Reviewerly/exHarmony huggingface dataset:
Mixed Reality Mobile Technologies and Tools in Education and Training

– Mixed Reality broadly refer to technologies which are in a continuum with two poles: the reality and the virtual reality. Such technologies heighten our sensory perception of reality through the superimposition of a computer-generated layer to one or more of our senses. For example, Augmented Reality is most used to heighten the sense of sight, providing the user with contextual information. The use of this technology is spreading thanks to the availability of mobile devices equipped with sensors and great computing power. This chapter discusses various applications of mobile MR technology, as well as the roles of various sensors in shaping educational mixed reality experiences. Experiences are shaped not only by the technology employed, but also by the context in which they are implemented. As a result, a variety of application contexts are presented and assessed. Finally, the outdoor cultural heritage context is given special attention, and several experiments in this field are presented.
Deteksi Pencilan Spasial pada Data Kandungan Klorida di Sungai Mahakam Wilayah Samarinda Kalimantan Timur

Spatial data is data presented in the geographical position of an object, relating to the location in the space of the earth. In spatial data often have conditions that are not reasonable because the existence of outlier. Outlier referred to are spatial outlier that are defined as local instability or spatial objects that describe relatively extreme non-spatial attributes or differ significantly from other objects. The existence of outlier can have an impact on the results of model parameter estimates for example, which causes the estimation results to be biased. One method of outlier detection is spatial statistic Z test. This research aims to detect outlier chloride level data in seven locations on the Mahakam River of Samarinda area using spatial statistic Z test method. Based on the calculations with a significance level of 5% from the seven locations, there is one location which is outlier at the location IPA Tirta Kencana value equal to Zhit is 1.997.
Social Media Sentiment Analysis on COVID-19

We are living in the information era, where data is growing rapidly. During critical events, people share their opinion on social media. Nowadays, the world is confronting an infectious disease called COVID-19 or Coronavirus. As social distancing and lockdown are considered the most considerate way to stay away from disease. Therefore, the usage of social media is increased, and a survey shows that during lockdown 3.3 million tweets a day reported on COVID-19. People are using social media for help and to express their opinion on the global pandemic. There are many social networking sites people use to share their opinion, but Twitter has emerged as one of the most popular social media among all other social media. We have done sentiment analysis on big data created by this social media. In this study, we used Twitter to study sentiment analysis. Our dataset contains 1,88,880 tweets on COVID-19. On this dataset, we used different feature extraction methods with the Naive Bayes machine learning approach and get 84.63% accuracy on big data.
A Multi-Image Mosaic Method for Farmland UAV Aerial Images via Reference Image Optimization

In agricultural remote sensing, multi-image mosaic, which stitches the images captured by the camera and get an image with large range, is an efficient way to monitor and inspect a large range of farmland. However, one of the challenges is to accurately locate every component image into right positions in the resultant image. This locating process performs many times in multi-image mosaic. Apart from the first image, before locating any component image, an image that has already been located should be chosen as a reference image. A novel method named Reference Image Optimization (RIO) is proposed in this paper to select reference image in multi-image mosaic to reduce mosaic errors, where SIFT and RANSAC algorithms are applied to obtain the matched feature point pairs for every two-image mosaics, and the image with the largest number of matched feature point pairs at a particular range of direction relative to the locating image is chosen as the optimal reference image. In this paper, farmland is used as an application scenario to validate the method. The trait of farmland UAV aerial images is that there is a high similarity among different images, so mosaic error often appears when using traditional methods. The proposed method automatically stitches hundreds of high-resolution farmland UAV aerial images into a complete and seamless large image without resolution loss. The proposed method can be used to improve the accuracy of image mosaic technology of agricultural remote sensing.
Non-linear, Sparse Dimensionality Reduction via Path Lasso Penalized Autoencoders

High-dimensional data sets are often analyzed and explored via the construction of a latent low-dimensional space which enables convenient visualization and efficient predictive modeling or clustering. For complex data structures, linear dimensionality reduction techniques like PCA may not be sufficiently flexible to enable low-dimensional representation. Non-linear dimension reduction techniques, like kernel PCA and autoencoders, suffer from loss of interpretability since each latent variable is dependent of all input dimensions. To address this limitation, we here present path lasso penalized autoencoders. This structured regularization enhances interpretability by penalizing each path through the encoder from an input to a latent variable, thus restricting how many input variables are represented in each latent dimension. Our algorithm uses a group lasso penalty and non-negative matrix factorization to construct a sparse, non-linear latent representation. We compare the path lasso regularized autoencoder to PCA, sparse PCA, autoencoders and sparse autoencoders on real and simulated data sets. We show that the algorithm exhibits much lower reconstruction errors than sparse PCA and parameter-wise lasso regularized autoencoders for low-dimensional representations. Moreover, path lasso representations provide a more accurate reconstruction match, i.e. preserved relative distance between objects in the original and reconstructed spaces.
APOS Theory Implementation of a Module Contained with Autonomous Character and Mathematics Connection on Algebra Material

This is a development research of a learning source based on APOS theory.The role of APOS theory is to facilitate framework constructions of an action, process, object, and scheme.This research aims to evaluate the existence of the learning material based on APOS theory and tests its validity and practicability based on the readers' responses.This is a Research and Development study.The stages consisted of 5 steps: analysis, plan, development, implementation and evaluation.The subjects consisted of the teachers, the parents, and the learners of Primary Schools, Junior High Schools, and Senior High Schools in Lingga Municipality.The variables consisted of the learners'autonomies and mathematics connections.The quality of the module was obtained from observation, interview guidance, and questionnaire.The findings showed the current learning source existence had not been oriented to APOS theory.The same thing also occurred in the action, object, and scheme stages.The findings also asserted that the develop module was valid and practical.The module had high validity, and an excellent criteria.The responses of both the parents and the teachers showed that the module could be used as a learning reference.The learners responded positively about the module since it was concluded that the module was applied for Primary School until Senior High Schools learners as the learning reference.
Privacy based Discrimination Prevention using Virtual Passwords and Anonymization Methods

Privacy preserving data mining refers to the part of data mining used to safeguard sensitive information illegal disclosure. Discrimination is the detrimental process of people based on their association with a certain classes or groups. Direct discrimination restricts a certain group of working class based on sensitive reasons. Indirect discrimination restricts a certain group of working class based on non sensitive ones. Both direct and indirect discrimination can be prevented using data transformation methods such as rule protection and rule generalization. Balanced iterative reducing and clustering using hierarchies (BIRCH) algorithm is used for analyzing discrimination datasets based on eligible criteria. In this paper, privacy can be enhanced using differentiated virtual password schemes and anonymization techniques. We provide a differentiated virtual password that applies user-specified randomized linear generation functions to protect user passwords. We provide an anonymization algorithm that processes inferring approach to prevent attacks in discrimination environment. We are evaluating these methods on Adult dataset and provide metrics for proposed methods that impact on information loss and data quality in data mining.
The non-native canonical accent—And how to use it

One of the key benefits of modern globalization is cross-pollination of cultures. This global community encourages diversity of thinking and communication across language boundaries. However, learning to speak a foreign language is predictably challenging and non-native speakers offer a quasi-infinite source of pronunciation variation. This variation presents a challenge to AI-based technologies where we make assumptions about user behavior and expected runtime input to the models. Inconsistent usage therefore is difficult to model successfully. A study of pronunciation patterns from a set of non-native speakers uncovered some of the underlying dynamics of different levels of non-nativeness. Anchored in key differences in phoneme inventory and phonotactic distance between L1 and L2, the notion of a non-native canonical accent is introduced. This accent captures a significant portion of the speakers in the data and allows us to describe the variation with the precision needed to model it. If we can more consistently anticipate the characteristics of the variation, we're better positioned to handle it. This means that by explicitly focusing on the pronunciation patterns that are likely to be challenging to non-native speakers, we can adapt the technology to build more robust speech recognizers and more personalized foreign language learning experiences.
Optimal Linear Optical Discrimination of Bell-Like states

One major challenge in utilizing linear optical setups for quantum computing, is that only a limited set of operations can be preformed. Achieving universal quantum computing using only linear optical components comes at the cost of either requiring an untenable number of ancillary photons or the acceptance of some probability of failure. Understanding the constraints and optimizing general linear optical operations under these constraints is both an important and challenging task. Here we consider the problem of perfectly discriminating between Bell-like states without the use of ancillary photons. For the discrimination between Bell states, the optimal success probability cannot exceed 50%. Here we derive the optimal approach for Bell-like states and show that the success probability without ancillary photons can only reach 25%.
Implementation of Real-Time Stereo Matching System Based on Speckle Structured Light

Real-time and accurate acquisition of target depth information is the prerequisite for subsequent 3D reconstruction and abnormal behavior detection. For this application, this paper designs and implements a binocular stereo real-time system based on speckle. The main hardware components are binocular and speckle projector, and the main algorithm is (Semi-Global Matching) SGM's GPU implementation. The detection range of the system is 1.2m-6m, the frame rate can reach 30, the parallax level is 256, and the image resolution can reach 1280×720 pixel.
Digital Communication Basics

This chapter talks about how an analogue signal is converted into a digital signal and all the attendant problems which arise in doing so. The Fourier transform of sampled signals is obtained, and the result shows how this Fourier transform is the forerunner of the Discrete Time Fourier Transform.
VADiMoS: A Web Tool for Designing Voice Assistant Independent and Ontology Based Dialogs

The development of custom skills for the popular Voice Assistants (VAs) of Google and Amazon is usually done in their corresponding eco system for the specific VA. However, the expectations to a voice assistant are very high: natural language understanding, open domain, task oriented, and smart dialogs resulting in correct and context dependent responses. The eco system of the VAs is often not capable to handle such natural dialogs. It is necessary to code simple dialogs running in the backend of the voice assistant, to learn dialogs based on a huge set of domain data, or to design dialogs based on rules. In our approach we design a knowledge graph based on objects and their relations. This knowledge represents the domain, the dialogs, language resources, and rules. A rule engine operates on this dynamic knowledge base and calculates the next dialog step. This approach is voice assistant independent and can be combined with the top on-market VAs, like Alexa or Google Assistant. In this paper we present our web-based Voice Assistant Dialog Modeling Service (VADiMoS) which enables such ontology based dialog modeling, testing, simulation, and deployment to the VA. VADiMoS abstracts the complex definition of dialog rules which are part of our ontology by providing a template-based rule editor. This enables the interactive and test-driven creation of human machine dialogs.
Multiactuators Control for Prototype Panorama Scanning Imaging With Input Saturation

In this article, we propose an adaptive sliding mode control scheme with a saturation coefficient (ASMC-SC) for panorama scanning imaging with multiple actuators in the presence of input saturation. By introducing a SC into the sliding surface and adaptive parameters, the actuator drive capability is more fully utilized, and undesired accumulations of adaptive parameters are avoided. A stability analysis was performed using the Lyapunov stability arguments. The simulation and experimental results show that the ASMC-SC guarantees imaging efficiency and has a better tracking performance.
Autonomous Navigation for Control of Unmanned Vehicles Based on Odometers and Radar Sensor

The paper describes a new principle of building autonomous positioning systems for wheeled unmanned platforms when working in industrial premises without the use of inertial sensors, global satellite and local navigation systems. An algorithm for calculating the vector of movement of a transport platform on a plane using odometric and microwave radar sensors is presented. The procedure for controlling movement along a given route between waypoints using circular inserts based on the received data is described.
Sense Making of the Congruence of Comprehension between Two Listeners of the Speech on "Budi Sejahtera Leadership"

Yusof IsmailDzuljastri Abdul RazakSuhaimi Mhd SarifReceiving information from indirect sources is common in daily lives. This may be due to the time constraint, giving priority to one’s current engagement, physical distance, mandatory non-face-to-face communication, and other factors. In fact, most of an individual’s time is spent on processing indirect information whether one deals with his office work or family matters. This chapter shows the extent of congruence that is identified by a co-author based on the description of the other two co-authors who attended the talk on the topic of “Budi,” “Sejahtera,” and “Leadership.” The lead author created and sent an attachment that contains a combination of dichotomous and open-ended questions related to the three-terminology theme to the other co-authors for their independent views. He analyzed their textual opinions and produced his analysis of the converging and diverging themes based on the opinions provided. This case study helps people become aware of the varying amount and depth of information acquired by listeners to a public lecture, moreover via online platform rather than among the audience of a lecture in a hall. In this case, only two listeners are involved, making content analysis easy.Keywords: Budi, Communication, Comprehension, Information, Islam, Listening, Malay, Sejahtera.
Automated HW/SW Co-design for Edge AI: State, Challenges and Steps Ahead: Special Session Paper

Gigantic rates of data production in the era of Big Data, Internet of Thing (IoT), and Smart Cyber Physical Systems (CPS) pose incessantly escalating demands for massive data processing, storage, and transmission while continuously interacting with the physical world using edge sensors and actuators. For IoT systems, there is now a strong trend to move the intelligence from the cloud to the edge or the extreme edge (known as TinyML). Yet, this shift to edge AI systems requires to design powerful machine learning systems under very strict resource constraints. This poses a difficult design task that needs to take the complete system stack from machine learning algorithm, to model optimization and compression, to software implementation, to hardware platform and ML accelerator design into account. This paper discusses the open research challenges to achieve such a holistic Design Space Exploration for a HW/SW Co-design for Edge AI Systems and discusses the current state with three currently developed flows: one design flow for systems with tightly-coupled accelerator architectures based on RISC-V, one approach using loosely-coupled, application-specific accelerators as well as one framework that integrates software and hardware optimization techniques to built efficient Deep Neural Network (DNN) systems.
Deformation monitoring method of connection structure of prefabricated building based on RBF network

In the deformation monitoring of the connecting structure of prefabricated buildings, the traditional monitoring method is difficult to guarantee the data quality when the monitoring distance is far or there are many obstacles. For this reason, this research designed a method for monitoring the deformation of the connection structure of a prefabricated building based on RBF network. First, use RFID positioning technology to determine the location of the connection structure of the prefabricated building, and then use the inclination sensor and STC15F2K60S2 microprocessor to collect deformation data. Based on this, set the RBF network parameters, input the collected deformation data into the RBF network, and use LoRa technology to design a remote monitoring communication module. With the support of this module, the deformation data is transmitted to the monitoring center, and the deformation degree of the connecting structure is judged through calculation and analysis of the monitoring results. The experimental results show that the effective communication transmission distance of this method is relatively long, and its monitoring signal quality is high, and the monitoring accuracy is high.
Perancangan Aplikasi Harga Cerdas Berbasis Android

The increasing number of customers at minimarkets creates problems in the convenience and effectiveness of the shopping process at the minimarket. The problem of information regarding the data of goods is often complained of by customers, such as there is often a difference in the price listed on the shelf with the price at the checkout and the lack of information makes customers busy looking for employees to ask about item details. The purpose of this study is to produce an android-based cashier application to help minimarket visitors to see information about the price of goods, the amount of groceries and the total shopping to be paid at the cashier. In addition, this application also includes information on expired items so that customers can find comfort in the forest. This application has a barcode scanning feature where each item is scanned and can view item details such as id, name, dimensions, quantity, color, price, and images of goods and expiration date. This mini market application is based on android which is integrated on a server via the internet and is supported by the MYSQL Database. By using a system like this, customer comfort and satisfaction when it is expected will increase and become more value from the minimarket side itself so that it helps cashiers in the process of managing sales data more effectively, efficiently and accurately so that customers get comfort in shopping activities and do not feel suspicious about the cheating of convenience stores.
Second-Order Specifications and Quantifier Elimination for Consistent Query Answering in Databases

Consistent answers to a query from a possibly inconsistent database are answers that are simultaneously retrieved from every possible repair of the database. Repairs are consistent instances that minimally differ from the original inconsistent instance. It has been shown before that database repairs can be specified as the stable models of a disjunctive logic program. In this paper we show how to use the repair programs to transform the problem of consistent query answering into a problem of reasoning w.r.t. a theory written in second-order predicate logic. It also investigated how a first-order theory can be obtained instead by applying second-order quantifier elimination techniques.
Systematic Translation of Formalizations of Type Theory from Intrinsic to Extrinsic Style.

Type theories can be formalized using the intrinsically (hard) or the extrinsically (soft) typed style. In large libraries of type theoretical features, often both styles are present, which can lead to code duplication and integration issues. We define an operator that systematically translates a hard-typed into the corresponding soft-typed formulation. Even though this translation is known in principle, a number of subtleties make it more difficult than naively expected. Importantly, our translation preserves modularity, i.e., it maps structured sets of hard-typed features to correspondingly structured soft-typed ones. We implement our operator in the MMT system and apply it to a library of type-theoretical features.
Improved image compression using lifting wavelet

This work gives an effective and efficient approach for image compression which is based on lifting wavelets. Here the image is decomposed into n-level binary sequence; this binary form image is then processed using lifting wavelet transform. The alternate modification of decomposed sequence enables to eliminate the delay of one sample which is more prominently available in compression done with conventional discrete wavelet transform. In this work the compression of image is achieved using lifting wavelets to have 11.05% improvement in PSNR and 35.89% improvement in compression ratio.