Reviewerly/exHarmony huggingface dataset:
Analisis Sistem Pembelajaran Daring (SPADA) dalam Mata Kuliah Menulis Teks Berbahasa Jawa

This study aims to analyze the Online Learning System (SPADA) in the Javanese Text Writing course. This type of research is a qualitative descriptive study using interpretive methods presented in the form of a description. The research subjects were students of the Java Language Education Study Program (PBJ) FKIP UNS semester II or the 2020 batch of 74 people. The sample was taken using a purposive sampling technique which only focused on students who were taking the MTBJ course in the even semester of 2021. The data collection technique used a questionnaire or questionnaire technique. The analysis technique used is data collection, data processing and giving conclusions. Data processing is presented in the form of a brief description or detailed narrative text. The data that has been obtained are categorized and then conclusions are drawn. The results showed that students got various conveniences and benefits, such as ease of remembering lecture history, improvement of IT skills, ease of sending assignments, ease of understanding theory and improving skills as well as increasing the effectiveness of the lecture process. The SPADA features or menus that are much favored by students while attending MTBJ lectures, which can increase the effectiveness of lectures are discussion forums, assignments, course materials, and my dashboard. Some improvements that must be made by SPADA are related to upgrading the system, added features, and lecturer skills improvement.
Podcast Berbasis Internet of Things (IoT) sebagai Media Pembelajaran Kompetensi Berbicara bagi Mahasiswa Pendidikan Bahasa &amp; Sastra Jawa FBS UNNES

This research was conducted to solve problems related to the Javanese speaking skills of PBSJ FBS UNNES students. For this reason, the development of IoT-based teaching media through podcasts is believed to be able to overcome these learning problems. Moreover, the development of the era provides space for the growth of information technology as a teaching medium that is easily accessible. Therefore, the formulation of this problem is proposed to answer the validity of research and development of IoT-based teaching media in the Javanese language achieved through R &amp; D adaptation of the Dick, Carey, &amp; Carey model. The results of this study are as follows. (1) IoT media speaking Javanese is able to answer the needs of research targets related to writing skills, creative power, and imagination. (2) Based on the validity test, satisfactory content validity was obtained for the Java language-speaking IoT media. For this reason, the product of this research can be used as teaching material, teaching media, theoretical foundation, as well as a reference for lecturers, students, or other researchers.
Penerapan Strategi Talking Stick dengan Media Kartu Berwarna Untuk Meningkatkan Aktivitas dan Hasil Belajar Aksara Jawa Kelas V SD Muhammadiyah 3 Ponorogo

&#x0D; This study aims to describe the application of the Talking Stick learning strategy with colored card media as an effort to increase student activity and learning outcomes in Javanese learning with Javanese script. The research was conducted in class V SD Muhammadiyah 3 Bungkal Ponorogo, amounting to 19 students. The method used was Classroom Action Research (CAR) developed by Kurt Lewin. This research carried out in two cycles, each cycle consisting of planning, action, observation, and reflection. The results showed that the application of the Talking Stick learning strategy using colored card media increased. This can be proven by its application by the teacher in the first cycle reaching 87.5% and in the second cycle, the success reached 92.5%. In cycle, I student activity reached 82.5%, and in the cycle, II increased to 92.5%. Student learning outcomes in the first cycle showed that the percentage of completeness in the class reached 84.21% and in the second cycle it reached 94.74%. These results increased compared to the results during the pre-cycle, where students' completeness only reached 52.63%.
Learning to Survive using Reinforcement Learning with MLAgents

Abstract: Simulations have been there for a long time, in different versions and level of complexity. Training a Reinforcement Learning model in a 3D environment lets us understand a lot of new insights from the inference. There have been some examples where the AI learns to Feed Itself, Learns to Start walking, jumping etc. The reason one trains an entire model from the agent knowing nothing to being a perfect task achiever is that during the process, new behavioral patterns can be recorded. Reinforcement Learning is a feedback-based Machine Learning technique in which an agent learns how to behave in a given environment by performing actions and observing the outcomes of those actions. For each positive action, the agent receives positive feedback; for each negative action, the agent receives negative feedback or a penalty. A general simple agent would learn to perform a task and get some reward on accomplishing it. The Agent is also given punishment if it does something that it’s not supposed to do. These simple simulations can evolve, try to use their surroundings, try to fight with other agents to accomplish their goal
Neural Machine Translation

Abstract: The project's novelty is not merely importing modules and preparing data and feeding the data to the model but understanding how the real language translation works and implementing the logics underlying each method utilized and creating every function from scratch, resulting in the creationof a Neural Machine Translation model. Initially, translation was accomplished by simply substituting words from one language for those from another. However, because languages are essentially different, a greater degree of knowledge (e.g., phrases/sentences) is required to achieveeffective results. With the introduction of deep learning, modern software now employs statisticaland neural techniques that have been shown to be more effective when translating. We are essentially translating German to English utilizing Sequence to Sequence models with attention and transformer models. Of course, everyone has access to Google Translates power, but if you want to learn how to implement translation in code, this project will show you how. We are writingour code from scratch, without using any libraries,in order to understand how each model works.While this design is a little out of date, it is still a great project to work on if you want to learn more about attention processes before moving on to Transformers. It is based on Effective Approaches to Attentionbased Neural Machine Translator and is a sequence to sequence (seq2seq) model for German to English translation.
Forensic Detection through the Identification and Collection of Data for Analysis

Forensic detection – identifying and collecting data for analysis detailed the key contribution forensic science is making in the discharge and or adjudication of criminal justice. The scope of forensic science was reviewed and the associated data collection techniques for analysis were discussed. Existing literature on the subject matter was reviewed and conclusions drawn. Some recommendations for policy and practices were made. Forensic science is often driven by specific issues and scandals (such as a miscarriage of justice), and resources are specifically deployed to address them (3). This means that forensic science is often reactive to “symptoms” that arise (4, 5), rather than engaging in continuous and systematic proactive examination, research, and self-reflection as routine practice. In addition, forensic science frequently works within the framework that “every case is different,” which creates a fundamental tension between research seeking to develop generalizable theories and approaches, and professional practices in crime reconstruction. Therefore, taking a longer term view of the possibilities and potentially desirable directions of the future of forensic science is an important undertaking. [4] Keywords: Data, Forensic Detection, Analysis, Reconstruction, Adjudication, Criminal Justice
Storing Forensic Data Against Interference

Digital forensic investigators face a wide range of inquiry goals, such as dealing with cybercrime. Digital forensic tools are no different. Different digital traces were examined on persistent storage devices (SSDs, SD cards, and USB drives), volatile memory snapshots, and network captures. A large realistic, timely training data is required to train experts, improve the forensic tools and keep their knowledge and capabilities up to date. However, there is a significant gap in digital forensic training data due to many factors such as privacy, secrecy, data protection, and intellectual property rights. Multiple frameworks for generating realistic digital forensic data sets have been proposed in recent years. None of these frameworks offers a comprehensive strategy for creating digital forensic tools, for relevant traces, from many sources. Keywords s: Data Storage, Cybersecurity, Cybercrime, Protection, Forensics, interference. BOOK Chapter ǀ Research Nexus in IT, Law, Cyber Security &amp; Forensics. Open Access. Distributed Free Citation: Amenuveve Gracious Adzogbley (2022). Storing Forensic Data Against Interference SMART-IEEE-Creative Research Publications Book Chapter Series on Research Nexus in IT, Law, Cyber Security &amp; Forensics. Pp 7-14. www.isteams.net/ITlawbookchapter2022. dx.doi.org/
Fuzzy Discriminative Block Representation Learning for Image Feature Extraction

Representation learning is widely used to project high-dimensional data to low-dimensional subspace for feature extraction in image recognition tasks. However, many related methods barely explore the fuzziness and uncertainty between data classes. Besides, the classical unsupervised sparse constraint weakens the evaluation of feature importance and neglects the preservation of discriminant information during sparse representation. To solve these issues, a novel fuzzy discriminative block representation learning (FDBRL) algorithm is proposed for image feature extraction. FDBRL aims to enhance the discriminability of subspace by designing effective constraints for projection learning. Specifically, based on the label information and the fuzzy relation between data, we construct a fuzzy block weight matrix and embed it into the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${l_{2,1}}$ </tex-math></inline-formula> norm regularization term to realize supervised sparse constraint for the representation learning. Next, the low-rank constraint is used to capture the inherent global structure information of data. Finally, we introduce a classification loss term with transformation matrix for joint optimization, such that the projection learning is not limited to number of classes, and the discriminative ability is further improved. Comprehensive experimental results on six benchmarks verify that our method achieves promising performance with other state-of-the-arts in both robustness and effectiveness.
The Strength of the Relationship of Self-Efficacy and Innovative Work Behavior

Organizations that want to maintain their position at a competitive level need innovative behavior from their members.Innovative behavior is indispensable in overcoming the ongoing challenges facing organizations.Increased innovative behavior can be built through strengthening self-efficacy.Confidence in the self-ability of members of the organization has a close relationship with actions in exploring opportunities, generating ideas, promoting and realizing them and reflecting on their professional work.The relationship between self-efficacy and innovative behavior is discussed implicitly in scientific journals, but only a few directly link the two variables.This meta-analysis study was conducted to determine the strength of the relationship between self-efficacy and innovative work behavior by measuring effect sizes in 7 international journals published in the last 10 years.The results of the analysis using the Random Effect model show that there was a significant positive correlation between self-efficacy and innovative behavior (z = 5.419; p < 0.001; 95% CI [0.300-0.639]).The effect of selfefficacy on innovative behavior is included in the moderate category (r = 0.469).This finding proves that self-efficacy has a positive and significant correlation to work innovative behavior.
Institutional Reforms and Entrepreneurial Gowth Ambitions

Institutional reforms have resulted in deep transformations of the global economy. Yet, accumulating insights about the effects of institutional reforms has been inconclusive and the theoretical development has been criticized to be largely lacking. Our study applies categorization theory to argue that flexibility- and stability-enhancing reforms may affect entrepreneurial growth ambitions in distinct ways, particularly depending on whether new versus established or innovative versus imitative entrepreneurs perceive specific reforms as an opportunity or a threat. We use a multisource and multilevel dataset including more than 1.5 million individuals from 65 countries covering 2002-2016. Our findings indicate that – on average – flexibility-enhancing reforms lead to higher growth ambitions yet they are particularly favored by established and imitative entrepreneurs. On the contrary, stability-enhancing reforms lead to higher growth ambitions of new and innovative entrepreneurs. With that, our study provides important theoretical and practical implications about the consequences of institutional reforms for different types of entrepreneurs.
Applying Network Analysis to Rethink How We Work

The current landscape of academic research on networks is exciting and innovative, often pushing the boundary on causal inference (endogeneity), computational and analytic techniques, and new data sources. The results of network analyses are also finding their place in analytics teams, HR departments and executive suites, acknowledging the reality that formal systems only capture a portion of the collaboration and communication occurring among employees. Increasingly, people with deep expertise in network methods are conducting this work from within organizations, reflecting a growing overlap and cross-fertilization between academia and practice. The convergence of people with ONA expertise, network data, and org challenges that lend themselves to ONA makes this an exciting time for everyone working in this domain. In this symposium we discuss challenges, draw inspiration from successful examples, and explore ideas for future work.
AI and Emerging Technologies Track: The Implications of Blockchain Technology for Business

Blockchain technology (BCT) has the potential to revolutionize many industries by enabling transactions among individuals anywhere in the world without relying on intermediaries (e.g., banks, agencies, and institutional actors) that historically have been required to establish trust between transaction parties. Many people associate BCT primarily with cryptocurrencies. However, BCT applications have now permeated a wide range of industries and contexts, such as food logistics, healthcare, insurance, and many others. This panel symposium assembles a group of management scholars that have research related to blockchain technology. Our intent is to highlight some of the first research on blockchain technology and have these researchers explain some of the possibilities that exist for high-quality research on blockchain technology.
Dealing with Uncertainty and Adaptivity: Agile Procurement Process for Agile New Product Development

In the development of new products that are characterized by high uncertainty and high adaptivity, an agile new product development process is often used. The benefits of an agile new product development process are often reduced when applying a traditional procurement process (e.g., Van Weele (2001)). Drawing on contingency theory, we predict that procurement processes must fit with their contingencies, task uncertainty and task interdependence (product uncertainty and adaptivity), to maximize performance. Furthermore, procurement processes need to be aligned to related processes such as the new product development process. We apply a design science approach to design an agile procurement process that is aligned with the agile new product development process and is capable of attaining the important new product development goals such as low costs, short time-to-market, and high quality. We develop the initial solution based on semi-structured interviews, implement the initial solution at a case company to refine the solution, and refine and validate it with further interviews. We contribute to the literature by developing an agile procurement process with its explanatory mechanisms and application domain, and by showcasing that the procurement process has to match its contingencies and related processes to maximize performance.
Aseptic Filling and Packaging for Retail Products and Food Service

Aseptic packaging is the principal part of aseptically manufactured food products. Unlike other conventional processing, the packaging containers must be sterilized separately with effective sterilants depending upon the filling machine, which is designed by the filler manufacturer. The sterile packages are then filled with sterile food under the sterile zone of filler in order to prevent microorganisms from contaminating the food product during filling and sealing process. Several types of packaging materials such as steal metal can, paperboard carton, plastic cup, plastic bottle, and flexible pouch can be used as aseptic packaging. There are many types of aseptic fillers based on the specific packaging system, including packaging types and sizes (retail and bulk packaging). In this chapter, current packaging materials used in today’s market with their sterilization technique and filling technology are discussed for retail products and food service. The demand for shelf-stable food has been steadily increasing over the years and it was further accelerated over the last two years due to the pandemic. The growth is mainly driven by the Asia-Pacific region and it is the largest as compared to other major regions. Europe and North America are the two other major markets for aseptically packaged food products. The packaging options and use of recycled materials, such as recycled PET and flexible packaging materials, have also made an impact on the market share for different aseptic products. However, from a sustainability perspective, there are recycling issues in the parts of the world where it is not fully established yet. As the aseptic processing and packaging technology continues to expand globally, there will be more demand on sustainable sources of packaging materials and sustainability in the manufacturing operations as well. Future needs of packaging innovation and sustainability for aseptic packaging are also reviewed.
Remote Data Auditing in a Cloud Computing Environment

In the current paradigms of information technology, cloud computing is the most essential kind of computer service. It satisfies the need for high-volume customers, flexible computing capabilities for a range of applications like as database archiving and business analytics, and the requirement for extra computer resources to provide a financial value for cloud providers. The purpose of this investigation is to assess the viability of doing data audits remotely inside a cloud computing setting. There includes discussion of the theory behind cloud computing and distributed storage systems, as well as the method of remote data auditing. In this research, it is mentioned to safeguard the data that is outsourced and stored in cloud servers. There are four different techniques of remote data auditing procedures that are presented here for distributed cloud services. There are several difficulties associated with data audit methods; however, these difficulties may be overcome by using a variety of techniques, such as the Boneh-Lynn-Shacham signature or the automated blocker protocol. In addition to that, other difficulties associated with distributed-based remote data auditing solutions are discussed. In addition, a variety of approaches might be researched further for further examination in order to find answers to these impending problems.
Identification of Forged Profiles in Online Social Networks Using Machine Learning and NLP

Abstract: Many people today use social networking sites as a part of their everyday lives. They create their own profiles on the social network platforms every day, and they interact with others regardless of their location and time. In addition to providing users with advantages, social networking sites also present security concerns to them and their information to them. We need to classify the social network profiles of the users to figure out who is encouraging threats on social networks. From the classification, we can figure out which profiles are genuine and which are fake. As far as detecting fake profiles on social networks is concerned, we currently have different classification methods. However, we must improve the accuracy of detecting fake profiles in social networks. We propose the use of a machine learning algorithm and Natural Language Processing (NLP) technique in this paper so as to increase the detection rate of fake profiles. This can be achieved using Support Vector Machines (SVM) and Naïve Bayes algorithms.
Development of Elementary Physical Education Net-type games Unit Based on Understanding by Design

본 연구는 UbD를 적용하여 체육과 경쟁 영역 네트형 게임(뉴스포츠) 단원을 개발 하는데 연구 목적이 있다. 본 연구에서는 2015 개정 교육과정을 기반으로 UbD의 3단계절차, 1단계‘바라는 결과 확인(Desired Results)’, 2단계‘수용 가능한 증거(Assessment Evidence)’, 3단계‘학습경험과 수업 계획(Learning Plan)’의 순서에 의하여 체육과 네트형 게임 단원을 설계하였다. 첫째, 1단계‘바라는 결과 확인’템플릿을 완성하였다. 경쟁 영역에 대한 교육과정 및 성취기준을 분석하고, 본질적 질문, 핵심 지식과 기능을분석하였다. 둘째, 2단계‘수용 가능한 증거 결정’단계에서는 UbD의 평가 개념을 적용한‘GRASPS’요소를 이용하여 1개의 수행과제와 루브릭을 개발하고, 기타 평가방법으로 자기평가, 동료평가, 구술평가 등을 제시하였다. 셋째, 3단계‘학습경험과 수업 계획’단계에서는 교수·학습 활동을 16차시로 구성하였으며‘WHERETO’요소를 활용한학습 경험과 수업을 계획하였다. 넷째, 교육과정의 성취기준-평가-수업이 일관성을 가지며 뉴스포츠 주제를 적용한‘프리테니스’단원을 개발하였다. 본 연구는 UbD를 활용하여 체육 단원을 설계한 결과 체육 교과의 지식의 구조를 이해하고 다양한 평가와 수업 설계의 전문성 및 재구성 능력을 향상시켜 학생들이 만족할 수 있는 수업을 진행할수 있도록 실천적이고 구체적인 자료를 제시하였다. 본 연구가 다양한 주제를 접목한체육 교과를 운영할 수 있는 예시 자료로 활용되기를 기대한다.This Study purpose to design elementary physical education unit Based on Understanding by design. In this study, based on the 2015 revised elementaty physical education curriculum, the three-stage of UbD, the first is desired result, the second is Assessment Evidence, and the third is Learing plan designed in order. First, desired result confirmation template was completed. Curriculum and achievement standards for competition were analyzed, and essential questions, core knowledge and skills were analyzed. Second, one performance task and an analytic scoreing rubric were developed using the‘GRASPS’to which the UbD evaluation concept was applied, and self-evaluation, peer-evaluation, and oral-evaluation were presented as various evaluation methods. Third, learning plan were composed of 16 sessions, and learning plan were planned using the‘WHERETO’. Fourth, the ‘Free Tennis’ unit was developed with a new sports theme with consistent achievement standards-evaluation-classes. As a result of designing a physical education unit applying UbD, practical and specific materials were presented so that students could conduct a class that could satisfy them by understanding the structure of knowledge in the physical education subject and improving the professionalism and reorganization ability of various evaluations and unit design. It is expected that this study will be used as an example material that can operate a physical education curriculum that incorporates various themes.