Reviewerly/exHarmony huggingface dataset:
The Development of Raspi-Met System with Raspberry Pi3 for Meteorological Monitoring in Remote Areas

Abstract The development of autonomous weather station systems using Raspberry Pi3 as a new alternative, named as ‘ Raspi-Met ’ to enhance conventional meteorological systems is reported in this paper. Today, a weather station with a compact size is required due to limited space and cost involved. Thus, this paper aims to design an application system using Raspberry Pi3 which is connected to Vaisala PTU300 sensors as Automatic Weather Station (AWS). The Python language under LINUX has been employed to design a graphical user interface (GUI) for a real-time monitoring system, acquisition process, and displaying three meteorological parameters at desired intervals. Data storage management and daily file in a text (*.txt) format have been created to archive historical data. The RTC module has also been developed and connected to Raspberry Pi3 to synchronize and maintain the time and date of the measurement system after the power is on. The system was installed at Carlini Base, Antarctica and has the ability to measure the surface pressure ( P ), temperature ( T ), and relative humidity ( H ). The results have been tested and validated that the system is capable as an AWS in the Antarctic Peninsula. The development of Raspi-Met system exhibits remarkable measurements of meteorological parameters for remote areas and the database organization becomes more efficient and practical.
Natural Language Processing based Text Imputation for Malayalam Corpora

The prediction task in Natural Language Processing intends to figure out the missing characters, letter, word, expression, or sentence that conceivable follows in a given fragment of a book. Since the beginning of NLP, numerous frameworks with various techniques were produced for various dialects. The missing content prediction is one among the significant concerns of Natural Language Processing. Moreover, most of the text prediction related tasks are conducted in different dialects but not in Malayalam. Over these years though having some of the best classics, historical records and many more to keep the world interested with, the Malayalam was lacking many of the advantages that any other language process in the digital world. This is because there are only a few standard models that could fit into the Malayalam. In this paper, an attempt is made to fit the BERT into Malayalam. A Malayalam pre-trained model will be creating and implementing some of its applications with the model and discussing its scope and areas of development to be addressed and future research scope.
Hilbert modular forms and codes over Fp2

Let p be an odd prime and consider the finite field Fp2. Given a linear code C⊂Fp2n, we use algebraic number theory to construct an associated lattice ΛC⊂OLn for L an algebraic number field and OL the ring of integers of L. We attach a theta series θΛC to the lattice ΛC and prove a relation between θΛC and the complete weight enumerator evaluated on weight one theta series.
Development of a Quality Model Based on ISO 25010 Using Fuzzy and PSO for E-commerce Websites

The e-commerce website is so important for other people in the product sales process. An e-commerce website is one of the most used businesses by people. A good quality e-commerce website will have many visitors. However, determining the quality of an e-commerce website is not easy. Many research on measuring software quality is carried out based on characteristics at ISO 9126. These models arise as a result of getting good software quality. However, the ISO 9126 standard has been replaced with ISO 25010 which has the addition of several characteristics. Therefore in this paper, we propose a software quality measurement model on an e-commerce website based on the characteristics of functional suitability, reliability, usability, and performance efficiency. The quality model that is build uses fuzzy logic to determine the level of quality and particle swarm optimization to find the particle with the best fuzzy set position to form a quality model. The model we propose to classify e-commerce website quality based on four characteristics of ISO 25010 produces an accuracy value of 0.684 and a precision of 0.867.
Work-in-Progress—Measuring Engagement in Virtual Reality for Talent Attraction Purposes

Virtual Reality (VR) is a powerful tool for situate users in environments difficult to replicate in real life due to restricted access (e.g. historical sites or restricted buildings) or dangerous situations (e.g. working on top of a pole) among other examples. Such simulations can be used for allowing users to experience real-life situations in a controlled environment, enabling the study of interesting phenomena, such as user's engagement. This paper introduces a work-in-progress mobile VR app that recreates everyday working scenarios, using a mixture of 3D modelled environments and media streamed resources (e.g. 360 videos) to attract talent for specific roles in a company, by providing a better understanding of the activities involved in those roles. We complement this with preliminary results of a user evaluation, and the results of an engagement evaluation provided via a fuzzy logic system (FLS).
SwiftPad: Exploring WYSIWYG TEX Editing on Electronic Paper

Electronic paper (i.e., e-paper) is a display technology that aims to imitate and substitute the conventional paper. Previous studies of e-paper mainly focus on evaluating or making practical use of its readability. However, there is little research to explore the potential of e-paper on input-oriented applications. In this paper, we introduce a document composition system named SwiftPad for e-paper. Specifically, SwiftPad renovates the famous TEX typesetting system, enabling users to compose high typographic quality documents on e-paper in a WYSIWYG (what you see is what you get), offline-first, and collaborative fashion. Building such a system on resource-constrained e-paper with low screen refresh rate creates unique challenges. In this paper, we identity these challenges and provides workable solutions. We also provide a preliminary evaluation of the new system.
Exploring the Rhetorical Affordances of Augmented Reality in the Context of the Anthropocene

Immersive technology is increasingly recognized for its rhetoric potentials. Similar to traditional genres such as text and image, immersive technology such as Augmented Reality (AR) is also context dependent and can be used to conduct persuasive ends, based on the advantages of their input/output affordances. AR provides new opportunities to represent human-nonhuman relationship rhetorically, which is central to the concept of the Anthropocene. In this study, we reviewed 14 AR applications that are designed for the understanding of the Anthropocene, the current geological epoch where human influence is the driving force. Our purpose is to understand what affordances of AR can help to create the rhetoric for the Anthropocene. We identified three major rhetorical affordances of AR in conveying the message of the Anthropocene: virtual objects, point of view, and the input-output link. We argue that the design of these applications can generate a local and personalized understanding of the Anthropocene. Such design is also a part of the posthuman endeavor as they can be used as a reflective tool of anthropocentric perceptions supported by the development of technology. We also discuss how AR differs from Virtual Reality (VR) when serving the rhetorical ends. The rhetoric effects can be implicit in AR, but it adds to the layers of meaning when we try to understand the make meaning-processes of AR.
Work-in-Progress—Augmented Reality at Scale: Using Physical Dimensionality of Spaces to Our Advantage!

A behemoth painting measuring 49 feet high and 358 feet in length, the Battle of Atlanta Cyclorama exhibits opened to the public at the Atlanta History Center on February 22, 2019, fully restored to its original form as painted by the artists of the American Panorama Company in the 1880s. The Cyclorama is an immersive experience depicting the battlefield at approximately 4:45 p.m., July 22, 1864. The goal of our application is to enable easy identification and illustration of significant points-of-interests (POIs) embedded in the painting as the artists originally intended without obscuring the illusion of hovering above the battle field from an abstract perspective. This work in progress paper details a novel approach to develop an Augmented Reality (AR) experience at scale to incorporate real-world museum exhibits to treat as AR markers as a whole. It also describes the enduring process of keeping a low footprint on hardware configuration to maximize accessibility and thus empowering public scholarship in the field.
Development of the Voting System for Game Show Program Using Blockchain Technology

At present, it is well known that blockchain technology can be applied in many organizations, whether large or small. The users can adapt the blockchain technology to suit their need. It has become an important technology in a very short time and it begins to play a beneficial role in many disciplines. This research is aimed to develop the voting system for game show program using blockchain technology in order to assess the efficiency and transparency of the system by voting through the application web developed by the researchers. The result revealed that the votes were correct and transparent because recording the votes in blockchain is immutable. Moreover, as the efficiency of proof of work (PoW) and Ganache were compared with each other, the transaction sending speed in Ganache was found to be slightly faster than that in PoW in the order of seconds.
Speeding-Up the Particle Filter Algorithm for Tracking Multiple Targets Using CUDA Programming

Object detection and tracking are essential tasks in many computer vision applications. One of the most popular tracking algorithms is the particle filter, which is widely used for real-time object tracking in live video streams. While very popular, the particle filter algorithm suffers from increased computational runtimes for high-resolution frames and large numbers of particles. In this paper, we investigate the use of CUDA programming as a method to parallelize portions of the particle filter algorithm in order to speed-up its execution time on compute systems that are equipped with NVIDIA GPUs. Experiments that compare a CPU sequential version, as the base case, with the CUDA parallelized version demonstrate an achievable speed-up of up to 7.5x for a 3840x2160 video resolution, and 9216 particles on a computer equipped with an NVIDIA Tesla K40c GPU.
Parameters Estimation Of Rayleigh Distribution In Survival Analysis On Type Ii Censored Data Using The Bayesian Method

Abstract This research aims to determine the estimation of Rayleigh’s distribution parameters on the data survival analysis of type II of tuberculosis patients. The method used in this research is the Bayesian method to perform estimate parameters. The process estimation parameter using the Bayesian method requires information from the likelihood function and the prior distribution. The prior distribution used was the prior distribution of Jeffreys. In this study, estimates of Rayleigh’s distribution parameters were applied in the survival analysis data of tuberculosis sufferers. And the value of estimated parameters in patients with tuberculosis acquired θ = 0.001097324 and the changes of the survival value decreased near to zero.
FACE RECOGNITION SYSTEM FOR VISUALLY IMPAIRED PEOPLE

In our proposed method, a real time System Recognition Face (FRS) introduced for low vision people and aiding the blind. Thework process includes face detection and face recognition to identify the person who is standing in front of them. First, thecaptured image is captured is taken by a camera Pi - 8 Mega Pixel. Oriented Gradient Histogram (HoG) features extracted withdatabase which already has the extracted HoG feature. For a face image 4680 HoG features are extracted. If the input image ismatched, it pronounces the person name to the blind person by audio signal through text to voice converter. Suppose the image isnot matched, it asks whether to store it in the database. In our proposed method, Balabolka software is used for text to voiceconversion. The work is implemented using Raspberry pi 3 processor and MATLAB 2017b. The experiment is implemented for100 faces with 10 different positions.
Improved Post-quantum Merkle Algorithm Based on Threads

Today scientists are actively working on the creation of quantum computers. Quantum computers will be able to solve the problem of factoring the large numbers. So, quantum computers can break the crypto system RSA, which is used in many products. Hash based digital signatures are the alternative to RSA. These systems use cryptographic hash function. The security of these systems depends on the resistance to collisions of the hash functions that they use. The paper analyzes hash based digital signature schemes. It analyzes the improvements of the scheme. Fractal Merkle algorithm is also analyzed. This algorithm can be considered as the static one, because it does not depend on the number of the threads in CPU. Authors have offered the post-quantum algorithm, which uses the threads of CPU in the parallel mode. The mathematical model of this algorithm and the pseudo code of its implementation are offered in the paper. This algorithm was analyzed and is shown that this algorithm provides rather good speed up, and can be implement to provide post-quantum security in modern information and communication systems.
An experimental audio-tactile interface for sculpting digital resonance models using modelling clay

Programming interfaces are still monopolised by the typewriter and paper emulator display. This makes programming exclusionary towards anyone for whom such interfaces are unpleasant, unnatural or unusable. Further, this monopoly excludes every other human faculty that might be used to express unexpressed programs through unimagined means. To destablise this status quo, alternative programming models have been sought which are more amenable to a wider range of interfaces. We believe a complimentary approach to be broadening the search for programming interfaces by excluding the need for an explicit programming model at first. We present an experimental audio-tactile interface for sculpting digital resonance models using clay, along with preliminary reflections from a study with 34 musicians, luthiers and other craftspeople. We reflect on how tracing the emergence of tacit and embodied knowledge about an unfamiliar, implicit programming interface could inspire different ideas about programming models and other aspects of programming systems.
Performance Analysis of Various Generative Adversarial Network using Dog image Dataset

Generative Adversarial Network is a novel concept for a general purpose solution to Deep Fake Image generation. These networks learn mapping from input image to output image and also assign value in loss function for the same mapping. We demonstrate that this approach is effective to synthesize images from labelled images, and colorizing images, and other tasks. We have investigate performance of three different types of model i.e. simple GAN, DC-GAN, BIG-GAN, which have provided different results with generation of different loss function on the same dataset i.e. Stanford Dogs Dataset. In this paper, we have investigated the performance of models by using inception score and also track the loss function at different stages (epochs).
Developing a Multi-modal Listing Service for Real Estate Agency Practice in Nigeria

Fraudsters posing as real estate agents threaten the reputation of real estate agencies in Nigeria. These fraudsters have continually defrauded unsuspecting members of the public. The major cause of this lapse is due largely to the fact that there is no known platform provided in the country that allows members of the public to verify a given real estate agent. This paper aims to provide support to real estate agency practice in Nigeria by developing a multi-modal listing service for verifying registered real estate agents and to also provide information on real estates available for sale, lease or rent. The requirements for the system were gathered through observation, literature survey and user survey. These requirements were then modelled using the Unified Modelling Language (UML). The system is developed both as a web and mobile application using an open source content management system (WordPress). This paper essentially presents the: requirements gathering process, design and implementation of the multi-modal listing service as well as how it compares with other similar services developed elsewhere. The multi-modal listing service developed in this study is a welcome development due to the availability and widespread adoption of the Internet and Internet-enabled mobile devices in Nigeria. The tool can be of use to the National Association of Estate Agents in Nigeria - a body saddled with the responsibility of rebranding the real estate agency profession in Nigeria.
Factors Analysis that Affecting “Knowledge Sharing” in T-vet Instructors at Aviation Polytechnic of Surabaya

This research aims to analyze the factors that influencing knowledge sharing. The factors are organization, individual, content, cooperation, and technology. This research is a type of causal research with a quantitative approach. The population that was used in this study were all Aviation Polytechnic of Surabaya cadets as many as 998 people, while the samples taken were 286 people. The data was sourced from primary data collected through questionnaires. The data analysis technique that was used is factor analysis with the help of the SPSS program Version 23.00. The results in this study indicate that: (1) organization factor has a significant and positive influence on knowledge sharing; (2) individual factors do not have a significant influence but have a positive influence on knowledge sharing; (3) content factor has a significant and positive influence on knowledge sharing; (4) cooperation factor has a significant positive influence on knowledge sharing; (5) technology factor has a significant positive influence on knowledge sharing.
A Comprehensive Statistical Scrutiny of HDT Dissimilarity for Localizing and Restoring Impulsive Noisy Images

This scrutinized report presents the comprehensive scrutiny of noisy restoration technique based on HDT (Hard Decision Threshold) dissimilarity, one of the most practical and efficient dissimilarity measurement technique for localizing the impulsive noisy pixels, for RVIN (Random Value Impulsive Noise). The main contribution of this scrutinized report is the determination of the optimal window size and optimal HDT threshold of the noisy restoration technique based on HDT. From many standard tested images, the comprehensive scrutiny illustrates that the obvious difference of the HDT dissimilarity between the genuine pixel and the noisy pixel. Moreover, the statistical relationship between HDT dissimilarity and the cluster size (3x3, 5x5 or 7x7) is simulated for determine the optimized cluster size from performance perspective. Finally, the statistical relationship between the denoising performance and the Hard Decision Threshold (HDT) is simulated by using many tested images for determine the optimized threshold.
Design of an Energy-Efficient True Random Number Generator Based on Triple Read-Write Data-Stream Multiplexing of MTJ Devices

In this paper, we introduce an energy-efficient true random number generator (TRNG) using triple read-write data-stream multiplexing combined CMOS-circuits with three-terminal magnetic tunnel junction (3T-MTJ) devices. When multiple 3T-MTJ devices are used and sequentially activated for high-speed random-number generation, the sufficient timing margin must be guaranteed for correct random-number bit stream from the 3T-MTJ devices. In the proposed TRNG, random-number bit streams are triplicated and three individual random-number bit streams are superposed among them on a single output line, which achieves high-speed and energy-efficient random number generation. We use 65 nm-CMOS/3T-MTJ design technologies, and confirm its correct operation verification by HSPICE simulation with a 3T-MTJ model. The quality of random numbers generated is verified by NIST test. As a result, the energy consumption per bit is 0.5 pJ / bit, which is about 1/10 of a conventional CMOS-based TRNG.
Model-Based Robot Learning Control with Uncertainty Directed Exploration

The Robot with nonlinear and stochastic dynamic challenges optimal control that relying on an analytical model. Model-free reinforcement learning algorithms have shown their potential in robot learning control without an analytical or statistical dynamic model. However, requiring numerous samples hinders its application. Model-based reinforcement learning that combines dynamic model learning with model predictive control provides promising methods to control the robot with complex dynamics. Robot exploration generates diverse data for dynamic model learning. Model predictive control exploits the approximated model to select an optimal action. There is a dilemma between exploration and exploitation. Uncertainty provides a direction for robot exploring, resulting in better exploration and exploitation trade-off. In this paper, we propose Model Predictive Control with Posterior Sampling (PSMPC) to make the robot learn to control efficiently. Our PSMPC does approximate sampling from the posterior of the dynamic model and applies model predictive control to achieve uncertainty directed exploration. In order to reduce the computational complexity of the resulting controller, we also propose a PSMPC guided policy optimization algorithm. The results of simulation in the high fidelity simulator “MuJoCo” show the effectiveness of our proposed robot learning control scheme.
Providing Security &amp;Minimizing Fake Calls by Use of Hashing Algorithm in Digital India

Hashing algorithm guarantee the integrity, authenticity of data or data transmitting between the sender and recipient. Hash function assumes a crucial job to organize security and cryptography. To produce symmetric key and deviated key hash function is utilized. Diverse degree of security is given by various algorithm relying upon how troublesome is to break them. There are four SHA algorithm and have diverse structure. SHA means ”Secure Hash Algorithm” which is utilized to deliver a message digest dependent on standards like those utilized in the plan of MD4 and MD5 message digest algorithm yet has a progressively moderate structure. This paper manages down to practical approach of hash algorithm additionally giving security and limiting fake calls by utilization of hashing algorithm in digital India. Also, there are various reasons to implement the proposed idea using MD-5 which are discussed in the paper.
Portable Alphabet Learning Device

Abstract The purpose of this research is to make a portable alphabet learning. The method used in this research was qualitative. This research discusses the making of learning devices using Raspberry Pi mini computers. The system input is the keyboard while the system output is sound on the speaker and displayed on the LCD. This system was built using the Python programming language. The system generates questions so users can learn and measure their ability to learn the alphabet. The results of this study indicated that the development of this device can facilitate learning the alphabet. This tool can be used to help reduce the problem of illiteracy in Indonesia.