Reviewerly/exHarmony huggingface dataset:
A Transistor Operations Model for Deep Learning Energy Consumption Scaling Law

Deep Neural Networks (DNN) has transformed the automation of a wide range of industries and finds increasing ubiquity in society. The high complexity of DNN models and its widespread adoption has led to global energy consumption doubling every 3-4 months. Current energy consumption measures largely monitor system wide consumption or make linear assumptions of DNN models. The former approach captures other unrelated energy consumption anomalies, whilst the latter does not accurately reflect nonlinear computations. In this paper, we are the first to develop a bottom-up Transistor Operations (TOs) approach to expose the role of non-linear activation functions and neural network structure. As there will be inevitable energy measurement errors at the core level, we statistically model the energy scaling laws as opposed to absolute consumption values. We offer models for both feedforward DNNs and convolution neural networks (CNNs) on a variety of data sets and hardware configurations - achieving a 93.6% - 99.5% precision. This outperforms existing FLOPs-based methods and our TOs method can be further extended to other DNN models.
ANALYSIS OF DEEP LEARNING MODELS FOR TEXT IN-FORMATION CLASSIFICATION TASKS

Text analysis as a whole is a new field of study. Fields such as marketing, product management, research, and management already use the process of analysing and extracting information from textual data. In the previous post, we discussed text classification technology, one of the most important parts of text analysis. Text classification or text categorisation is the activity of labelling texts in natural language with appropriate categories from a predetermined set. To put it bluntly, text classification is the process of extracting generic tags from unstructured text. These generic tags come from a set of predefined categories. Categorising content and products helps users easily find and navigate to a website or app. Text classification, also known as text categorisation, is a classic problem in natural language processing (NLP) that aims to assign labels or tags to text units such as sentences, queries, paragraphs, and documents. It has a wide range of applications, including question answering, spam detection, sentiment analysis, news categorisation, user intent classification, content moderation, and more. Text data can come from a variety of sources, including web data, emails, chats, social media, tickets, insurance claims, user feedback, and customer service questions and answers. The text is an extremely rich source of information. But extracting useful data from text is usually difficult and time-consuming due to the unstructured nature of natural language information. Deep learning based models have surpassed classical machine learning based approaches in various text classification tasks, including sentiment analysis, news categorisation, question answering, and natural language inference. In this paper, we provide a comprehensive review of most widespread deep learning based models for text classification developed in recent years, and discuss their technical contributions, similarities, and strengths.
SISTEM PENDUKUNG KEPUTUSAN UNTUK PENYELEKSIAN CALON PENERIMA BANTUAN PROGRAM INDONESIA PINTAR MENGGUNAKAN SIMPLE ADDITIVE WEIGHTING

The "Program Indonesia Pintar" (PIP) is a program from the Indonesian government to help children from poor families to get the proper education. Schools often deal with obstacles when selecting the students who are eligible for the PIP grant, due to the process of collecting and managing many registration files, thus requiring high accuracy to prevent errors in the selection results. Therefore, this research aims to develop a website of Decision Support System to support the tasks of the PIP recipient selection committee. The Decision Support System applies the Simple Additive Weighting (SAW) method to obtain the selection results from the ranking of the requirements data handed over by the applicants for the selection of PIP beneficiaries. Then this research applies the Waterfall software development method to analyze, design and develop the Decision Support System website. Furthermore, the results of the black box test indicate that the functions of this Decision Support System work according to their objectives. The system can manage the selection registration data and generate the rankings of prospective PIP beneficiaries.
Learners reflection on collaborative project in project-oriented problem-based learning for software engineering courses

This study aims to promote the initiative to incorporate collaborative case study as an integrated project in different courses, using the designed Project-Oriented Problem-Based Learning (PoPbL) framework as a basis. The generic Software Engineering (SE)-PoPbL framework was improved and adapted to integrate the collaborative case study. This allows for the assimilation of the project element into the different courses in the SE undergraduate program. This paper reports a three-year implementation experiences (2017-2019) of the collaborative project over two courses in the Computing's SE program: (i) Requirements engineering and software modelling (RESM) (ii) Introduction to SE. Data collected through survey showed promising and positive feedback from students who participate in the study. Further work on presented data-driven using thematic analysis would complement the quantitative results for better themes definition related to the learner's reflections.
Open Science, Research Assessment and HSS (Humanities and Social Sciences)

This conference on open science is covering many aspects of strategic relevance to build the future of Europe, a future based on knowledge leading to more opportunities for younger generations to express their talent in attractive research careers, be it in universities, research organisations or industry.Some sessions will be dedicated to discussing the assessment of research and researchers' performance, which affects their behaviours.This debate is timely and justified.Most researchers are used to measuring in their labs when collecting and processing data.Scientists have to measure with accuracy to produce reliable and verifiable results.The Nobel laureate Richard Feynman started one of his famous lectures challenging his students about the complexity introduced over the centuries by using different measurement units.Measuring research and researchers' performance is of a different nature and more complex in many ways.It has direct impact on people and a far-reaching policy dimension for the European Research Area.We therefore agree on the need to ensure objectiveness and fairness as guiding principles and we can use assessment methodologies to support broader policy objectives, considering that we live in times of change, including in the scientific methods and the public perception of the role of science.Research processes are in constant evolution, accelerated by the current pandemic and the transition to a resilient, green and digital economy and an inclusive society.The variety of activities making increased use of advanced technologies puts us in a situation where research deliverables are richer and not limited to delivering and counting publications.Modern science delivers other outputs, mostly digital, like datasets, software, algorithms or protocols, and it delivers highly skilled people through specialised education and mentoring.Multidisciplinary collaborations are required to address new scientific questions arising from increased complexity and that is another aspect of this evolution.More and more researchers from different domains, from biology and physics to economics, anthropology or humanities, work together in the boundaries of areas of knowledge.One of the actions included in the first Policy Agenda for the European Research Area, for the next three years 2022-2024, is to advance towards the reform of the assessment system for research, researchers and institutions to improve their quality, performance and impact.We consulted a variety of stakeholders in 2021, including organisations representing researchers, public funders, private funders, universities, research centres, academies, national evaluation agencies and policymakers, and we received strong support for the objective of ensuring a combination of qualitative and quantitative indicators to evaluate research and researchers without compromising on objectivity and peer review.
Implementasi Metode K-Nearest Neighbor (K-NN) untuk Analisis Sentimen Kepuasan Pengguna Aplikasi Teknologi Finansial FLIP

The phenomenon of technological development can transform systems in various sectors to provide efficiency and convenience at a lower cost, including the financial sector. Flip is a financial service application that makes it easy to transfer money between banks without administrative fees. By the end of 2021, the Flip will have a 4.9 rating on the Google Play Store. The purpose of this study was to analyze user sentiment towards the Flip app to see if flip user ratings were as positive as the ratings received. This study uses a set of text mining processes on the user rating data of the Flip app on the Google Play Store, using the classification algorithm K-Nearest Neighbor with TF-IDF weighting. The results show that 77.67% of the test data are correctly classified as positive evaluation classes, with high accuracy and recall rates of 82.67% and 86.92%, respectively. In addition, from the results of applying the Flip user rating data classification method, the comparison between training data and test data is 80%:20%, and the classification accuracy using the K-Nearest Neighbor algorithm is 76.68%. User reviews of the Flip app have shown positive results, as well as the ratings obtained in the Google Play Store and the K-Nearest Neighbor algorithm, TF-IDF weighting process used to analyze user sentiment towards the Flip app.
Visualisation of research trends in proximity sensors

A wide variety of application are possible with proximity sensors. This paper consolidates the research trends through a bibliometric analysis of research on proximity sensors. The key authors, regions and research organisations were focused on this review. The top authors were Suzuki Y. and Cattuto C and Sungkyunkwan University was the most influential research organisation. The leading country was United States of America. The future agenda for research was recommended in this paper.
DIGITAL TECHNOLOGIES IN PROFESSIONAL AND PEDAGOGICAL DEVELOPMENT OF A TEACHER

The article characterizes digital technologies in the professional and pedagogical development of a teacher. The purpose of the article is to reveal the content of digital technologies in the professional and pedagogical development of a teacher; to analyze the potential of innovative forms of professional development of teachers. The following research methods are used in paper: analysis of scientific literature on the research problem; interpretive-analytical method, synthesis, systematization, generalization. It is noted that the use of digital technologies or Internet resources in the teaching of various disciplines is now considered one of the most topical issues in education. The main effective solution to this issue is the use of electronic publications of educational complexes and educational materials. It is claimed that cloud computing has a high potential for optimizing the professional development of teachers. It caused a real revolution in education, encouraging teachers to improve themselves. Cloud computing is defined as technologies that provide Internet users with access to server computer resources and the use of software as an online service. With regard to pedagogical orientation, cloud computing is interpreted as a system of processing and storing educational information, which contributes to its assimilation by participants of pedagogical activity. It is proved that the above mentioned technologies are valuable because they provide free access to information, educational materials, promote the use of video and audio files in the educational process. There is a practice of active use of online lessons, webinars, integrated practical classes, laboratory work. New opportunities for scientific work open up, in particular, group, collective research, interactive project activities, as well as trainings, online communication with fellow teachers, etc. It is determined that the opportunity to work on joint educational and research tasks provides subject-subject interaction for educational purposes, enables the teacher to discover ways of using information and communication technologies in education, using various devices, such as smartphones, tablets etc. Therefore, all participants of the educational process can work together on tasks and various projects in real time.
Effective Planning in Resource-Competition Problems by Task Decomposition

Effective planning while competing for limited resources is crucial in many real-world applications such as on-demand transport companies competing for passengers. Planning techniques therefore have to take into account possible actions of an adversarial agent. Such a challenge that can be tackled by leveraging game-theoretical methods such as Double Oracle. This paper aims at the scalability issues arising from combining planning techniques with Double Oracle. In particular, we propose an abstraction-based heuristic for deciding how resources will be collected (e.g. which car goes for which passenger and in which order) and we propose a method for decomposing planning tasks into smaller ones (e.g. generate plans for each car separately). Our empirical evaluation shows that our proposed approach considerably improves scalability compared to the state-of-the-art techniques.
PENYEDIAAN SUMBER DAYA LISTRIK BERBASIS SOLAR SEL DI GEREJA GPDI BUKIT HERMON TO’ LIMBONG LEMBANG TONDON, KECAMATAN TONDON, KABUPATEN TORAJA UTARA

Without electrical energy, electronic equipment cannot be used as a work aid to meet human needs. The GPDI Church of the Bukit Hermon To' Limbong Congregation, is one of the houses of worship whose location is not yet reached by the PLN electricity network. To get electrical energy, it still takes a long time because they are waiting for the plan to add electricity to the church site. The church already has several electronic devices such as sound systems and pianos that were donated by the congregation. However, these tools cannot be used because electrical energy is not yet available in the church. To meet the electricity needs in the church, solar cell-based electrical energy is provided. Service activities are carried out using the method of applying solar cell technology by installing solar panels. The function of the solar panel is to convert solar energy into direct current electrical energy which is then converted into alternating current electrical energy. With the installation of a 160 Wp solar panel, the electricity source is already available, in the Bukit Hermon GPDI church so that the electric lighting in the church is lit during the day and at night. Electronic devices that have not been used before, can already be functioned properly when carrying out activities
Blockchain Technology, Trust &amp;amp; Confidence: Reinterpreting Trust in a Trustless System?

This report provides an in-depth analysis of the theoretical foundations of the concepts of trust and confidence and their correlation to the notions of risk, agency and legitimacy. These theoretical underpinnings are thereafter applied to permissionless blockchains, in order to identify how the foundational nature of the technology lends itself to bridging traditional paradigms in generating greater trust and confidence amongst users. We first review the literature which distinguishes the concept of trust from confidence before turning to major scholarly contributions on interpersonal trust, system trust and trust in technology. This literature has been examined through the lens of a multi-disciplinary reading group, which subsequently brings to bear practical and philosophical considerations in the use of blockchain technology in the modern world. The report concludes by providing the key areas in which trust can be reinforced, identifies the limitations of traditional factors as a measure for building trust with a decentralised and pseudonymous environment and clearly defines the differing levels of trust and confidence which are required within an on-chain and off-chain governance structure and its nexus to engendering legitimacy.
USING ADVERTISEMENT IN ENGLISH LANGUAGE TEACHING TO INCREASE LISTENING COMPREHENSION SKILL AT JUNIOR HIGH SCHOOL 3 BONTOMARANNU

This research aimed at finding out the increase of students’ listening skill in terms of accuracy of answer by using Advertisement at eighth Grade students of SMP Negeri 3 Bontomarannu. The Researcher used a quantitative method with one group pre-test and post-test; the researcher used a pre-experimental design. The findings showed that Advertisement was effective to increase students’ listening skill. It was supported by the students mean score in pre-test was 45.00 and it was increase to be 84.09 in post-test and the value of t-test was higher rather than the value of t-table (6.919 &gt; 1.720). Therefore, the Alternative Hypothesis was accepted and the Null hypothesis was rejected. Based on the result analysis, the researcher concluded that advertisement increase students’ listening skill
Implementasi Watermarking pada Citra Digital dengan Metode Singular Value Decomposition (svd)

Today computers have been used in all aspects of life as a means of processing digital data. The Development of computer makes digital files mostly used because the computer is an electronic equipment used to process digital file. Moreover with network technology developments internet it enables file exchange and process the file.This ease impacts to copyright, so that needs to be considered the protection of copyrights. Such protection insertion namely with a proprietary identity against certain files.one of them is watermarking technique. There are several techniques of digital watermarking which have developed. One technique is digital watermark image on singular value decomposition (svd), ie insertion a singular image. Watermarking method using singular value decomposition (svd) leads the overall in scattered watermark image, so that when the slightest changes occurred on with easy image can be known. In addition itu resistant against different attacks, such as croping, rotation changes. The author discusses about the digital image watermarking based svd. In making application he uses delphi 7.Keywords: Digital Image, Watermarking, Singular Value Decomposition.
Research Design and Analysis Methods

In this chapter, the author illustrates the framework for analyzing the two analytical issues raised in this book. In order to optimize the supply and demand balance of development resources, the author examines continuous development activities from two perspectives: supply and demand for development resources. The author focuses on the online game industry in China as the subject of investigation. The four main reasons for this include product complexity, rapid environmental change, continuity of development activities, and the limited development resources available to companies in emerging economies.
Combined algorithm for training neural networks of direct propagation

The essence of learning neural networks of direct propagation is to minimize the function of the root mean square error of the output. This function is multimodal, ie it has several local minima. To find the minimum of such functions, gradient and stochastic methods are most often used, which do not guarantee finding the global minimum. The article analyzes the gradient algorithm of inverse error propagation and the stochastic method of particle swarm for training neural networks of direct propagation, their advantages and disadvantages are indicated. It is proposed to combine the advantages of both methods in a combined algorithm.The learning process using a combined algorithm is carried out in two stages. At the first stage, the stochastic method of particle swarm conducts a given number of learning epochs and determines the set of points in the vicinity of which there may be points of local minimum. In the second stage, the gradient backpropagation algorithm finds the local minimum for each point and selects the optimal one. If the set value of the standard error of the output is not reached, the learning steps are repeated.To evaluate the effectiveness of the proposed approach to the training of neural networks, a series of comparative experiments using the well-known database of computer attack recognition KDD Cup 1999 Data. The experiments compared the results of training the direct propagation neural network for the particle swarm method, the inverse error propagation algorithm, and the combined algorithm. The experimental results proved the superiority of the combined algorithm.
An Analysis of Students’ Reading Comprehension Difficulties during Covid-19 Pandemic with Online Classes in Junior High School

This study aimed at finding out the junior high school students' difficulties in reading and students' attempts to overcome their reading difficulties during the covid-19 pandemic. This study used a qualitative method with a descriptive approach. The research participant took from six students in junior high school in Karawang with different levels from high, middle, and high levels, each level took from two students. The data on students’ reading comprehension difficulties were collected through observation, interviews, and documentation. The results show that students’ reading comprehension difficulties were affected by internal factors and external factors. and the use of the internet became the media for students’ attempts to deal with reading difficulties.
Pengaruh Waktu Penambahan Doping Fluor terhadap Luas Permukaan dan Struktur Nanotitania dengan Menggunakan Metode Sol-Gel

F-dop ed TiO 2 has been synthesized using the solgel method using NH 4 F as a source of fluorine. This study aims to determine the effect of adding variations in the rate of doping fluorine during 0, 30, 60, 90 and 120 minutes using an injection pump to the formation and change of crystal structure and specific surface area of TiO 2 . Titanium isopropoxide (TTIP), tween-80, isopropyl alcohol and NH 4 F are used as the main ingredients in the synthesis of nanotreans. The F-TiO 2 powder was then calcined at 450 °C for 5 hours. The powder was tested for characterization using (X-Ray Diffraction) XRD and (Surface Area Analyzer) SAA. The XRD characterization results showed that all samples had purely anatase phases. XRD analysis on sample F-01 with a drop rate of 0 minutes obtained the largest particle diameter of 14.21 nm. Whereas the sample F-04 with a dropping rate of 90 minutes obtained the smallest particle diameter of 11.60 nm. The results of the SAA characterization in sample F-01 with a drop rate of 0 minutes obtained the smallest surface area of 68.845 m 2 /g. Whereas in sample F-04 with a dropping rate of 90 minutes the largest surface area was 103,585 m 2 /g .
State-Set Search

State-set search is state space search when the states being manipulated by the search algorithm are sets of states from some underlying state space. State-set search arises commonly in planning and abstraction systems, but this paper provides the first formal, general analysis of state-set search. We show that the state-set distance computed by planning systems is different than that computed by abstraction systems and introduce a distance in between the two, dww, the maximum admissible distance. We introduce the concept of a multi-abstraction, which maps a state to more than one abstract state in the same abstract space, describe the first implementation of a multi-abstraction system that computes dww, and give initial experimental evidence that it can be superior to domain abstraction.