Reviewerly/exHarmony huggingface dataset:
EMOTION RECOGNITION ON SPEECH PROCESSING USING MACHINE LEARNING

Emotional intelligence in speech is the process of estimating one's emotions using various indicators obtained from speech.Although speaking is not easy and it is difficult to predict a person's emotions due to the subjective nature of emotions, "Speech Emotion Recognition (SER)" makes it possible.Understanding the logic of audio signals requires important steps such as feature extraction and classification.Tone of voice, pitch of voice, facial expressions, behaviour, and other situations can be used to predict a person's mood, some are used to predict emotions.These extracted features are called classifiers.Classifiers are trained to recognize emotional speech using small datasets.Emotions are very important to human psychology.It is a tool to convey an emotion or mood to another person.Emotion of speech recognition is the procedure of extracting a person's emotions from a speech wave.Any cognitive function with restricted processing capacity can be skilled to recognize or synthesize a bunch of general emotions (angry, neutral, happy, and sad) as required.Since the incorporeal and poetic features hold emotional details, they were used for speech recognition in this study, one of the incorporeal things is the Mel-frequency cepstral coefficient (MFCC) algorithm.Incorporeal elements used to express various emotions include key frequency, loudness, pitch, speech use, and guttural factors.Possible features are taken from each speech for analysis of personality and speech patterns.The selected features enable the perception of the sound and thus the classification of the gender.In this study, support vector machines (SVMs) were used to determine gender, based on selected features, demand is defined using radial basis and network regression.The radial base study has been shown to produce more accurate imaging results than the back propagation networks.
Utilization of the SAW Algorithm in Decision Support Systems for Determining Learning Strategies for Adaptive Learning

During the Covid-19 pandemic, where the teaching process is carried out online, adaptive learning can be an alternative choice in distance learning due to different conditions of each student with various learning instruments.Despite the many advantages of implementing adaptive learning in online learning and using digital materials, many teachers and students are not prepared for this sudden change.Not all teachers feel ready to make adjustments in carrying out distance learning and helping students optimally as when teaching directly in class.As a result, many students may find online learning materials too simple, or even very complicated.This of course results in treatment that is not in accordance with their needs so that learning outcomes are less than optimal.One solution to this problem is the use of IT-based learning technology which refers to the adaptive learning method.A decision support system (DSS) is built by applying the Simple Additive Weight (SAW) algorithm.From this, the teacher can obtain an overview related to the condition of the students as well as recommendations for treatment according to their condition.The system was tested in the distance learning process in the Informatics Education study program at Universitas Sebelas Maret.
Blockchain in the Natuna Tourism Industry: Opportunity and Challenges

In 2018, Natuna was designated as a National Geopark.However, the promotion of Maritime Tourism on the Natuna beaches is still inferior when compared to Bali, Bangka and Belitung.Currently, Natuna is being prepared by the regional and central governments to become a UNESCO Global Geopark.Some of the requirements that must be met are geological heritage, international recognition, management systems, geopark sites, domestic and international facilities and networks.Based on the results of the Focus Discussion Group with the Head of the Tourism and Creative Industry Office and their staff, the obstacles faced by Natuna are human resources as well as technology and data in tourism promotion.This article discusses the Blockchain application model in the Natuna tourism industry.The developed model provides convenience in storing and using data and other sources of information.This technology promises to increase transparency and security in transactions, so tourists who want to travel to Natuna don't have to worry about Blockchain bringing security and transparency to several important touchpoints.Blockchain can make booking flights and hotels more secure and transparent as responsibility spreads across the network.With blockchain, all information appearing on the network is public, reliable, and secure, achieving greater transparency and increasing consumer trust.By presenting a case study of the application of blockchain technology in Natuna tourism, the authors analyze the potential use of blockchain technology in the tourism industry and discuss topics for further research.
Tracking Javanese Cultural Heritage through Augmented Reality and its Implications in Indonesian Language for Foreign Speakers (BIPA) Learning

The development of Information and Communication Technology (ICT) in cultural heritage (CH) shows a very large impact at this time.In particular, it is about cultural heritage development uses the Augmented Reality (AR) technology.This study aimed to digitize the aspects of Javanese cultures (traditional clothes, houses, and weapons) and its implications in learning of Indonesian Language for Foreigners (BIPA).This current research used Thiagarajan 4D research and development design.The research was conducted through four (4) stages namely define, design, develop, and disseminate stages.The Augmented Reality development implemented the virtual buttons on each marker.Some markers were designed by using the Vuforia Software Development Kit (SDK).The 3D Unity and the Vuforia Engine SDK were used as the platforms to develop Augmented Reality software.The 3D objects were designed using the 3D blender app to imitate the traditional clothing, houses, and the traditional weapons.The results showed that this product has good sensitivity and is proven to be able to imitate object images.In addition, this product has implications and is interesting to use in the intermediate-level of BIPA learning on the cultural aspect.This research is important to do in addition to maintain, preserve, digitize the cultural aspects, as well as introducing Indonesian culture to foreigners.
A Comparison of Ant Colony Optimization and Depth First Search for Solving Unmanned Aerial Vehicle – Ground Vehicle Routing Problem in Humanitarian Logistics

Time is of the essence in disaster relief operation.The casualties might be huge if disaster relief operation can't be done quickly.The broken infrastructure and post-disaster environment make it difficult to search for survivors.To solve this, Unmanned Aerial Vehicle (UAV) is deployed since UAV can survey the location easily from the air.One downside of UAV is its limited energy capacity.UAV needs to be deployed with a Ground Vehicle (GV) who charges or swaps UAV battery during the operation.As such, the coordination between UAV and GV becomes an important part in the operation.This research focuses on constructing a route for the UAV -GV to find survivors using Ant Colony Optimization (ACO).The studied case is the 2010 Merapi eruption, which is one of the volcano eruptions in Indonesia.The result of this research will be compared with the result from previous research that used Depth-First Search (DFS).The route from ACO needs 90.48 minutes to complete whereas the route from previous research needs 95.48 minutes, implying that the route evaluated using ACO results in 5 minutes faster than that constructed using DFS.
Analysis of Japanese-Indonesian Translation Using Machine Translation

Translating Japanese to Indonesian using the Google translation engine is an easy thing.However, the results of the google translate translation must go along as possible with reasonable accuracy.This study aims to determine the accuracy of Google Translate translation in translating Japanese articles into Indonesian.The research uses combined research methods through literature studies from various literature sources.The theories used in this study are Machali's assessment theory (2009), Hartono's translation theory (2017), Bassnett-McGuire's addition and subtraction theory (1991), and the BLEU algorithm (2002).The data is taken from a speech of the Ambassador of Japan to Indonesia, taken from an official article on the embassy's website.The research found the correct semantic assessment value, incorrect semantic assessment value, type of semantic error, and the value of the BLEU algorithm assessment.Google translate can provide a correct result in terms of semantics or meaning.The average correct semantic value indicates this is around 88.03%.The assessment of the BLEU algorithm for google translate text gets an assessment result of 37.11.This average value includes a low value, which shows a significant difference in structure between the google translate text and the translator text.In other words, the results of google translate are suitable for conveying the meaning of the results of the translation.However, it is essential to improve the sentence structure of the results of Google Translations.
Decentralized Asset Marketplace

Abstract: The decentralized asset marketplace is a cutting-edge platform that simplifies the buying and selling of non-fungible tokens (NFTs) by providing a secure and transparent peer-to-peer trading platform. The marketplace is built on the Ethereum blockchain, ensuring that transactions are immutable, secure, and transparent. It allows users to buy, sell and trade NFTs using cryptocurrencies such as Ethereum and Bitcoin. The smart contract that powers the platform defines a MarketItem struct that represents an NFT on sale and has several functions to support trading. The platform is designed to provide a seamless user experience with fast and efficient transactions, and performance enhancements such as using IPFS to store NFT metadata. The platform's benefits include increased security, transparency, and cost-effectiveness, making it a significant breakthrough in the world of NFT trading. Overall, the decentralized asset marketplace provides a safe, secure, and efficient way for users to trade NFTs without intermediaries or complex transaction processes.
‘Co-Production’ of School Innovation: The Effect of School-Home-Community Partnerships Revisited

학교혁신은 한국사회에서 정책적으로 많은 관심을 받아온 주제이다. 이 연구는 신공공거버넌스론의 ‘공동생산’ 개념에 기초하여 학교혁신 가능성을 새롭게 조명한다. 시민 참여를 통한 공공 서비스의 공동생산이 서비스의 꾸준한 개선에 효과적으로 기여한다는 최근의 행정학적 관점을 차용하여, 학교-가정-지역사회 협력 파트너십이 단위학교의 혁신 역량을 강화하는 기제로 기능할 가능성을 실증적으로 살펴보고자 한다. TALIS 2018 조사를 통해 수집된 163개 국내 중학교 자료를 다각도로 분석한 결과, 학교-가정-지역사회 협력 파트너십은 학교의 혁신역량을 강화하는 데 직접적으로 기여할 뿐만 아니라, 학교의 혁신 역량에 미치는 협력적 학교문화의 효과를 증폭시키는 방식으로도 학교의 혁신 역량 강화에 기여하는 것으로 나타났다. 구체적으로, 학교와 가정 및 지역사회 간에 ‘연계적 소통’에 기반한 ‘참여적 결정’과 ‘협력적 수행’이 원활하고 활발할수록 이것이 학교의 혁신성 강화에 긍정적 여건을 제공하는 경향성이 관찰되었다. 이러한 결과는 자생적이고 지속가능한 학교혁신을 위한 여건을 모색하는데 있어 공동생산 개념이 유용성을 지님을 시사한다. School innovation is an important topic that has attracted great attention from educational researchers and policy makers. This study aims to shed new light on school innovation based on the concept of “co-production” in the public administration literature. Building on the emerging literature on the positive effects of co-production on public service improvement, the present study examines the possibility that school-home-community partnerships may function as a mechanism to enhance school innovativeness. TALIS 2018 data for 163 middle schools in Korea reveal that school-home-community partnerships not only directly strengthen school innovativeness but also amplify the effect of collaborative school culture on school innovativeness. Specifically, the higher the level of “participatory decision-making” and “collaborative performance” based on “networked communication” between school, home, and community, the more positive conditions are created to bolster school innovativeness. These results suggest that the concept of co-production is useful for school administrators to design conditions for sustained school innovation.
Measurement of thin film thickness using diffraction Lloyd mirror interferometer

Thin films are used in many applications including holography, integrated optical circuits, polarizers, low-pass filters, beam splitters, and antireflection coatings. Refractive index and thickness of thin films are important parameters to understand its optical characteristics. In this work, thickness of thin film is measured by diffraction Lloyd mirror interferometer (DLMI). This interferometer works on the principle of superimposing two diffracted waves and direct geometric waves to generate the interference pattern. In comparison to the conventional Lloyd mirror interferometer, the interference pattern obtained by proposed interferometer covers a large area due to the presence of diffracted light in almost 4π region. The main idea of this work is to check the feasibility of DLMI to measure the thickness of films in single step. Three different test samples containing different step heights are used as a Lloyd mirror. The fringe patterns obtained from intereference of direct diffracted wavefront and reflected wavefront from samples are recorded using CMOS sensor. Recorded fringe patterns were further processed to extract phase by the application of Fourier transform. The 3D and 2D line profile of retrieved phase information are utilized to find the thickness of the film. The measured values of the thin film thickness by DLMI are compared with that of a standard mechanical profilometer. The experimental findings verify the usefulness of the proposed method.
Generative-based AI and the possibility of Chinese language education revolution

Recently, the word convergence has become a hot topic. This word, which has been talked about in earnest since the 4th Industrial Revolution, is already pouring out concrete results, and we are required to create new values by connecting different areas. Now, we have to think about how to incorporate the tool AI into education and research. In addition, we need to redefine the definition of education as to what talent is needed in the future for global competition. The goal of education should not be to convey and learn specific knowledge, but to cultivate talented people with subjective thinking, correct value judgment, innovative ability, and above all, correct AI ethics. To this end, a re-examination of the humanities is required, and a convergence perspective in the educational and industrial circles must appear. In this paper, I would like to address the recent arrival of generative-based AI and the changes in education.
On the Lexical morphology and Semantics of Compound words: Focusing on the Chinese Cooking verbs

The morphemes in a word are related structurally and semantically. This study uses the notion of verbal morpheme, and a verbal morpheme with lexical meaning of cooking is a cooking verbal morpheme. Most Chinese cooking verbs are monosyllabic, consisting of a single verbal morpheme, which has concrete lexical meaning and strong productivity of word formation. The objects of this study are Chinese compound words formed by cooking verbal morphemes. This study aims to investigate the structural and semantic relation of the verbal morphemes, mainly investigating the lexical morphology in a specific word group with the cooking meaning. As a result, in Chinese, the relative compound words are rich in the number and types, and some of them have similar structure with Chinese phrasal structure. As for lexical morphology, the most productive type is modifier-core type. As for the meaning of the components, those with the related relation(关联关系) are the most productive. But original meaning relation(一致关系) is also quite productive. This means participating in word formation while maintaining the conceptual meaning as much as possible rather than the expanding meaning. The core meaning of most compound words are cooking, however, some of the compound words(熬, 涮) choose metaphorical meanings as its core meaning. It is widely used as a metaphor in our life.
Copy-Move Forgery Detection Using Texture Features of Hidden Forged Regions

The recent revolution in technology has not only eased our daily activities at work and home but also introduced new threats. In their daily activities, people exchange a lot of files such as text files, images, videos, etc. that can be used for a variety of purposes. One of the most common types of files is images. These kinds of files can be used to socialize people or spread knowledge among communities. Some of the exchanged images are fake or forged which can lead to the spread of misinformation, which is dangerous. This paper tries to suggest a method for image forgery detection that is copy-move-based. This means a part of the image is used to hide or change other parts in the same image. The suggested method divides an image into several blocks. The feature vectors of the blocks are extracted using a modified Gabor filter. The extracted features are, then, reduced using the principal component analysis technique. The next step is to match the blocks and extract similar ones (duplicated blocks). The findings show that the suggested method is efficient compared to other methods in the literature in terms of detection rate and false positive detection. Also, the proposed method detected forged regions of images when having a 60% of compression rate.
RESEARCH PAPER ON BLOCKCHAIN IN COFFEE SUPPLY CHAIN

The coffee Industry involves various actors throughout the supply chain process, some of the major actors include farmers, transporters/logistics, producers, distributors and retailers.Therefore, ensuring the quality and traceability of the coffee beans throughout the supply chain is a necessity in the existing coffee industry.However, it faces several challenges such as lack of transparency, data inconsistency, and vulnerability to fraud.To overcome these challenges, we propose a smart contract-based solution for coffee transport and traceability by using blockchain technology, the proposed system aims to enhance trust, transparency and efficiency in the coffee supply chain which will enable the various participants/actors to participate in the decentralized network in which the transactions and data will be recorded immutably on the blockchain.Therefore, by the implementation of these proposed solution, tracking of coffee shipments becomes possible and easier, allowing various actors to monitor the progress of the coffee beans at each stage without having to worry about the tampering of data as it is handled by blockchain, which ensures that the recorded data cannot be tampered with providing a reliable source of information for auditing, quality control, and compliance purposes.
ENHANCING THE TRAINING OF MODERN LEADERS IN THE MANAGEMENT SYSTEM OF HIGHER EDUCATION INSTITUTIONS

There is great interest in present-day leaders in the 21st century because of the widespread belief that the quality of leadership makes a significant difference to universities and student outcomes. There is also increasing recognition that schools require effective leader if they are to provide the best possible management system of higher education institutions. While the need for effective training contemporary leaders is widely acknowledged, there is much less certainty about leadership behaviors that are most likely to produce favorable outcomes. The researcher examines the underpinnings for the field of educational leadership and discuss the evidence of their relative effectiveness in developing successful universities especially during the periods of change. The research paper focuses on the improving of setting standards of training modern administration members in management system of higher education institutions (HEIs) and suggests a standard system for the modern leaders of education institutions according to competence-based approach to reÂ­spond to the current education reform. It is the authors strong believe that training of modern leaders of administrative staff of higher education institutions stimulate social vitality, which itself has an economic impact, drives innovation and productivity growth in global economy.
A Model is Worth Tens of Thousands of Examples

Traditional signal processing methods relying on mathematical data generation models have been cast aside in favour of deep neural networks, which require vast amounts of data. Since the theoretical sample complexity is nearly impossible to evaluate, these amounts of examples are usually estimated with crude rules of thumb. However, these rules only suggest when the networks should work, but do not relate to the traditional methods. In particular, an interesting question is: how much data is required for neural networks to be on par or outperform, if possible, the traditional model-based methods? In this work, we empirically investigate this question in two simple examples, where the data is generated according to precisely defined mathematical models, and where well-understood optimal or state-of-the-art mathematical data-agnostic solutions are known. A first problem is deconvolving one-dimensional Gaussian signals and a second one is estimating a circle’s radius and location in random grayscale images of disks. By training various networks, either naive custom designed or well-established ones, with various amounts of training data, we find that networks require tens of thousands of examples in comparison to the traditional methods, whether the networks are trained from scratch or even with transfer-learning or finetuning.
Building Geographic Information System Story Maps for Jakarta’s Local Community Health Infrastructures Awareness

COVID-19 is caused by the novel coronavirus SARS-CoV-2. First started in Wuhan, COVID-19 has spread everywhere, including Indonesia. COVID-19 can cause severe pneumonia, severe acute respiratory distress syndrome (ARDS) symptoms, and multiple organ failure. According to the WHO, COVID-19 generally has an incubation period of 5–6 days, ranging from 1 to 14 days. However, in Jakarta, the cases have decreased significantly since the implementation of PPKM (Restrictions of Activity), running since early July 2021. The government claimed that the PPKM rule has significantly impacted COVID-19 cases, decreasing every day, especially in Jawa-Bali Region. In addition, the Vaccination rate in Indonesia also played a significant part in decreasing COVID-19 cases, with Jakarta currently standing with 9 million people fully vaccinated per December 2021. To monitor the development of COVID-19 in Jakarta and provide information to the public about health facilities, especially hospitals in Jakarta, in this study, the distribution area of COVID-19 cases will be mapped with CHIME using ArcGIS Online tools. The analysis results obtained based on the mapping results that most cases were in the Cengkareng area, and the area with the most hospitals werein East Jakarta.