Reviewerly/exHarmony huggingface dataset:
Is tonal language a problem for speaker identification (SPID)?

The availability of numerous technologies has led to an increase in the usage of bioinformatics in recent years. Siri, Alexa, and other artificial intelligence systems assist us in our daily lives. Voice recognition systems are used to confirm an individual's identity based on particular elements retrieved from his or her voice. In this regard, the current study attempted to assess the proportion of speaker identification in tonal language speaking persons. The study included 20 participants in the age range from 20 to 40 years. All participants were given a few phrases to speak and were recorded. PRAAT software was used to analyze the obtained data. A vector was developed by using the first two formants, which was then utilized to calculate the percentage for speaker identification. From small sample size to bigger sample size, three groups were formed: A-5, B-10, and C-20 speakers. In a lower sample size, results showed a benchmark of 65% for vowel /i:/, which is better for SPID, 60% for /a:/, which is above chance level, and 45% for /u:/, which is below chance level. The authors stated that increasing the sample size has an influence on speaker identification.
Rope Jumping Strength Monitoring on Smart Devices via Passive Acoustic Sensing

Rope jumping, as a fitness exercise recommended by many sports medicine practitioners, can improve cardiorespiratory capacity and physical coordination. Existing rope jump monitoring systems have limitations in terms of convenience, comfort, and exercise intensity evaluation. This paper presents a rope jump monitoring system using passive acoustic sensing. Our system exploits the off-the-shelf smartphone and headphones to capture the user's rope-jumping sound and breathing sound after exercise. Given the captured acoustic data, the system uses a short-time energy-based approach and the high correlation between rope jumping cycles to detect the rope-jumping sound frames, then applies a dual-threshold endpoint detection algorithm to calculate the number of rope jumps. Finally, our system performs regression predictions of exercise intensity based on features extracted from the jumping speed and the mel spectrograms of the user's breathing sound. The significant advantage of the system lies in the solution of the problem of poorly characterized mel spectrograms. We employ an attentive mechanism-based GAN to generate optimized breathing sound mel spectrograms and apply domain adversarial adaptive in the network to improve the migration capability of the system. Through extensive experiments, our system achieves (on average) 0.32 and 2.3% error rates for the rope jumping count and exercise intensity evaluation, respectively.
Malaria disease detection system based on convolutional neural network (CNN)

Traditionally to diagnose malaria and compute the parasitemia, a microscope is being used, which involves the use of thick and thin blood smears. However, the efficiency in examining the blood smear depends on the expertise of the laboratory technician in classifying the blood smear using the natural eye, through observation on the microscope as this may produce inaccurate reports due to human errors and offer less classification accuracy for novice laboratory technicians with less experience. In order to carry out a highly, accurate diagnosis of malaria. This paper presents a mobile malaria disease detection system based on Convolutional Neural Network (CNN), a class of Deep Learning (DL) algorithm with end-to-end feature extraction and classification. It is highly scalable and offers superior results in image classification problems, this would be used in training a classification model and deploying the model in a Mobile App. The Mobile App would then be used to diagnose malaria by using the device camera to take photo of patient blood smears for the model to classify, and give result output. Structured System Analysis and Design Methodology (SSADM) was adopted in the design of the research. The Malaria diagnosis system was developed using the JAVA Mobile Edition (ME) programming language and Python programming language to train the model and deployed in the developed software. The developed software meets the objectives of the system.
E-FARMING IMPLEMENTATION EFFECT ON SUPPLY CHAIN PERFORMANCE OF SUGAR CANE COMMODITIES IN A PLANTATION COMPANY

Information technology has been developed by many companies to achieve supply chain performance, E-farming is an application developed to register own sugarcane land/cane people and monitor the progress of plant work based on web and mobile application (android) supported by GIS and satellite technology. The research used is a quantitative method using survey methods through distributing questionnaires to e-farming actors/users at PTPN X. Survey research is research conducted on large and small populations, but the data studied are 352 samples from the population. Analysis using Structural Equation Modeling (SEM) with Smart PLS 3.0 software. The calculation results show that there is a positive and significant effect on the implementation of e-farming on supply chain performance. This means that to improve Supply Chain Performance, it is necessary to increase the role of the application of E-Farming technology, especially application tools can be developed to increase the effectiveness of the company's business processes.
Clusters

Not all data sets have explanatory variables and outcomes. The data may nevertheless contain associations that are worth revealing.
Penerapan Algoritma Sentimen Analysis dan Naïve Bayes terhadap opini pengunjung di tempat wisata pantai Pintu Kota, Kota Ambon

In the current development of information technology, sentiment analysis is often used as a tool to seek public opinion about something. Naive Bayes analysis is a method of classifying data based on simple probabilities and is designed to be used with the assumption that there is no interdependence between one class and another. The purpose of this study was to determine public opinion about visitor satisfaction at Pintu Kota Ambon by testing positive and negative recall values, as well as positive and negative precision values ​​and accuracy values ​​using sentiment analysis and naive Bayes analysis. All data are processed using RapidMiner tools. In this survey, we obtained data from the results of the search for comments from visitors to the Pintu Kota Ambon attraction on the Google Maps website. The results obtained from this study indicate that the tracking of sentiment analysis and Naive Bayes analysis of the opinions of 113 visitors showed a negative recall value of 97.62% and a negative recall value of 83.33%.The negative accuracy value is 85.42%, while the positive accuracy value is 97.22% From these results obtained an accuracy value of 90.65%.From the results of the analysis, tourist destinations at Ambon City Gate are considered good because they get a high accurate value of 90.65%. From this research, it can be concluded that it is necessary to develop an information system to track visitor satisfaction in other tourist destinations.&#x0D;
Analisis Rekaman Suara Magic Call pada Provider Seluler dengan Rekaman Suara Asli.

Abstract&#x0D; Magic call is a voice changer modification service from the provider that allows you to change the original voice when calling. This study was conducted to analyze the characteristics of the similarity level of magic call voice recordings on Telkomsel and XL providers with original voice recordings for forensic audio purposes. The voice recordings of magic call Telkomsel and XL use 4 voice recording samples consisting of 2 women and 2 men using their original voices. The data were analyzed using pitch, formant, and spectrogram analysis techniques. The data were then extracted using praat and gnumeric tools. The findings in this study showed that the four-voice recordings of 2 women and 2 men from magic call were compared with the original voice recordings showing non-identical results. This can be seen from the analysis results table which shows that 13 words from the sound recordings have very high non-identical values compared to identical values. It can be concluded that the magic call on Telkomsel and XL providers are not identical.&#x0D; &#x0D; Keywords— Forensic Audio, Sound Recording, Provider, Magic Call. &#x0D;
Pendampingan Penulisan Karya Tulis Ilmiah Bagi Guru-Guru PAUD KKG Gugus Tulip Kabupaten Banjar

The teacher can communicate ideas, ideas, results from research through scientific work. Teachers who are able to write scientific papers are the main thing in developing as professional teachers, but in fact there are still many teachers who have low knowledge about writing scientific papers, this is due to the lack of teacher creativity in developing the results of activities carried out in the classroom. The purpose of the service activities carried out is to provide knowledge and writing skills of PAUD teachers of the KKG Tulip Cluster, Banjar Regency regarding the writing of scientific papers. This method of service is through lectures, questions and answers and discussions of problem analysis, as well as pre-tests and post-tests. Mentoring activities are carried out online through zoom cloud meetings. The participants were 29 PAUD teachers of the Tulip Cluster, Banjar Regency. The results of the training showed that participants were able to write scientific papers properly and precisely, at the end of the activity participants produced scientific papers.
Content and Context Based Analysis of University Social Media Engagement

Social media has become an essential tool for institutions to create interactions with their users. Creating successful and relevant material for social media content is challenging as institutions struggle to comprehend what drives user engagement. Using analytics on user-generated social media material to determine the relation between post features and user engagement becomes a method for overcoming this challenge. In this study, engagement is measured based on a quantitative approach to the number of likes and comments. We applied machine learning algorithm to extract contextual features (time of post) and content features (caption and image classification) from university Instagram posts, and their influence on user engagement is statistically modeled. LASSO regression is applied, which is an effective strategy for automated variable selection. The results indicate that context features around 13:00 on Sunday, during the month of June, and content features containing the words "Gedung" and "Foto," as well as image classifications of "Sight" and "Sadness," will receive more likes and comments.
Complicating Futures

As futures become an increasingly central question for anthropologists, new conceptual and methodological tools, approaches and modes of engaging with stakeholders in research are needed. In this chapter, we take a new step in this dimension of futures anthropology. We outline and discuss how anthropologists might intervene conceptually and practically, by making ethnographic alliances with stakeholders in our research and ‘complicating’ the ways that the shared futures which are at stake are imagined. In doing so, we advance the conceptual discussion in a future-oriented anthropology through examining the potentialities and limits of future as a concept in the methodological design of ethnography, in fieldwork and in analysis. To do this, we discuss ethnographic insights developed from co-envisioning with qualified tech workers. We draw on fieldwork undertaken during different stages of the design process of Internet of Things and artificial intelligence, and our analysis of how tech designers’ practices of ‘focusing on’ or ‘sketching’ the future of market labour in technological design differ from the dominant imaginary of the dramatic changes these emerging technologies will bring.
Introduction

This introductory chapter presents a move towards An Anthropology of Futures and Technologies. It joins recent arguments made by the authors and their colleagues, in what is fast becoming a movement which argues that thinking critically about technologies and possible, plausible and impossible futures is insufficient. Instead, insisting that anthropology must now propose alternative ways, rooted in ethnography, to approach and engage with what is coming and to contest dominant narratives of industry, policy and government. In doing so, the Introduction discusses both methods and horizons for an anthropology of futures and technologies. It introduces the ten chapters and their cross-cutting arguments, as they examine theoretically and ethnographically – from a very tangible and situated perspective – how new technologies come about, and people and technologies participate in constituting futures that cannot be predicted or necessarily imagined. Turning to early works in the field, it raises questions about our relation to technology. It both highlights our futures with specific technologies and questions the ‘essence’ of technology in terms of how our relationship to it becomes a specific ‘enframing’ in Heidegger’s term, something that dominates how we perceive the world.
Efektivitas Program pada Pelayanan Publik E-Parking di Taman Bungkul Kota Surabaya

This study aims to describe the level of program effectiveness in e-parking publik services at Taman Bungkul Surabaya City which was launched by the Surabaya City Government through the Surabaya City Transportation Service. E-parking is an e-government program launched with the hope of being able to meet the needs of the people of Surabaya in the parking sector. The reason underlying this research is that the Surabaya City Government answers various parking problems that are complained by the community by implementing a technology-based parking service program, namely parking meters. With this parking meter, he hopes to be able to provide solutions to parking problems in the city of Surabaya. Therefore, there are indications of wasting the regional budget (APBD) if this program does not run in accordance with what the Surabaya City government wants. This study uses a descriptive method with a quantitative approach. Respondents in this study amounted to 100 people. The sampling technique used is incidental sampling technique. In this study, researchers used 4 (four) data collection techniques, namely questionnaires, observation, interviews and documentation. The data obtained were then tested for validity through the product moment correlation test using the SPSS 26 application, then the data that were declared valid were presented and analyzed. The data analysis technique in this study uses frequency distribution. The data evidence is in the form of respondent's questionnaires, photos, and also interview transcripts. Based on the research results, it is known that the e-parking service program implemented by the Surabaya City Transportation Service is declared effective. Based on the results of the calculation of the frequency distribution, it shows significant results that the implementation of the e-parking service program is in the Good category with a total frequency of 47% with a total of 47 respondents. Based on the results of calculations carried out in measuring the effectiveness of the e-parking service program in the city of Surabaya, it can be concluded that it is effective or in the good category
Study of Trust Aggregation Authentication Protocol

The main focus of this work is to sense and share the data that are required to be trusted and the solutions are to be provided to the data, as trust management models. Additionally, the elements in the IoT network model are required to communicate with the trusted links, hence the identity services and authorization model are to be defined to develop the trust between the different entities or elements to exchange data in a reliable manner. Moreover, data and the services are to be accessed from the trusted elements, where the access control measures are also to be clearly defined. While considering the whole trust management model, identification, authentication, authorization and access control are to be clearly defined.
Data Security and Anonymization in Neighborhood Attacks in Clustered Network in Internet of Things (NIoT)

In this paper author tries to focus on the review on the K Nearest Neighbor (KNN) tied by one or more specific types of inter dependency, such as values, visions, ideas, financial exchange, friendship, conflict, or trade. Social network analysis views social relationships in terms of nodes and ties. It also focuses the network analysis, application as well as problem statement. In this paper presents a outline for the privacy hazard and sharing the anonymized data in the network. This includes a proposed architecture design flow, for which the author considers the several variations and make connections. On several real-world social networks, we show that simple anonymization techniques are inadequate, it results in considerable breaks of privacy for even modestly informed opponents. It also concentrates on a new anonymization technique. It based on the network and validate analytically that leads to saving of the privacy threat. It also analyses the effect that anonymizing the network has on the utility of the data for social network analysis.
Discrete Wavelet Transform based Cryptosystem

In this article, the authors proposed, implemented and analysed a symmetric key cryptographic algorithm that can be considered as a lossless encryption and decryption technique, advantageous especially in situations where, even a slight marginal distortion is not tolerable. In the proposed system, Haar wavelet is used initially, to transform the original target image into its frequency domain, followed by encrypting the resulting sub-bands, so as to obtain a secure and reliable encrypted image. The resulting coefficients after Haar decomposition is scattered using a reversible weighing factor, suitably reversed and swapped to get the secure encrypted image. The encrypted image is then correspondingly decrypted, by the reverse process to get back the original decrypted image. Statistical testing and security methods were used to evaluate and analyse the proposed cryptosystem and the results showed that the proposed system is cryptographically resistant to attacks and is also highly secure when compared to other cryptographic systems in the frequency domain.
Stability and Effective Process Control for Secure Email Filtering

A fantastic tool for both commercial and personal communication is electronic mail. It has increasingly become a necessary component of our working life since it is straightforward, available, and simple to use. Spam emails have started to tarnish internet experiences and threaten the integrity of email. Due to the exponential growth of spam, both people and organisations are under a great deal of financial and other strain. In order to prevent the future of email itself from being in jeopardy, a solution to the spam problem must be discovered. There is an urgent need to solve the Email spam issue since spam volume has been rising over the last several decades. As part of this effort, many effects of spam emails on businesses and people were noted and thoroughly examined. In order to properly assess current technologies, solutions, and methods, a comprehensive literature review was conducted throughout the procedures. The goals of this work is to develop new methodologies for the implementation of new strategies for the efficient management of email spam and to construct a proof-of-concept software system for the Process controlled assessment of such strategies.
Creating humanoid intelligent digital twin on spectral and holographic approaches

A person perceives his environment through the influence of various complexes of conjugated vibrations on the eyes, ears and other sensitive components of the body. The psyche and neural systems of a person form the impression of vibration impact. The mind creates a language equivalent and connects it with the impression that has formed. Communication links are formed between impressions and language equivalents. Live vibrational information involves a person in a communicative creative process. In the creative communicative process, human intelligence develops. The combination of modern interdisciplinary technologies can contribute to the creation of an intelligent digital twin, similar to humans on spectral and holographic principles, relying on achievements in the field of artificial intelligence. The digital twin fixes the effects of the environment in the form of a spectrogram, and stores the effect result in the form of a hologram. Multilayer neural network systems with additional training work with spectra and holograms and their communications. Language communications are associated with spectra, holograms and their communications. A humanoid digital twin with an ensemble of intellectual agents will be able to form and develop intelligence in interaction with similar digital twins and people.
Ensembles of intelligent agents with expanding communication abilities

Ensembles of intellectual agents solve the problem in the course of self-organization and cooperation according to the criteria of preference and restriction. The solution is considered found when, in the course of their nondeterministic interactions, agents reach the best consensus (temporary equilibrium or balance of interests), which is taken as a solution to the problem. Solving a problem is always seen as an equilibrium when none of the agents can improve their condition anymore, which is evidence of reaching a reasonable compromise, balance of interests, or agreement (harmony) of all intellectual agents in a problematic situation. Agents can act both on behalf of and on behalf of a person, and any physical and abstract entities. In the ensemble of intellectual agents of each entity of the real world, a software agent is put in line, which represents the interests of this entity and can coordinate its decisions with other agents. The advantages of intelligent agents that allow you to build self-organizing ensembles are especially manifested in conditions of a priori uncertainty and high dynamics of the world around you, allowing you to build adaptive ensembles with communicative abilities, rebuilding your plans for events in real time. The higher the intelligence of each agent and the richer the opportunities for communication between agents, the more complex and creative behavior the ensemble can demonstrate. The intellect of the ensemble arises and manifests itself in the process of self-organization of intellectual agents.
Unsupervised Deep Keyphrase Generation

Keyphrase generation aims to summarize long documents with a collection of salient phrases. Deep neural models have demonstrated a remarkable success in this task, capable of predicting keyphrases that are even absent from a document. However, such abstractiveness is acquired at the expense of a substantial amount of annotated data. In this paper, we present a novel method for keyphrase generation, AutoKeyGen, without the supervision of any human annotation. Motivated by the observation that an absent keyphrase in one document can appear in other places, in whole or in part, we first construct a phrase bank by pooling all phrases in a corpus. With this phrase bank, we then draw candidate absent keyphrases for each document through a partial matching process. To rank both types of candidates, we combine their lexical- and semantic-level similarities to the input document. Moreover, we utilize these top-ranked candidates as to train a deep generative model for more absent keyphrases. Extensive experiments demonstrate that AutoKeyGen outperforms all unsupervised baselines and can even beat strong supervised methods in certain cases.