machine to Machine (M2M) communications. Be it a personal assistant (softbot)making an appointment with a doctor or an autonomous car filling fuel or charging at a refueling station, in the future, it is going to be M2M communications without human intervention. In such a scenario, robust and secure technology is essential to record every M2M transactions. This paper makes use of blockchain, a distributed ledger technology for intelligent transportation systems. It is proposed that blockchain networks such as Ethereum have the foundations to record and satisfy the transaction that has happened between the machines. A permissioned Ethereum blockchain  the smart contract is used for recording each every transaction that come off between the car and electric station. An algorithm is proposed to recharge the autonomous electric vehicles as a case study.
SMART SCHOOL MANAGEMENT INTEGRASI DENGAN FINGERPRINT

The teaching-learning process that is currently running at the vocational school in Medan is still largely conventional in nature, the teacher conveys subject matter, assignments, quizzes, collection assignments in class and each subject are only done a few meetings a week with limited time. Submission of information / announcements, management and services Academic administration and reporting are still done manually so that it is slow and not effective. The purpose of this study is to create a smart school design with a system web-based online learning to overcome various problems faced by Vocational school in Medan (case study at Vocational Tritech Informatics Medan). Smart school will to be blended learning that combines conventional methods or faces with an online learning system towards smart school. The results of this study are the creation online learning system models so that interaction between teachers and students can be done whenever and wherever to improve the quality of education and administrative management academic as well as accelerating the delivery of information to students and parents about students the development and achievements of each student. And use a fingerprint that is directly integrated with the system to be designed. This can support learning in school and creating a culture / learning environment that is effective and efficient and paperless. Design Smart School software uses the waterfall method which includes five stages, namely: (1) identification of user needs; (2) analysis; (3) design; (4) implementation; and (5) testing. Smart school system design uses object-oriented modeling language, UML (Unified Modeling Language).
Decoupling Global Features by Imposing Orthogonality on the Gradients: Analysis , Synthesis and Signal Processing

MSDA, Prague CZ, 25 - 26 November 2019. -- http://naridv.cas.cz/msda-workshop. -- Conferencia invitada
THE APPLICATION OF SOCIAL MEDIA IN LIBRARY AND INFORMATION SCIENCE EDUCATION OF CHINA: A CASE STUDY

The new era of big data speeds up the development of information technology, social media has become an integral part of peopleÂs daily life and changed the way of communication between individuals. Currently, social media has been applied to education in many disciplines, there is also no exception to Library and Information Science (LIS) education. ChinaÂs LIS education is undergoing profound changes, which is more necessary to improve the quality of LIS education with the help of high-tech products. Firstly, this study gave a brief introduction to social media and past literature regarding social media applications in LIS education worldwide. Secondly, a survey on the relationship between social media and LIS education was carried out to analyze the views from two consecutive MLIS graduates from Information Management School at Heilongjiang University (HLJU). Thirdly, an actual teaching case using QQ series software was exposed keeping in view the feature of social mediaÂs application in LIS courses. Finally, some suggestions were given based on the results of the above thorough analysis.
SISTEM PAKAR DIAGNOSA TINGKAT RETARDASI DOWN SYNDROME PADA ANAK MENGGUNAKAN METODE CERTAINTY FACTOR

Down Syndrome is a condition of physical and mental development's retardation in childrenthat caused by abnormalities in the development of the chromosome. However, behind thespecial needs held by children with Down Syndrome, they have a chance to live like any othernormal child. This study aims to create a web-base application that can assist parents to makeearly detection of the retardation level of Down Syndrome in children, as well as provideinformation about how to deal with Down Syndrome. One of the benefit of this application is tohelp parents who have Down Syndrome’s children in order to make early treatment correctly.The results of the testing and evaluation declared that this web fit and feasible to detect the levelof retardation in children with Down Syndrome.Keywords— Down Syndrome, detection, level of retardation, web
A Framework for Fusion of T1-Weighted and Dynamic MRI Sequences

Breast cancer imaging research has seen continuous progress throughout the years. Innovative visualization tools and easier planning techniques are being developed. Image segmentation methodologies generally have best results when applied to specific types of exams or sequences, as their features enhance and expedite those approaches. Particular methods have more purchase with the segmentation of particular structures. This is the case with diverse breast structures and the respective lesions on MRI sequences, over T1w and Dyn. The present study presents a methodology to tackle an unapproached task. We aim to facilitate the volumetric alignment of data retrieved from T1w and Dyn sequences, leveraging breast surface segmentation and registration. The proposed method revolves around Canny edge detection and mending potential holes on the surface, in order to accurately reproduce the breast shape. The contour is refined with a Level-set approach and the surfaces are aligned together using a restriction of the Iterative Closest Point (ICP) method. This could easily be applied to other paired same-time, volumetric sequences. The process seems to have promising results as average two-dimensional contour distances are at sub-voxel resolution and visual results seem well within range for the valid transference of other segmented or annotated structures.
Time Series Anomaly Detection Based on Language Model

Energy-saving studies on edge computing generally depend on the analysis of monitoring data of the energy-consuming equipment. However, due to the dynamic nature of the deployment environment, monitoring data is prone to failure or errors, which brings challenges to energy-saving performance. In this paper, we propose a novel method based on language model to detect anomalies in the monitoring data. Unlike recent proposals, this method using a small amount of labeled historical data and performs better. Technically, the architecture of this method comprise of three parts: the input representation, the original Bert and additional output layer. Simulation results demonstrate that this method only needs a small amount of label data to train the model to obtain better results than the state-of-the-art work.
Exploratory Analysis of Consultation Patterns Prior to the Diagnosis of Depression.

Depression is frequently underdiagnosed or the diagnosis occurs in late stages, mainly because it usually presents as a paucisymptmatic diseorder. Electronic health records (EHRs) are a very useful tool to capture the longitudinal medical history of the patient which may help in diagnosing these patients earlier. We aimed to understand how these patients' consultation patterns are represented in the EHR up until depression diagnosis.
ОСОБЛИВОСТІ ВИКОРИСТАННЯ ЗАСОБІВ МУЛЬТИМЕДІА НА ЗАНЯТТЯХ З УКРАЇНСЬКОЇ МОВИ ЯК ІНОЗЕМНОЇ

The article deals with the problem of using multimedia resources in classes from the Ukrainian language as a foreign language in order to increase the level of motivation of teaching foreign students. It is emphasized the importance of combining appropriate lexical material with visualization of concepts, phenomena, processes, which will help foreign students acquire the lexical meaning of new words.
PENGUJIAN KUALITAS KELAYAKAN SISTEM INFORMASI KEUANGAN SEKOLAH SMK YPT2 PURBALINGGA MENGGUNAKAN MODEL RAPID APPLICATION DEVELOPMENT

Building a quality software is not easy. Many things must be considered in making a quality software. The more quality a software or application will be, the more expensive the price will be sold. YPT 2 Vocational School currently has an Integrated Financial Information System, but it is still running on a webbased platform. Foundations and school management have agreed to increase the reach of the system by utilizing the Android platform. In connection with the foregoing, a feasibility test for the School Financial Information System that is currently operational. Based on the literature review, it was found that the validation of the test could use the Rapid Application Development (RAD) model. The RAD testing involved competent parties in the system, including foundations, management, teachers and students. Testing was carried out by 20 respondents, and based on test results obtained information that value obtained from testing for completeness of the features obtained by the smallest standard error value of 0.008 and the highest error of 0.058. The ease of use variable with the smallest standard error is 0.013 and the highest is 0.063. The last variable tested was flexibility with the smallest error value of 0.015 and the highest 0.035. Based on research that has been done, it can be concluded that the YPT Financial Information System is declared suitable for use by users. The results of this study recommend that in creating a new platform, the Android platform, later to continue to base on the DBMS model that is currently tested. Developers can create a fire rest by utilizing a model of the system that is already running, so that the addition of service coverage will not at all interact with the controller and the model related to the presentation of information.
Introducing Extended DEMO Construction Model to RPA Application

Business Process technology has long been discussed in various business process methodologies with diverse perspectives.Among them, the discussions on were mainly limited only in effectively fulfilling functional, informational and organizational aspects.For enriching the discussion scope, from DEMO (Design and Engineering Method for Organizations) perspective, this research extends to capture both human interactions and human capabilities aspects in the business process and the relating modeling methodology is also provided.For contextualizing our proposal, RPA (Robotic Process Automation), as one of the typical new application in freeing human workers from tedious and repetitive tasks, is adopted as an illustration example of our artifact development.Also, our proposed modeling methodology is evaluated in a deep-dive field study with a Chinese Bank X to testify the utility in analyzing and identifying applicable tasks for RPA adoptions and eventually delivering the business process model.
Optimal Training Data Selection in Active Learning for Discrimination and Classification

Active learning has become a popular learning process for classification. By selecting the most beneficial training data, an active classifier achieves better classification accuracy than a passive classifier. We investigate the methods of developing two different types of optimal active learning processes, via either estimated discriminant functions or logistic regression. A comparison study is presented for the classifiers obtained by these methods. Performance of proposed active classifiers is evaluated under various conditions and assumptions. Optimal two-stage active learning is provided. Monte Carlo simulations have shown improved classification accuracy of our proposed active learning processes compared to passive learning process for all scenarios considered, with up to 10% accuracy improvement.
461 Emojis in dermatology: Changing the faces in medicine

Today's modern world is focused around incorporating advancing technologies into day-to-day activities to streamline tasks, and the medical field is no different. The surge of emoticon (emoji) use has flourished in the past decade, with more platforms available for delivery, and more emoticons being created constantly. Emojis have already found purpose in medicine, as proxies for emotions expression, and understanding between providers. Studies thus far involving emojis have integrated them into depression screens and medication instruction handouts. As studies and use increase, different areas of medicine will also explore their use for emojis in practice. Although there is no reported use of emojis in the world of dermatology, we extrapolated ideas from past studies as well as proposed new uses in the field of dermatology. We offer many new and exciting uses for emojis in dermatology, with the goal to improve communication, understanding, and patient-provider interactions. Our communication and methods of information delivery are constantly evolving, as well as the population we address. This is what makes use of emojis a rising topic in the medical field, and therefore relevant in dermatology.
Formalization of the Gateaux derivative of functional and application in the principle of virtual work

Abstract Analytical mechanics provides the central guidelines for the design of engineering machinery in use today. One of the main pillars for analytical mechanics is the principle of virtual work. In the establishment of this principle, the Gateaux derivative plays an indispensable role. In this paper, we formalize the Gateaux derivative in the interactive theorem prover HOL Light. On this basis, we formally verify the principle of virtual work. This effort paves way for the computerized formalization of analytical mechanics. Thus, it will ultimately contribute to the verified design of engineering machinery, which comes with correctness guarantees beyond what is enabled by the currently adopted validation techniques.
Efficient Half Face Detection System Based on Linear Binary Pattern

In the field of computer vision, face detection algorithms achieved accuracy to a great extent, but for the real time applications it remains a challenge to maintain the balance between the accuracy and efficiency i.e., to gain accuracy computational cost also increases to deal with the large data sets. This paper, propose half face detection algorithm to address the efficiency of the face detection algorithm. The full face detection algorithm consider complete face data set for training which incur more computation cost. To reduce the computation cost, proposed model captures the features of the half of the face by assuming that the human face is symmetric about the vertical axis passing through the nose and train the system using reduced half face features. The proposed algorithm extracts Linear Binary Pattern (LBP) features and train model using adaboost classifier. Algorithm performance is presented in terms of the accuracy i.e., True Positive Rate (TPR), False Positive Rate (FTR) and face recognition time complexity.
When Octatonic and Hexatonic Collide

Following the rise of Deleuze in chapter 6, the chapter passes through famous remarks by Deleuze concerning cybernetics and acceleration, focusing on the futuristic projects of Alexander Skryabin, who wanted to speed up time through his music and, in particular, through his harmony. While other works set the hexatonic and the octatonic in a diatonic flux, the first as an energy-discharging mechanism, the second as a storage capacity, Skryabin’s Sonata No. 10, Op. 70, recently explored by Vasilis Kallis (2015), is unique in juxtaposing hexatonic composition with the octatonically rotating model as clearly segregated areas. The chapter asks: To what extent can the flow between these cycles carry our tonal desire? To what extent does our diatonic engagement fluctuate between distinct sections? How do these different types of tonal “space” impact on our perception of “time”? How can drive analysis meaningfully integrate with <italic>Funktionstheorie</italic>?
Evaluation of heavy metals in agricultural soils from Katsina state Nigeria

This work contributes to the monitoring of Agricultural soil pollution in Katsina State, North western Nigeria by assessing the degree of heavy metal pollution in Agricultural soil samples. The study was conducted in the year 2017 within some catchment areas located within the 3 senatorial zones that constitute to make up the state (Katsina senatorial zone: Birchi, Dutsinma and Katsina; Daura senatorial zone: Daura, Ingawa and Zango; Funtua senatorial zone: Dabai, Funtua, Kafur, Malunfashi and Matazu). Analysis for the concentration of these heavy metals; Cr, Cd, Fe, Ni, Mn, Pb and Zn was conducted by the use of AAS (by Atomic Absorption Spectrophotometry) method. . Several indices were used to assess the metal contamination levels in the Agricultural soil samples, namely; Geo-accumulation Index (Igeo), Enrichment Factor (EF), Contamination Factor (CF), Degree of Contamination (Cd) and Pollution Load Index (PLI). The result of this study has shown that generally among the heavy metals evaluated, the highest concentration was observed for Fe (range: 20.195-38.347 ppm), followed by Zn (range: 0.528-1.134 ppm), Pb (range: 0.256-0.627 ppm), Mn (range: 0.261-0.572 ppm) and Cr (range: 0.093-0.344 ppm). While Cd has the lowest concentration (range: 0.022-0.043 ppm). For all the site sampled the heavy metal Ni was below detection level (BDL). From the results of heavy metals I-geo values, according to Muller’s classification, soil samples from Birchi, Daura, Dutsinma, Kafur and Zango were unpolluted (class 0) while soil samples from Dabai, Funtua, Ingawa, Katsina, Malunfashi and Matazu are moderately polluted (class 1). The result for the enrichment factor has shown that with the exception of the heavy metal Fe, which shows significant enrichment for all the sites sampled all the other heavy metals show deficiency to minimal enrichment. Also based on the contamination factors for all soil samples the heavy metal Fe has a CF values range of 1.2861-2.3240, indicating that the Agricultural soil samples are moderately contaminated with Fe. In contrast, the rest of the heavy metals exhibit low contamination in general. The value of PLI ranges from 0.2408 to 0.4935, indicating unpolluted to moderate pollution, with the sampling site for Katsina displaying the highest PLI value while the sampling site of Ingawa has the lowest PLI. The Eri values for all samples are all &lt; 40, presenting low ecological risk. The results suggest that the Agricultural soils samples from Katsina state has low contamination by the heavy metals evaluated.Key words: Agricultural soils, Heavy metals, Katsina state, Pollution load index, Contamination factor.