Reviewerly/exHarmony huggingface dataset:
Development of a Web-Based Environment for Test and Item Statistics

The aim of the research is to develop an online environment where teachers can access test and item statistics and a comprehensible report regarding the tests they have used, to ensure the storage of their reports in their own online environment as well as to have an idea on the utility of the subject matter environment. The research is planned as a design and development research. Research data was collected in two stages. The data which was needed to compare were obtained simulatively through the TAP program. Also, dta was collected from a group of 15 teachers to collect evidence for the usability of the application. Test and item statistics were calculated for the collected data and compared with the results of the programs making similar calculations. Descriptive analysis was used in the interpretation of the usability questionnaire and of teacher opinions. As a result of the research, the item and test statistics calculated for all data sets created by sampling different situations were found to be similar to those of reliable equivalent package programs. With the opinions received from the teachers, it has been concluded that the environment is useful and practical. While one of the important differences of the online environment formed by this study is its keeping a record of the past; another is its accessibility through the internet without the need for an additional program and thirdly, its usability on a mobile platform.
E-Voting Software Quality Analysis with McCall's Method

Nowadays, software testing is important, especially to determine its quality. This study aims to test the quality of e-voting software using the McCall method framework that focuses on software Product Operation aspects. By knowing the current quality of e-voting software, we know how much positive impact the existing software has, besides that the lowest metric can be improved in the future. There are five metrics tested, namely, Correctness, Reliability, Efficiency, Integrity, and Usability. The test results show that the highest metric value is correctness with 89.85%, and the lowest metric is the efficiency with 48.3%. Average, the e-voting software is considered to be of good quality with an average score of 79,932%.
IDIO: Orchestrating Inbound Network Data on Server Processors

Network bandwidth demand in datacenters is doubling every 12 to 15 months. In response to this demand, high-bandwidth network interface cards, each capable of transferring 100s of Gigabits of data per second, are making inroads into the servers of next-generation datacenters. Such unprecedented data delivery rates on server endpoints raise new challenges, as inbound network traffic placement decisions within the memory hierarchy have a direct impact on end-to-end performance. Modern server-class Intel processors leverage DDIO technology to steer all inbound network data into the last-level cache (LLC), regardless of the network traffic’s nature. This static data placement policy is suboptimal, both from a performance and an energy efficiency standpoint. In this work, we design <monospace>IDIO</monospace> , a framework that—unlike DDIO—dynamically decides where to place inbound network traffic within a server’s multi-level memory hierarchy. <monospace>IDIO</monospace> dynamically monitors system behavior and distinguishes between different traffic classes to determine and periodically re-evaluate the best placement location for each flow: LLC, mid-level (L2) cache or DRAM. Our results show that <monospace>IDIO</monospace> increases a server’s maximum sustainable load by up to <inline-formula><tex-math notation="LaTeX">$\sim$</tex-math></inline-formula> 33.3% across various network functions.
Integrative links in musical-theoretical and musical-historical cycles teaching

This paper deals with actual questions of modernization of musical pedagogical middle level teaching. Specific thinking features of contemporary students are marked, and problems of innovative development of information society are described. Difficulties of secondary professional musical education are shown. System thinking and scientific knowledge integration are pointed out as a basis of new ideological settings formation. Scientific researches in musical pedagogy about integrative links are analyzed. A use of integrative links in teaching musical-theoretical and musical-historical areas is marked as a necessary factor of solid and systematic music language image development. A language of music, as a complex of musical means of expression is named as an integrity factor. A system analysis of every element of music language aimed to discover their inner correlation and semantic role is named as a necessary clause, allowing to form a solid image of musical language and musical art in general. The authors justify a necessity of optimization and intensification of musical-theoretical schooling on the basis of integrative links inside the subjects of musical-theoretical and musical-historical cycles.
The Role of Ecb Speeches in Nowcasting German Gdp

The literature shows that the nowcasting models generally use structured data such as real, financial and survey indicators.Recent research has focused on finding the way how to use the unstructured data in the nowcasting models.The search items such as sentiments or emotions were gathered from internet platforms and used as unstructured data.In this study, it is analysed how the ECB presidents' speeches are included in the nowcasting model and to what degree they affect the quarterly gross domestic product (GDP) of Germany.First, ECB presidents' speeches are analysed to obtain the emotion indicators with assistance of the newly harmonised complex dictionary.These emotion indicators are next added to the unbalanced and mixed frequency data and the nowcasting model estimation for GDP is performed with these data using the expectation-maximisation algorithm in the dynamic factor model representation.Moreover, the news analysis is performed to show how the revisions in the real-time data, including emotion indicators, affect the nowcasts for the current and next quarter GDPs.Finally, a forecast scenario is performed to demonstrate the effects of emotion indicators in the nowcasting model of GDP which shows a slowdown for the last two years.In conclusion, it is suggested that ECB presidents' speeches may increase the performance of nowcasting models for the German GDP.
Regression Model to Estimate Effort for Software-Oriented Projects

The assessment of the product development initiative remains a complicated issue requiring additional analysis. The efficiency of the development in software depends on an appropriate estimation of the effort needed for software development and enables project managers to design software life cycle operations correctly with the efficient software cost estimating techniques. The major experimental work conducted throughout this paper is to accurately forecast the problems in developing program-related projects. The parallelization of the behavior factors is achieved using the M5P approach to maintain statistical precision. Besides, performance differences with random forest are offered with the models acquired using the M5P Method to demonstrate the efficiency attained with each method.
Pemasaran Perumahan PT. Permata Indah Bersinar Menggunakan E- CRM Berbasis WEB

Quality of service at PT. Permata Indah Bersinar is still ineffective and not maximized. Because this company does not have a web-based housing marketing information system. This company also has not implemented a Customer Relationship Management strategy. In this research, the system created is a web-based housing marketing information system. With this system, companies will find it easier to disseminate information about their housing, consumers will also find it easier to get information without having to come directly to the marketing office. This system also implements Customer Relationship Management (CRM), so that consumers can ask and answer questions about housing through this website. By utilizing a housing marketing information system using web-based Customer Relationship Management (CRM), as an effort to improve service quality and increase customer satisfaction and maintain relationships between companies and consumers.
Local Manifold Regularization for Knowledge Transfer in Convolutional Neural Networks

In this work we present a method for local manifold-based regularization, as a mechanism for knowledge transfer during training of Convolutional Neural Networks. The proposed method aims at regularizing local features produced in intermediate layers of a “student” CNN through an appropriate loss function that encourages the model to adapt such that the local features to exhibit similar geometrical characteristics to those of an “instructor” model, at corresponding layers. To that purpose we formulate a computationally efficient function, loosely encoding the neighboring information in the feature space of the involved feature sets. Experimental evaluation demonstrates the effectiveness of the proposed scheme under various scenarios involving knowledge-transfer, even for difficult tasks where it proves more efficient than the established technique of knowledge distillation. We demonstrate that the presented regularization scheme, utilized in combination with distillation improves the performance of both techniques in most tested configurations. Furthermore, experiments on training with limited data, demonstrate that a combined regularization scheme can achieve the same generalization as an un-regularized training with 50% of the data.
Educational Laboratory Complex for the Study of Complicated Systems

Laboratory practice is an important part of the educational process in a technical university. It helps to develop the skills of independent work of a future engineer and to consolidate theoretical knowledge. Due to a change-over to the digital economy, the introduction of complex production systems and their digital twins, the organization of laboratory work corresponding to the current state of the art gets more complicated. The article presents a biotechnological educational research complex for laboratory practice of the future specialists in the field of managing complex organizational and technical systems. Main feature of the complex is that the student performs two functions at the same time. He is both a researcher and an object of study, representing a complex system. The initial information in the process of laboratory work is the biosignals registered by mini sensors. The main purpose is to identify and evaluate the functional state of a person as a complex system. Various methods and algorithms for processing time series are used. Being an effective form of active learning, this approach motivates the student not only to acquire knowledge, but also to actively search for it. We give an example of using the complex to create a digital twin.
Testing as a way to assess the development of bachelors’ environmental competence at pedagogical universities

The paper is devoted to the problem of prospective teachers ecological competence development, as well as to the peculiarities of diagnostics of ecological competence components development. The goal of the paper is to show the experience of implementing a competence-based approach for a professional training of bachelors majoring in Pedagogical Education and methodological approaches aimed at assessing the process of professional competencies development. The paper deals with the concepts of environmental education and environmental competence. The authors define the environmental competence of a pedagogical university graduate as an integrated quality of personality based on theoretical knowledge, practical skills in the field of ecology and readiness of a prospective teacher for environmentally adequate and professionally appropriate behavior in situations of moral choice. A students environmental competence is presented as a complex system that includes a number of components (cognitive, value-motivational, professional-activity). The authors describe means of assessing students environmental competence development, paying special attention to a pedagogical testing. The paper defines the main stages of designing a pedagogical test and the conditions for its use. The paper also contains the results of a pedagogical experiment which was done at Natural Geography Institute of Samara State University of Social Sciences and Education. The use of testing for professional education makes it possible to determine the compliance of the content, level and quality of students training, while systematic testing allows you to evaluate the process of pedagogical university students environmental competence development.
Voice Command and Hand Gestures for Smart Home

The aim of smart home (SH) applications is to control and monitor home devices in an automated manner. This paper presents a unique approach for SH applications using a multimodal user interface (MUI), which allows users to interact with the system through multiple modes. It is implemented by fusing data from different modalities (text, audio, image, etc.). The fusion of information can occur at different levels, namely the feature, intermediate, and decision levels. This paper introduces an MUI that receives two types of inputs: voice commands and hand gestures. The proposed model relies on a feature-level fusion approach using deep learning. The performance of the proposed model has been evaluated and compared with other works. The results show that the proposed model exceeds other models.
Path Planning and optimization of Unmanned Ground Vehicles (UGVs) in the Field

Unmanned Ground Vehicle (UGV) can be as a replacement of human beings during a dangerous mission. It can also be applied to military and performs repetitive mechanical transportation. For the UGVs in the conventional layout and structured urban environment, the research of environment perception and path planning technology has been relatively mature. Compared with the flat ground, the control of the UGV in the field is unknown and more complex. This article revolves autonomous control of the UGV in the field, putting forward a kind of path planning and optimizing technology for the UGV under complex environment. Research content includes: Conduct field environment modeling with environment information. First, the environment is detected by the fusion of lidar and IMU. Then a more accurate environment model is obtained by training the RBF neural network. Use the obtained environmental model to conduct path planning for the UGV in the field. The path planning trajectory is obtained by introducing the distance between the starting point and target point, the environmental height and environmental gradient constraints to construct the cost function. Then Analyze different characteristics of the paths that are generated by modifying the constraint function. optimize the smoothness of the generated path for the field UGV. The path is optimized from broken lines into a curve by using a 5th order polynomial trajectory.
Volatile Memory Disk Forensics: Investigate the Criminal Activity of RAMDisk

In this ever-expanding cyber space, computer is a very valuable asset, but if used with malicious intentions it can create an environment of chaos. Computer forensics which is a part of digital forensics aims at collecting, analyzing, and documenting digital evidences such that they are admissible in court of law. But integrity of digital evidences comes under scrutiny due to anti-forensics tools and techniques that are exercised by cybercriminals to evade detection. RAMDisk is one of such technique used by cybercriminals to avoid detection and perform clean up after the crime that has been committed. Cybercriminals use this technique to store sensitive information and data in RAMDisk and discard it once the purpose has been served. This paper discusses the working of three popular RAMDisk softwares namely AMD Radeon RAMDisk, ImDisk Toolkit. and Miray RAM Drive. We have also identified proprietary drivers and unique signatures for each software and what approach can be adopted by a forensics investigator to investigate them.
Radio frequency identification based electronic voting machine using fingerprint module

Abstract Radio frequency identification (RFID) based electronic voting machine (EVM) with fingerprint module overcomes the challenges of wired electronic voting. Finger print module is to authenticate the voters. In this paper the system is constructed with microcontroller, Liquid Crystal Display (LCD), RS232 cable, RFID reader, RFID tag, fingerprint module and buzzer alarm. Dishonest voting will be avoided if the government uses the biometric based system. The details of all voters with their fingerprint will be stored in the database. Database is kept in microcontroller. Microcontroller verifies the voter by comparing the database during polling. If a person with RFID comes for second time voting, immediately the buzzer gives sound. The RFID base EVM will reduce time consumption. When compared to the existing voting system, the system in this paper is expected to be fast and reliable. The voters’ details will not be revealed out. For every polling end, the button should be pressed for getting the number of votes polled.
RETRACTED: Simulation of dance performance analysis with microprocessor and machine vision interaction

Dance is the expression of artists' favourite art forms such as express emotions, their body language, and the combination of dance art and stage effects in dance performance. In almost all genres of the art form, the effectiveness of the dance performance is largely due to the quality of the individual dancer's and group dance performance. Performing arts, particularly dance, it is one of the most important of intangible cultural heritage. However, due to the preservation, documentation, analysis, and visualization understanding of dance mode, it is difficult because of technical difficulties relations. The Proposed Machine Learning Support Decision Vector Machine (SDVM) algorithm and Field Programmable Gate Array (FPGA) is a dance expert watching dance due to the recognition task, the task knowledge of professional forecasters, gestures, and facial expressions and face-to-face conditions led to better synchronization of timing. In the proposed Machine learning SDVM algorithm, the results show that positive and dancers in the audience increased negative emotions; acceleration rate and body movement also increased. SDVM is classified as dancer performance based on the artist's facial expressions, stage performance, emotions. The simulation results show good results compared to other methods.
SuperCoder: Program learning under noisy conditions from superposition of states

We propose a new method of program learning in a Domain Specific Language (DSL) which is based on gradient descent with no direct search. The first component of our method is a probabilistic representation of the DSL variables. At each timestep in the program sequence, different DSL functions are applied on the DSL variables with a certain probability, leading to different possible outcomes. Rather than handling all these outputs separately, whose number grows exponentially with each timestep, we collect them into a superposition of variables which captures the information in a single, but fuzzy, state. This state is to be contrasted at the final timestep with the ground-truth output, through a loss function. The second component of our method is an attention-based recurrent neural network, which provides an appropriate initialization point for the gradient descent that optimizes the probabilistic representation. The method we have developed surpasses the state-of-the-art for synthesising long programs and is able to learn programs under noise.
Safety Properties of Hybrid System Product Lines

Hybrid systems are an important class of Cyber-physical systems. Hybrid systems are characterized by a combination of discrete and continuous dynamics. Over the last two decades, research has focused on formal techniques and tools for proving properties of hybrid systems, these techniques have matured to the point where they are ready for industrial application. An advantage of the existing formal techniques is their ability to prove safety properties over a range of model parameters and thus allow for results to be generalized to an entire product line. However, a critical barrier to industrial adoption of formal techniques is their integration with widely adopted industrial standards. This paper identifies “parameterized hybrid systems” as an extension of the existing notion of a hybrid system and provides a formal definition based on foundational theory from the domain of software product line engineering. Using this definition, an engineering procedure is proposed to aid in proving properties over many choices of system parameters for a product line. The proposed engineering procedure is discussed in the context of several widely adopted industrial standards (ISO 26262, DO-178C, and EN 50128) which contain gaps regarding the use of formal methods for proving safety of parameterized systems.
Peningkatan Aktivitas Dan Hasil Belajar Bahasa Indonesia Pada Materi Teks Eksposisi Melalui Model Contextual Teaching And Learning (CTL) Siswa Kelas X IS 3 SMAN 4 Banda Aceh

he purpose of this study was to increase the activities and results of Indonesian language learning in the exposition text material of class X IS 3 SMAN 4 Banda Aceh. The learning model used in this study is the CTL learning model. The subjects of this study were students of class X IS 3 SMAN 4 Banda Aceh. The number of students is 35 students with 16 male students and 19 female students. This research was conducted in the 2019/2020 school year for a period of 3 months, from August 2019 to October 2019 in the odd semester. The research methodology is Classroom Action Research (PTK) consisting of two cy-cles and each cycle consisting of two meetings. Each cycle consists of planning, implementing, observ-ing and reflecting. The data collection technique is to collect test scores that are carried out at the end of each lesson in each cycle using a question instrument (written test). Observation data was carried out by looking at the activeness of students in the learning process. Data were analyzed by means of percentage statistics. The results showed that there was an increase in student learning activities in both cycles, from good enough to good categories and to very good categories. Completeness of student learning outcomes has increased from 48.57% in the pre cycle increased to 68.57% in cycle I and increased to 88.57% in cycle II. The use of the CTL learning model can increase the activities and results of Indone-sian language learning in the exposition text material of class X IS 3 SMAN 4 Banda Aceh Academic Year 2019/2020
Distributional Semantics for CRM: Making Word2vec Models Robust by Structurizing Them

Distributional Semantics has become extremely popular in natural language processing (NLP) and language learning tasks. We subject it to critical evaluation and observe its limitations in expressing semantic relatedness of words. We spot-check representation of meaning by the Distributional Semantics and also obtain an anecdotal evidence about various systems employing it. To overcome the revealed limitations of the Distributional Semantics, we propose to use it on top of a linguistic structure, not in a stand-alone mode. In a phrase similarity task, only when phrases are aligned and syntactic, semantic and entity-based map is established, we assess word2vec similarity between aligned words. We add the Distributional Semantics feature to the results of syntactic, semantic and entity/attribute-based generalizations and observe an improvement in the similarity assessment task. Structurized word2vec improves the similarity assessment task performed by the integrated syntactic, abstract meaning representation (AMR) and entity comparison baseline system by more than 10%.