Reviewerly/exHarmony huggingface dataset:
Characterization of a Metric for Web Applications (Web Points)

Software estimation is crucial for any software project, since it ensures better planning and project management, which results in aspects such as timely deliveries, use of the right resources, and well-established budgets. Objectively measuring applications is an important concern from the perspective of improving the engineering approach to software development. This goal is related to improving estimates of the effort required to develop an application, but also to measure existing products. Currently, there are already several variations of software measurement metrics. Despite this, they cannot be classified as better or worse, since they have different purposes and respond according to what is intended to be measured. This article aims to propose a metric to measure the functional size of Web Applications (Web Points). For this purpose, a study was made in the literature on Software Engineering and existing metrics. The metric was then proposed and applied to Web applications developed in academic environment.
Resolving lithostratigraphic complexities in the Crayfish Group, Otway Basin using chemostratigraphy

The Otway Basin comprises a significant part of the eastern Australian Southern Rift System, a divergent passive continental margin formed during the Cretaceous separation of the Australian and Antarctic continents. Early rifting activity resulted in the development of many half grabens within the Otway Basin, which are largely infilled by sediments of the Casterton Formation and Crayfish Group. Despite over 20 years of exploration and hydrocarbon production from these units however, their lithostratigraphic characterisation and nomenclature remain ambiguous, with structural complexity and prevalent lateral facies changes leading to confusion in their basin-wide correlation. Deposited in a largely non-marine, fluvial/lacustrine environment, repeating cycles of sandstones and shales of the Crayfish Group can be difficult to resolve using petrology, palynology and wireline log data. The use of chemostratigraphy is favoured as an investigative tool in this situation since changes in provenance, lithic composition, facies, weathering and diagenesis are reflected in the mineralogy of the sediments, resulting in variations in their inorganic geochemistry. Uniform sedimentary successions can thus potentially be differentiated into unique sequences and packages based on their characteristic geochemistry, aiding in the resolution of complex structural relationships and facies changes. In this study, we present new inorganic geochemistry data for four key wells in the South Australian (SA) Penola Trough and interpret the geochemistry data consistent with, and building on, the chemostratigraphic schema of Forbes et al. to demonstrate its utility and robustness. We then undertake inter-well wireline log correlations across the SA Penola Trough using the wells with chemostratigraphic data as controls.
Avatar Twin Using Shadow Avatar in Avatar-Mediated Communication

Shadow is an effective projection for presence of real objects, and has important roles in three-dimensional effects and reality of virtual space. Therefore avatar's shadow would be able to have interactive effects with the avatar's self in a virtual space. In our previous research, we reported that an auto-generated interactive avatar's motion which is different from the talker's own motion not always supports human communication. However, by using an avatar-shadow, talkers could communicate effectively without inconsistency between their own motions and their avatar's motions in a virtual space, in which the avatar-shadow's motions are expressed by combining the talker's own motions with auto-generated interactive motions. Accordingly we propose an embodied entrainment system called "Avatar Twin" using shadow avatar. This system is constructed by talkers' shadow avatars based on their own motions, and their avatars based on auto-generated entrained motions, in addition to the previous avatar-shadows. In previous studies, an avatar was a subject as a substitute for the user, and the main purpose was to investigate the effects of shadow support in communication. In this paper, we propose the master-slave inversed approach by swapping between measured and entrainment motions in shadow avatar communication system, and develop the system prototype.
Module of Fiscal and Monetery Policy Based on Saintific Approach and HOTS Orientation as Learning Tools For Grade XI in High School

This study aims to create a learning device in a module form as a learning media during the Covid-19 pandemic which these new normal period makes hone learning become urgency. This method also required students to be more independent and help students to study by adjust their needs and time without using face-to-face learning during the pandemic. The module is made using K-13 as a reference in learning and using HOTS (Higher Order Thinking Skills) in exercises that articles provided. The process of making this module uses a 4-D model: Define, Design, Develop, and Disseminate. The module validated by material and language experts to determine whether this module suitable or not as learning media and validation results shows from material experts were obtained with 93% (valid), then from linguists were obtained 90.5% (valid). The module was also tested on students and received a response 77%.
Syntactic Coherence in Word Embedding Spaces

Word embeddings have recently become a vital part of many Natural Language Processing (NLP) systems. Word embeddings are a suite of techniques that represent words in a language as vectors in an n-dimensional real space that has been shown to encode a significant amount of syntactic and semantic information. When used in NLP systems, these representations have resulted in improved performance across a wide range of NLP tasks. However, it is not clear how syntactic properties interact with the more widely studied semantic properties of words. Or what the main factors in the modeling formulation are that encourages embedding spaces to pick up more of syntactic behavior as opposed to semantic behavior of words. We investigate several aspects of word embedding spaces and modeling assumptions that maximize syntactic coherence — the degree to which words with similar syntactic properties form distinct neighborhoods in the embedding space. We do so in order to understand which of the existing models maximize syntactic coherence making it a more reliable source for extracting syntactic category (POS) information. Our analysis shows that syntactic coherence of S-CODE is superior to the other more popular and more recent embedding techniques such as Word2vec, fastText, GloVe and LexVec, when measured under compatible parameter settings. Our investigation also gives deeper insights into the geometry of the embedding space with respect to syntactic coherence, and how this is influenced by context size, frequency of words, and dimensionality of the embedding space.
A Co-Design Approach for a Smart Cooking Appliance. The Application of a Domain Specific Language

Our environment, whether at work, in public spaces, or at home, is becoming more connected, adaptive and increasingly responsive. This is due in part to the significant number of sensors that detect information and data around us. Connected technologies are also emerging as a support to address daily challenges for people with disabilities and for ageing people, bringing care from hospitals into the community and increased provision of health services into homes. Meal preparation, even when it involves simply heating ready-made food, can be perceived as a complex process for people with disabilities. This research aimed to prototype, using a co-Design approach, a Community Supported Appliance (CSA) by developing a Domain Specific Language (DSL), precisely created for a semi/automated cooking process. The DSL was shaped and expressed in the users’ idiom and allowed the CSA to support independence for users while performing daily cooking activities.
Design of Block-Chain Polynomial Digests for Secure Message Authentication

The advent of the internet and cloud solutions have completely transformed the conventional storage and retrieval mechanisms. In modern computing, the data are not under the manual control of the owner. This demands radical solutions to be incorporated for this model to address the integrity violations of the remote data. This chapter attempts to perform the functional analysis of standard digest functions and it proposes an idea for the design of a block-chain based 512-bit digest function using polynomials. Besides, this chapter attempts to examine the erratic behavior of the proposed design through the avalanche response, near-collision response, and statistical analysis of confusion and diffusion. The result proves the response of the proposed design is random and also the proposed design meets the strict avalanche criteria. Therefore, the block-chain based polynomial digest could be considered as an alternative for the contemporary digest function in the perspective of security.
Multi tree operators for genetic programming to identify optimal energy flow controllers

Genetic programming is known to be able to find nearly optimal solutions for quite complex problems. So far, the focus was more on solution candidates that hold just one symbolic regression tree. For complex problems like controlling the energy flows of a building in order to minimize its energy costs, this is often not sufficient. This is why this work presents a solution candidate implementation in HeuristicLab where they hold multiple symbolic regression trees. Additionally, also new crossover and mutation operators were implemented as the existing ones cannot handle multiple trees in one solution candidate. The first type of operators applies them on all trees in the solution candidate, whereas the second one only applies them to one of the trees. It is found that applying the mutator to only one of the trees significantly reduces the training duration. Applying the crossover to one of the trees instead of all needs longer training times but can also achieve better results.
Piano Player with Embedded Microcontrollers

This paper presents the design and implementation of a piano player device which will be attached to a 61-key piano, allowing a song to play from start to finish. The system translates information from a midi file or generated from a standardized music sheet utilizing an image recognition program to control the solenoids. Using solenoids controlled by two separate Arduino microcontrollers with linked serial ports, the keyboard will be actuated. The controlling program provides the user with a Graphical Interface, which provides a saved list of songs that can easily be added to and runs the image recognition program that translates and sends the midi file data to the master Arduino microcontroller.
Organizational Commitment and Employees’ Retention among Jordanians

While the factor of employee engagement and retention is always important to any organization for its sustenance and development, the same can even turn crucial under unique situations, like the one in Jordan business environment, where the psyche of the employees due to the influence of the prevailing cultures proves detrimental in employee engagement and retention. Therefore this study explored the nuances of both Jordanian business environment and the relevant literature of HRM on employee engagement and retention before conducting research and analysis of the whole to come up with the conclusion that successful inculcation of intrinsic motivation is the key to Engage and Retain Employees in Jordan and that is possible through adopting servant leadership style and HPWS (High-Performance Work System), and finally recommending a package of the same.
A Minimally Supervised Event Detection Method

Solving classification problems with machine learning often entails laborious manual labeling of test data, requiring valuable time from a subject matter expert (SME). This process can be even more challenging when each sample is multidimensional. In the case of an anomaly detection system, a standard two-class problem, the dataset is likely imbalanced with few anomalous observations and many “normal” observations (e.g., credit card fraud detection). We propose a unique methodology that quickly identifies individual samples for SME tagging while automatically classifying commonly occurring samples as normal. In order to facilitate such a process, the relationships among the dimensions (or features) must be easily understood by both the SME and system architects such that tuning of the system can be readily achieved. The resulting system demonstrates how combining human knowledge with machine learning can create an interpretable classification system with robust performance.
Quantum Computer and Post-Quantum Cryptography

An overview of the current state of the problem of building a quantum computer and its hypothetical use for breaking cryptographic protocols is presented. The necessary parameters are considered. An overview of existing quantum algorithms and post-quantum cryptographic protocols that are strong with respect to them is presented. The problem of constructing a quantum computer is considered in comparison with the development of the theory and practice of conventional mechanical and electronic computers. The results of contests on the topic of post-quantum cryptography are presented.
A Survey of Sentiment Analysis Based on Product Review

Sentiment analysis (SA) is becoming more and more irreplaceable when we talk about recommendation or analyze guest's preference. Sentiment classification gives prediction ratings or classifying the emotion into two or more poles. We are now looking forward to perfect the precision of the prediction of models. Nowadays, with the development of neural network, deep learning has been broadly used in sentiment analysis. In this paper, we survey large number of papers concerning sentiment classification with deep learning. We propose a new venue to make a division of all the models into 6 kinds. Moreover, we make a comparison of these results of models and draw a conclusion.
A Reference Architecture for Enhanced Design of Software Ecosystems

Software ecosystems have become a novel architectural approach to extend software development to the outside of companies, where third-party providers develop applications on top of a common platform. While designing software ecosystems, platform providers face an overwhelming design space of business and technical architectural decisions. Usually, enterprise architecture modeling languages such as ArchiMate are used to design the ecosystem around the platforms. Despite a body of work studying architecture of software ecosystems, there is still a lack of a reference architecture that captures both business and technical aspects, which can be followed by platform providers to design these systems. In this paper, we develop a reference architecture by using different sources of information such as existing ecosystems and the literature. After identifying the shortcomings of the ArchiMate language to design software ecosystems, we extend the language using the reference architecture to enable direct and enhanced modeling of ecosystem-specific concepts. The extended ArchiMate has been implemented in a tool that we use to design a real-world ecosystem called F-Droid. Our results show the reference architecture captures the F-Droid ecosystem architecture. Bad architectural smells are detected, and improvement suggestions are made. Our work will assist platform providers to improve architectural decision-making by making informed design decisions.
Machine Learning-based Automated Problem Categorization in a Helpdesk Ticketing Application

To handle internal complaints, some companies have implemented a helpdesk system while some other processes are still carried out manually. The helpdesk ticket is categorized manually by human operators. This procedure prone to be an error resulting in many tickets bounced to the wrong business unit and delaying the complaint handling. In this study, an automated problem categorization based on the title of helpdesk ticketing using machine learning is studied. The results show that the random forest classification has the highest accuracy value of 82%.
Development of a Programming Learning Tool Using a Train Toy

In Japan, programming education has become compulsory in elementary school, and it is expected that programming thinking will flourish in elementary school and beyond by fostering programming thinking in young children. There have been several studies of toys for fostering programming thinking in young children. However, they have some problems. In this letter, we develop a programming toy for young children using ‘Plarail’ train toy to overcome problems of the toys used in the previous studies. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.
Work in Progress: Role-based Deep Reinforcement Learning with Information Sharing for Intelligent Unmanned Systems

Intelligent unmanned systems (IUSs) are distributed systems composed of multiple agents that share information or cooperate to accomplish specific complex tasks. Agents of the IUS are capable of perception, cognition, control, decision-making, and action. In some cases, the environmental situation and task objectives faced by the IUSs are constantly changing with time. Thus, IUSs are time-sensitive systems. To accelerate the task execution time and response speed, IUSs use artificial intelligence technology to increase the speed and quality of the `observation-orientation-decision-action' (OODA) cycle of task execution. IUSs will tend to decompose the system into different functional units in the future, and individuals take different task roles from the functional perspective of OODA. The system is evolving from a linear OODA cycle of individuals to a cooperative OODA (Co-OODA) with different node roles. At present, the reinforcement learning (RL) algorithm is the mainstream method to solve IUSs cooperation problems. However, it does not adapt to the Co-OODA with different roles; and cannot maximize the Co-OODA system's potential. This paper introduces the role-based Co-OODA system. Furthermore, we propose and design a role-based deep reinforcement learning framework and its corresponding information sharing mechanism.
Iterative Doppler-Only Track initialization enhanced with Direction of Arrival information

We study the sensitivity of tracking initialization in a passive radar receiver network which uses the concept of forward-scattering for target tracking. Multi-static radar on VHF is used with Doppler-only information, which as a method is a challenging way of tracking targets. Doppler does not reveal the location of the target easily and this often leads to ambiguous location estimates on track initialization. Direction of arrival information (DOA) can cancel ambiguity on track initialization and the impact of DOA information is discussed in this paper. The validity of the track initialization is verified with reference data based on Automatic Dependent Surveillance - Broadcast (ADS-B) information. The Extended Kalman filter is used for tracker after the track initialization with Doppler-only measurements.
Digital Transformation of E-Commerce Services and Cybersecurity for Modernizing the Banking Sector of Pakistan

The practice of protecting computers, websites, mobile devices, electronic services, networks, and digital data from malicious attacks is known as cybersecurity. Since political, military, private, financial, and medical institutions collect, process, and maintain massive volumes of data on computers and other devices, cybersecurity is critical. Sensitive data, such as intellectual property, financial data, personal records, or other forms of data, can make up a large amount of the data. Improper access or disclosure to that data can have profound implications. Technology has undoubtedly made a significant change in every aspect of life in Pakistan, whether it is a financial or non-financial sphere. Technology's usage is thoroughly utilized by banks worldwide. They have started adopting it frequently because of the immense need to achieve goals and satisfy customer needs more efficiently. Almost all leading banks have now provided e-commerce facilities. Over time, more and more services and facilities are offered to bank customers conveniently via e-commerce products.
Pedagogical Interface Agent for Kenya Sign Language

This paper proposes a pedagogical Interface Agent (PIA), for Kenya Sign language (KSL). The PIA is designed as a font for KSL that will assist new learners, as well as people with interest, to learn KSL alphabet. The PIA translates the alphabets typed on the keyboard to the equivalent KSL alphabets. This PIA is not only important to learning KSL but it can also be used to create fingerspelling learning materials as well as KSL datasets. The PIA was designed following the Design Science Research (DSR) methodology. The PIA agent was developed using several software applications. It runs well on the Microsoft office suite packages. All the alphabets of the font were typed in Microsoft word and Microsoft PowerPoint and found to be responding 100%. Therefore, the PIA agent is recommended as a font to be used by both the HI and hearing people in learning the KSL alphabets.
Some aspects of teachers'readinness for health activitles in educational institution

In the article revealed different approaches to the definition of teachers’ professional readiness to educational activities based on the theoretical analysis of scientific and educational literature. And also described different views of researchers about the readiness of the future teacher to realization of healthy environment activities. In particular, disclosed the essence of the concept of readiness of teachers to formation of to realization of healthy environment activities. Described structural components of the teachers’ readiness of readiness to carry out health activities are identified and described.
Increasing cyber security awareness by creating a case study and video project

Writing case studies in undergraduate and graduate courses in cyber security is a great way to learn class material. In this assignment, a student creates a case study and video about a cyber secur...
A complementary validation of Egyptian faience jewellery reconstruction using elemental and statistical analyses

Jewellery made from faience beads are frequently recovered from Middle Kingdom tombs at Abydos, Egypt. Through the passage of time, many of these artefacts became displaced from their original context due to post-depositional disturbances. We measured the elemental compositions of nine beaded faience artefacts to determine whether or not it was possible to infer the original arrangements of separate, multicomponent artefacts. Using statistical analyses of the elemental compositions, we demonstrated that it is possible to reconstruct the configurations of nine faience artefacts as defined by the groupings listed in their excavation reports.