Reviewerly/exHarmony huggingface dataset:
4GL Code Generation: A Systematic Review

Code generation is longstanding goal in software engineering.It allows more productivity of computer programming as it aims to provide automation of transformation of models into actual source code.This process has been covered adequately in many programming languages.However, this topic has not been covered sufficiently with regards to Fourth Generation Languages (4GL) which have a high specialized nature.The goal of this paper is to represent a systematic literature review of 4GL Code generation.The paper focuses on reviewing systemically the studies published in the past 20 years on the topic.This is to investigate the trends in the topic and the approaches introduced in order to identify potential new research lines.
Mobil Anlık Mesajlaşma Uygulamaları Üzerinden Üniversite Öğrencilerinin Yabancı Dil Gelişimlerinin Desteklenmesi

Applications on the smartphones that university students frequently use are actively involved in their learning processes.These applications can be used to support students' foreign language development processes in the form of extracurricular activities.The aim of this study is to examine the changes in foreign language development as a result of supporting university students through instant messaging applications.In addition, the views of some of these participants on this process were included in the study.The study was designed as mixed pattern.Quantitative and qualitative methods are used.In the assessments of the quantitative data, paired sample t-test analyzes were performed over the pretest and posttest success scores of 31 participants.Qualitative data were collected through face-to-face interviews with seven participants through a semistructured interview form.Qualitative data were analyzed via content analysis.When the findings of the study are examined, it is understood that instant messaging application is effective.It was determined that the foreign language development of the participants increased significantly in the six-week period.It was also determined that, with the process, the participants started to be more effective in the lessons due to the development of vocational foreign language.In this context, it was stated that the participants' interest in the course increased.It is understood that this situation has positive effects on the self-confidence and motivation levels of the participants.However, it was stated that some participants were bored with the application because they had low interest in foreign languages.Among the suggestions of the study, there is a suggestion that a similar study can be conducted for a longer period of time, and that the participants' foreign language development, changes in the interest and motivation levels of the course can be followed.Structured Abstract: Technological devices have started to be among the most important requirements of daily life.It increases the interaction of users with these devices over time.This result has an impact on the emergence of applications that allow greater interaction over time.In particular, portable devices are more preferred because they give users more flexibility.Smartphones, which are the most common among these devices, are used extensively by university youth today.Since mobile devices are used by students for multiple purposes, they are at the center of students' lives.Applications on the smartphones that university students
Pengujian Black Box pada Perangkat Lunak Sistem Penilaian Mahasiswa Menggunakan Teknik Boundary Value Analysis

With this student assessment application, if there is an error in the program, there will be losses for students and universities. The loss that is in the natural student, if this application has an error (trouble) then the student assessment process will be delayed and difficult in the calculation of the value of students and students will be late in obtaining the value. The losses are in the natural universities where students want a quick assessment process but the university cannot calculate quickly and precisely. Method used in this application use black box method with boundary value analysis technique. The boundary value analysis technique measures application's assessment if there is an error when entering data that will be tested in the field to determine the value has been valid or no more errors will be stored in the database. The test is done on the Student assessment form by measuring the upper limit value and lower limit value through several predefined stages for each of the columns in the form. Test results can be input to improve the application. The results of this test can provide reference to the quality testing of the student assessment application by analyzing the functionality of the programs that have been made in accordance with the results expected
A Privacy-Aware Dynamic Authentication Scheme for IoT Enabled Business Services

Tech-savvy users are striving to bring automation and digitization in their lifestyle to make life more comfortable and efficient; Internet of Things (IoT) is an enabler in this direction.Technology advancements and new business opportunities are rapidly changing the IoT adoption landscape, and thereby security and privacy concerns have also started raising and realizing.The increasing number of IP enabled electronic devices, enormous data generation, and communication traffic have enhanced the attack surface for security and privacy violators.Many security attack scenarios are the result of poor identification and authentication mechanisms of communicating entities.In this paper, we present a secure scheme to perform a business transaction initiated by a smart device in the IoT environment.Scheme performs dynamic authentication of a business transaction while ensuring the privacy of the associated user(s).This scheme relies on Message Authentication Code (MAC) and dynamic key generation method to achieve a secure workflow.In this paper, we present a pluggable Roaming Smart Meters (RSM) concept to demonstrate the applicability of the proposed authentication scheme.
Applicability and Efficiency of Socio-Cultural Inspired Algorithms in Optimizing Mechanical Systems – A Critical Review

In the recent years' optimization algorithms are used in many real-life applications to get the best out of everything.There are many types of optimization algorithm such as Nature inspired algorithm, Bio-Inspired algorithm which also have their applications.This paper aims to presents different category of algorithms and their applications, which are inspired by the social behavior of humans in groups termed as family.These algorithms are widely appreciated by researchers from various domains for optimization.The performance of social algorithm (SA) to discover the global optimum solution for the constrained, unconstrained and multi-objective optimization problems is sound.This paper extensively reviews and presents the applicability and also efficiency of the socio-inspired algorithm in solving real life problems in the field of mechanical engineering mechanical engineering problems.
The Phubbing: The interference in communication within the classroom

Currently, the fourth industrial revolution and the advantages that it brings in relation to the use of technologies are discussed, which is also reflected in the educational field. Nowadays it is increasingly common to observe that students use the cell phone as a technological instrument that allows them to consult relevant information within the classroom, as well as perform various activities associated with the academic field. However, it has also increased the habit of misusing the mobile device by the student, by sending personal messages or entering various social pages without the authorization of their teachers and during classroom sessions, which generates interference of communication and is known as Phubbing. The objective of this research is to describe the different uses of the cell phone in a school day by university students of a technological educational institution in central Mexico. The study is quantitative, descriptive - correlational, transversal and non-experimental. A sample of 92 subjects was used. A questionnaire based on [1-3], among other authors, was applied. The main results obtained show that at least 30% of the students participating in the study use the cell phone in class for personal use, without the teacher's consent.
Cost Optimization based Resource Allocation Scheme for Vehicular Cloud Networks

Efficient Resource management in an Vehicular Cloud Networks (VCN) results in an increase resource utilization and reduction of the cost.Proper resource allocation schemes in VCN provides the better performance in terms the reduction of cost, reduction in the waiting time of vehicle (client) and also the waiting queue length.Resources are required to provide more efficiently by the cloud providers for the requested services by the vehicle.For this reason it is necessary to design proper resource allocation schemes in VCN.The aim of resource allocation scheme in VCN is to allocate the appropriate computing resources for the client vehicle application.Efficient resource allocation scheme in VCN plays a major role in the overall performance of the system.Members of VCN change dynamically due to the mobility in their movement.Vehicles may face high costs or issue related to the performance parameter when proper resource allocation schemes are not applied.In this work, we proposed the cost effective based resource allocation in VCN.The proposed cost model provides the resource to vehicle by considering the lesser expensive approach hence by achieving in the reduction of cost.We compare the results of the cost optimization with the generic algorithm that uses a combination of best fit and first fit techniques for resource allocation in VCN.
On the task approach in artificial intelligence

The authors discuss the problem of the integration approach to artificial intelligence, analyzing the content and positive aspects of the integration agent approach. It is noted that this approach implicitly follows the task approach. The paper gives answers to the questions that make up the essence of the task approach - where do the tasks come from, what is the task, what should be considered a solution to the problem. It also discusses the classification of intellectual problems into direct, inverse, and hybrid. It is noted that modern artificial intelligence focuses mainly on solving direct and inverse problems, leaving a huge and important class of hybrid problems outside its scope of attention. The paper describes the theoretical model approach to solving the whole variety of intellectual problems, called semantic modeling. It analyzes the advantages of the proposed conception, including the possibility of a flexible combination when solving hybrid problems of tools already created in artificial intelligence. It also discusses the problem of creating a “strong” / “general” artificial intelligence (AGI) in the framework of the task approach.
A 4D Counter-Example Showing that DWCness Does Not Imply CWCness in nD

In this paper, we prove that the two flavours of well-composedness called Continuous Well-Composedness (shortly CWCness), stating that the boundary of the continuous analog of a discrete set is a manifold, and Digital Well-Composedness (shortly DWCness), stating that a discrete set does not contain any critical configuration, are not equivalent in dimension 4. To prove this, we exhibit the example of a configuration of 8 tesseracts (4D cubes) sharing a common corner (vertex), which is DWC but not CWC. This result is surprising since we know that CWCness and DWCness are equivalent in 2D and 3D. To reach our goal, we use local homology.
FlowSynth: Simplifying Complex Audio Generation Through Explorable Latent Spaces with Normalizing Flows

Audio synthesizers are pervasive in modern music production. These highly complex audio generation functions provide a unique diversity through their large sets of parameters. However, this feature also can make them extremely hard and obfuscated to use, especially for non-expert users with no formal knowledge on signal processing. We recently introduced a novel formalization of the problem of synthesizer control as learning an invertible mapping between an audio latent space, extracted from the audio signal, and a target parameter latent space, extracted from the synthesizer's presets, using normalizing flows. In addition to model a continuous representation allowing to ease the intuitive exploration of the synthesizer, it also provides a ground-breaking method for audio-based parameter inference, vocal control and macro-control learning. Here, we discuss the details of integrating these high-level features to develop new interaction schemes between a human user and the generating device: parameters inference from audio, high-level preset visualization and interpolation, that can be used both in off-time and real-time situations. Moreover, we also leverage LeapMotion devices to allow the control of hundreds of parameters simply by moving one hand across space to explore the low-dimensional latent space, allowing to both empower and facilitate the user's interaction with the synthesizer.
Respons Dosimeter OSL Lingkungan terhadap Radiasi Gamma 137Cs Dosis Rendah

Optically stimulated luminescence (OSL) dosimeter is used as a measurement tool for natural radiation and occupational area.OSL dosemeter has characteristics which are sensitive to low dose, simple and repeatable dose reading.This research is carried out to determine the response of the environmental OSL dosimeter to low dose.The method is conducted by preparing four groups of OSL dosimeters.Each with four pieces was irradiated with gamma 137 Cs of 0.1 mSv, 0.5 mSv, 1 mSv and without irradiated (control) as much two times of irradiation with different dosimeter configurations.Ambient dose responses or H*(10) show a linier curve with the equation of Y (reading dose) = 0.802 * X (exposure dose) -0.121 and Y = 0.851 * X -0.119 and also correlation factor was 0.97-0.98.The exposure dose to OSL dosemeter can be read by OSLD microStar reader if it exceeds 0.151 mSv (configuration 1) and 0,140 mSv (configuration 2).
Cross-Modal Search for Social Networks via Adversarial Learning

Cross-modal search has become a research hotspot in the recent years. In contrast to traditional cross-modal search, social network cross-modal information search is restricted by data quality for arbitrary text and low-resolution visual features. In addition, the semantic sparseness of cross-modal data from social networks results in the text and visual modalities misleading each other. In this paper, we propose a cross-modal search method for social network data that capitalizes on adversarial learning (cross-modal search with adversarial learning: CMSAL). We adopt self-attention-based neural networks to generate modality-oriented representations for further intermodal correlation learning. A search module is implemented based on adversarial learning, through which the discriminator is designed to measure the distribution of generated features from intramodal and intramodal perspectives. Experiments on real-word datasets from Sina Weibo and Wikipedia, which have similar properties to social networks, show that the proposed method outperforms the state-of-the-art cross-modal search methods.
Android-based Application Utilizing Image Processing with Artificial Neural Network for Detecting Ringworm and Yeast Infections for Dogs Using Neuroph Framework

This study offers dog owners a system deeloped using Android that can determine a dog's skin infections such as yeast and ringworm with the use of an image processing algorithm.The system can run on Android devices with a minimum camera resolution of five megapixels to clearly capture the dog's skin and make a precise prediction.In this study, the Open Source Computer Vision (OpenCV) was used to detect and analyze captured image as a localized skin lesion, in which it has the ability to stitch the image together in order to produce a high-resolution image of the entire scene and to clearly find a similar data image from the images in the database.The artificial Neural Network (ANN) model was also utilized in the application for the training and testing of the dog skin disease dataset where the captured images can be detected and analyzed by using OpenCV.Captured images are compared to the sample images in the database and is used for image classification.Further, the application has the ability to analyze the captured image and provide the details when determined.
Salient context-based semantic matching for information retrieval

Abstract Neural networks provide new possibilities to uncover semantic relationships between words by involving contextual information, and further a way to learn the matching pattern from document-query word contextual similarity matrix, which has brought promising results in IR. However, most neural IR methods rely on the conventional word-word matching framework for finding a relevant document for a query. Its effect is limited due to the wide gap between the lengths of query and document. To address this problem, we propose a salient context-based semantic matching (SCSM) method to build a bridge between query and document. Our method locates the most relevant context in the document using a shifting window with adapted length and then calculates the relevance score within it as the representation of the document. We define the notion of contextual salience and the corresponding measures to calculate the relevance of a context to a given query, in which the interaction between the query and the context is modeled by semantic similarity. Experiments on various collections from TREC show the effectiveness of our model as compared to the state-of-the-art methods.
Like Two Pis in a Pod: Author Similarity Across Time in the Ancient Greek Corpus

One commonly recognized feature of the Ancient Greek corpus is that later texts frequently imitate and allude to model texts from earlier time periods, but analysis of this phenomenon is mostly done for specific author pairs based on close reading and highly visible instances of imitation. In this work, we use computational techniques to examine the similarity of a wide range of Ancient Greek authors, with a focus on similarity between authors writing many centuries apart. We represent texts and authors based on their usage of high-frequency words to capture author signatures rather than document topics and measure similarity using Jensen-Shannon Divergence. We then analyze author similarity across centuries, finding high similarity between specific authors and across the corpus that is not common to all languages.
A New Japan Volcanological Database

For the purpose of the development of volcanology and practical application to volcanic hazard mitigation, we are conducting a new project named the Integrated Program for Next Generation Volcano Research and Human Resources Development (INeVRH). This project consists of 4 themes focusing on observation, forecasting, countermeasures and data sharing system. Data sharing system is named the Japan Volcanological Data Network (JVDN), which will be a platform to combine observation, prediction and countermeasure data to give information for the judgement at branch nodes of event tree for volcanic crises.
Theme and Thematic Progression in Narrative Texts of Indonesian EFL Learners

This study aims to analyze and describe the Thematic progression patterns and types of Theme in students' narrative texts of Indonesian EFL Learners.This study employs a descriptive-qualitative research design.The data were obtained from a collection of students' texts.This study uses the theory of Thematic progression: Bloor and Bloor (2004), and the theory of types of Theme developed by Halliday (1994), Gerot & Wignell (1994), Halliday et al. (2004).The finding shows a dominant use of Constant pattern in narrative texts indicates that the students are able to create a focus on specific participants as this is one of the linguistics features of narrative texts.The use of Linear pattern indicates that the students have achieved the ability to create cohesion of the texts by introducing the new information by taking a Rheme to become Theme of the upcoming clause.In terms of types of Theme, the high number of Topical Themes in students' text may indicate that the students are able to lead the reader to focus on participants (characters) of the story.The use of Interpersonal Themes, which dominantly used by middle and low achievers, indicate that high achievers tend to be complex lexically (written language), while middle and low achievers tend to use complex grammatically (spoken language).The dominant use of Textual Theme indicates that the students are able to create complex clause and to connect the clause which helps them to create a cohesive and coherent text.
Modelling epistemic irrelevance with choice functions

We consider coherent choice functions under the recent axiomatisation proposed by De Bock and de Cooman that guarantees a representation in terms of binary preferences, and we discuss how to define conditioning in this framework. In a multivariate context, we propose a notion of marginalisation, and its inverse operation called weak (cylindrical) extension. We combine this with our definition of conditioning to define a notion of irrelevance, and we obtain the irrelevant natural extension in this framework: the least informative choice function that satisfies a given irrelevance assessment.
Multilevel Voter Identity Protocol for Secure Online Voting

The word vote means to choose from a list, to elect or to agree on.The main goal of voting, in a scenario involving the citizens of a given country, is to come up with leaders of the people's choice.Some of the problems involved in existing voting systems include vote rigging during election, insecure or inaccessible polling stations, inadequate polling materials and also inexperienced personnel.In the era of Internet of Things/Everything, it is decadent to say online voting is not secure.Rather we have to arise with Aadhaar as an enabler.Unique Identification Authority of India (UIDAI) ensures and slogs so that its ecosystem adopts measures to keep Central Identities Data Repository (CIDR) up to dateand safe.Also, in current situation where almost whole world is facing pandemic situation because of COVID-19, only E-services like E-Banking, E-Learning, E-voting are unaffectedly operational.Proposed system seeks to address these issues.Voters can vote from anywhere around the globe online, satisfying the condition that they have a valid Aadhaar card and they are registered voters.We are proposing multilevel voter identity protocol for secure online voting.We are naming our proposed work as COVID (Consolidate Online Voter IDentification) as it is merging CIDR with E-voting system.In this, the Aadhaar number authenticates Demographic details and fingerprints to develop an online identity service system.The paper is complemented with algorithms for Multiple Face detection, Eye-blinking detection or eye-tracking as a countermeasure against spoofing in face recognition systems.Objective of this work includes online voting system to automate the data flow and validating the system to ensure that only legible voters are permitted to vote and only once.Considering enormity of CIDR, scope of the work can be extended by incorporating iris detection system for authenticating voters.On the other hand, major challenge is to provide end to end security of Demographic details from CIDR to voting devices.