Reviewerly/exHarmony huggingface dataset:
Perancangan Sistem Microsoft Office Access pada Toko Batam Sumber Indah

Financial reports are a source of information that stakeholders use to make decisions regarding controlling company operational costs, understanding company profits and losses, understanding debts and liabilities, and calculating taxes. As financial reports also play an important role in Micro Small and Medium Enterprises sector, there are still many Micro Small and Medium Enterprises sector that have not prepared financial reports or have prepared them in the middle of difficulties and complications. This community service activity is carried out using survey and interview methods. After finding the obstacles faced by Batam Sumber Indah Store, the solution was to design an accounting system information in the form of Microsoft Office Access. The results of this activity are expected to increase the efficiency and effectiveness of the Batam Sumber Indah Store in producing reliable financial reports.
Teachers’ and Students’ Perception on the Use of Cake Application toward Their Speaking Skill On Merdeka Belajar Era

The purpose of this research is to understand and describe the perceptions of teachers and students about the use of cake applications on English speaking skills. The method applied in this research is descriptive qualitative which is presented in the form of a proportion diagram. The data collecting technique of this research used observation,questionnaires, and documentation. The researcher did direct observation in SMP Surya Dharma Bandar Lampung both in the class and out class. The questionnairesof this research used the four most alternative answers, namely strongly agree, agree, neutral and disagree. The questionnaires consisted of 10 numbers questions. The documentation technique were the documentation of score English Speaking skill from the English teacher before giving the cake application. Participants in this research were 40 students of SMP Surya Dharma Bandar Lampung and 10 teachers of SMP Surya Dharma Bandar Lampung. This research used 9th grade class. Based on the research results obtained, it showed that most teachers and students agree with the learning method using the Cake application. The students were more interested in English learning. The students felt enjoy and fun learning English using the Cake application. Therefore, this research found that the variety of teaching method gave positive effect for the students.
Analysis of Energy Consumption Optimization for Shared Cache Conflicts

Multi-core shared cache conflict constraint technology for low energy consumption and low latency can be widely applied in various industries such as intelligent automobiles, aviation, aerospace, medical, industrial control, etc., and has important application backgrounds. This paper analyzes the energy consumption optimization method for multi-core shared cache conflict constraints, providing important reference for energy consumption optimization research under shared resource conflicts and promoting the development of multi-core industries.
Particle Swarm Optimization for Penalize cox models in long-term prediction of breast cancer data

The particle swarm optimization algorithm (PSO) was applied to penalize the Cox model for predicting long-term outcomes of breast cancer patients. This study makes use of data on 198 patients' breast cancer survival, including their age, estrogen receptor status, tumor size, and grade, as well as the expression levels of 76 genes. The objective was to identify a subset of features that could accurately predict patient survival while controlling for overfitting and model complexity. PSO was used to search for optimal model parameters. The algorithm was designed to minimize a penalized partial likelihood function, which balances the tradeoff between an accurate model and model complexity. The values of the objective function were compared with other feature selection techniques, including the Least Absolute Shrinkage and Selection Operator (LASSO) and Elastic regression, and were found to perform better in relation to predictive accuracy and feature selection. The study results showed that PSO-based Cox models with cross-validation to regularization parameters had higher prediction accuracy than models trained with other feature selection methods. The PSO algorithm identified a subset of features that were consistently selected across multiple iterations, indicating their importance in predicting patient survival. Overall, the study demonstrates the potential of PSO-based feature selection in improving the accuracy and interpretability of Cox regression models for predicting long-term outcomes in breast cancer patients.
Use Of RPA For Email Automation With Salesforce Integration

In today's fast-paced corporate environment, email automation has become a critical component of efficient business operations. However, managing email automation processes can be time-consuming and labor-intensive, necessitating significant manual effort. To address these challenges, the integration of Robotic Process Automation (RPA), Artificial Intelligence (AI), and Salesforce offers a powerful solution. By automating email processes using RPA and AI, and leveraging sentiment analysis on incoming emails, businesses can streamline their email automation activities, ensuring targeted, personalized, and efficient communication. This research paper aims to provide an in-depth exploration of the integration of RPA, AI, and Salesforce in email automation. The paper outlines a comprehensive framework for implementing this integration, covering key steps such as defining the project scope and objectives, assessing the current email process, selecting appropriate RPA tools and AI technologies, developing an automated workflow, integrating with Salesforce, testing, and enhancing the automation process. The proposed approach enables businesses to simplify their email operations, reduce manual tasks, and achieve better results. By leveraging RPA and AI technologies, organizations can automate email creation, personalization, scheduling, tracking, and categorization. The seamless integration with Salesforce allows for the measurement and evaluation of email performance indicators, providing valuable insights into customer demands. This research paper contributes to the growing body of knowledge on RPA, AI, and Salesforce integration in email automation. This research paper demonstrates the potential of RPA as a technology that streamlines operations, enhances productivity, and empowers employees to focus on higher-value tasks. The integration of RPA, AI, and Salesforce in email automation represents a significant step towards achieving organizational success in the digital age.
METHODS OF EXPERIMENTAL WORK ON THE FORMATION OF CIVIL COMPETENCE OF STUDENTS OF TECHNICAL COLLEGES

The article is devoted to the description of the methodology of experimental work on the formation of civic competence of students of technical colleges. The methodology is defined by the author as a systematic set of measures aimed at solving a single problem, which requires the combined efforts of performers. Its main purpose is purposefulness, organization of methods, forms, means and actions of all subjects of the formation of students' civic competence with their orientation towards the final result, while not depriving the performers of initiative, creativity and independence. The measures proposed by the author were aimed at the formation of cognitive personal and activity components of civic competence. The author considers the ability to operate with concepts in the plane of "citizenship" to be the basis for the formation of the cognitive component of civic competence. The personal criterion is interpreted as determining in the process of forming the civic competence of students, since one of the main tasks of the formation of civic competence is the transformation of acquired civic knowledge into personal beliefs as a strong established opinion. The formation of professional competence according to the activity criterion takes place in the conditions of the implementation of the civic position in practice. For this, simulation methods are widely used during training. The main methods of forming civic concepts were: formulation of the definition based on the key features of the concept; compilation of associative chains, comparative analysis; creating an associative-graphic picture of the concept; contextual use of the concept in plot-illustrative material (thematic mini-narrative, presentation, etc.); compilation of thematic structural and logical schemes, etc. The method of forming students' civic competence aims to improve this process. Its implementation is carried out in the following directions: coordination of purposeful activities of students studying in various educational programs with the aim of forming civic competence; improvement of the theoretical and methodological foundations of the formation of civic competence of students; information provision of the process of formation of students' civic competence.
A Sound Abstraction Method Towards Efficient Neural Networks Verification

With the increasing application of neural networks (NN) in safety-critical systems, the (formal) verification of NN is becoming more than essential. Although several NN verification techniques have been developed in recent years, these techniques are often limited to small networks and do not scale well to larger NN. The primarily reason for this limitation is the complexity and non-linearity of neural network models. Abstraction and model reduction approaches, that aim to reduce the size of the neural networks and over-approximate their outcomes, have been seen as a promising research direction to help existing verification methods to handle larger models. In this paper, we introduce a model reduction method for neural networks with non-negative activation functions (e.g., ReLU and Sigmoid). The method relies on merging neurons while ensuring that the obtained model (i.e., the abstract model) over-approximates the original one. Concretely, it consists in merging a set of neurons that have positive outgoing weights and substituting it with a single abstract neuron, while ensuring that if a given property holds on the abstract network, it necessarily holds on the original one. In order to assess the efficiency of the approach, we perform an experimental comparison with two existing model reduction methods on the ACAS Xu benchmark. The obtained results show that our approach outperforms both methods in terms of precision and execution time.
Blockchain-Based Trust Management for IoMT Environment

Nowadays, many services keep evolving and can be used in different environments. One of the challenging environments is the Internet of Things, which makes people’s lives easier. Nevertheless, securing these systems is a big challenge. To address this challenge, several methods have been proposed to establish a trust level for entities considering different characteristics, basically the direct observations and feedbacks. In this paper, we present a trust computation model that considers not only the collected observations from different nodes, but also the collected medical data. In this contribution, we choose to work with ECG data. In our model, a decentralized propagation method is adopted where we use a private blockchain to track different trust updates. The results show the time required to compute the trust.
Populating the Zoo of Rugged Pseudorandom Permutations

A Rugged Pseudorandom Permutation (RPRP) is a variable-input-length tweakable cipher satisfying a security notion that is intermediate between tweakable PRP and tweakable SPRP. It was introduced at CRYPTO 2022 by Degabriele and Karadžić, who additionally showed how to generically convert such a primitive into nonce-based and nonce-hiding AEAD schemes satisfying either misuse-resistance or release-of-unverified-plaintext security as well as Nonce-Set AEAD which has applications in protocols like QUIC and DTLS. Their work shows that RPRPs are powerful and versatile cryptographic primitives. However, the RPRP security notion itself can seem rather contrived, and the motivation behind it is not immediately clear. Moreover, they only provided a single RPRP construction, called UIV, which puts into question the generality of their modular approach and whether other instantiations are even possible. In this work, we address this question positively by presenting new RPRP constructions, thereby validating their modular approach and providing further justification in support of the RPRP security definition. Furthermore, we present a more refined view of their results by showing that strictly weaker RPRP variants, which we introduce, suffice for many of their transformations. From a theoretical perspective, our results show that the well-known three-round Feistel structure achieves stronger security as a permutation than a mere pseudorandom permutation—as was established in the seminal result by Luby and Rackoff. We conclude on a more practical note by showing how to extend the left domain of one RPRP construction for applications that require larger values in order to meet the desired level of security.
Optimizing Business Potential: A Framework for the Implementation of Cloud Computing by SMEs in the Bolgatanga Municipality, Ghana

Cloud computing has significantly impacted businesses across different scales, presenting advantages that can be harnessed by small and medium enterprises (SMEs) in Bolgatanga. However, the effective adoption of cloud services requires a well-defined strategy. SMEs in the Bolgatanga Municipality face challenges in implementing cloud computing due to limited knowledge of its applicability, a lack of expertise, and concerns about perceived high costs, among other factors. It was therefore necessary to develop a framework that can be utilized by SMEs in Bolgatanga to implement cloud solutions. The design science research methodology was employed where an extensive evaluation of existing cloud frameworks was performed. The findings suggest that although current cloud transition models have potential value, their complexity and lack of context applicability make them less suitable. The application of the design science research methodology paved way for the development of a practical framework for successful cloud computing implementation by SMEs in Bolgatanga, Ghana. The newly developed framework would enable SMEs to embrace the benefits of the emerging cloud computing era, reducing costs, and gaining a larger market share. Beyond the immediate benefits, leveraging cloud computing will promote collaboration, agile decision-making, and innovation. Cloud solutions provide scalability and accessibility, allowing SMEs to adapt quickly to market changes, improve customer experiences, and make significant progress in their industries. Implementing cloud computing strategically by SMES in Bolgatanga is therefore not just a technological upgrade but a crucial step towards unlocking substantial business advancements for SMEs.
Accessibility by Numbers: A Critical Review of Game Accessibility Guidelines

As official regulations and unofficial recommendations on designing accessible video games have continued to grow, several organisations have developed guidelines to make the endeavour easier for developers. This chapter discusses a variety of these guidelines, tests how well these documents delineate areas for improvement in commercial video games and attempts to apply accessibility checklists based on these documents against titles with which are considered applicable. Horowitz’s findings demonstrate each of the documents’ strengths and weaknesses, concluding that while more recent publications are thorough, they also feature highly inapplicable areas that could disproportionately cost developers time and effort. However, in conducting this evaluation, he is also able to conclude by indicating some important areas of accessible game design that developers appear to almost universally neglect.
Word Classes in Computational Linguistics and Artificial Intelligence

Abstract Word classes, or parts of speech, are groupings of words that share common characteristics, both syntactic and semantic. In the fields of natural language processing (NLP) and artificial intelligence (AI), word classes have been seen as the first level of annotation for text tokens within a text processing pipeline: (pos) tagging. These pos tags were originally conceived as the first step for syntactic processing, but are often used to prepare a stream of unstructured text in for the purpose of natural language understanding. The level of understanding achieved by such a system can be as deep as achieving a semantically motivated representation of meaning or as superficial as recognizing the usage of certain types of words that are important for the task at hand. The importance of word classes in these fields is that they allow a level of abstraction that can alleviate data sparsity and are generally quite accurate, especially when considering left and right contexts and other contextual information. Further, they can help in suggesting the function of a token within a sentence, as well as suggesting its semantic type (such as event, attribute, or referent). Scientists and practitioners in NLP and AI are consumers of word classes. However, the field of computational linguistics has slightly different goals that overlap more with the interest of linguists. Computational linguists ask questions that a linguist might about word classes but the answers to these questions are arrived at either by methods employed in grammar engineering or big data methods employed in NLP.
The task of assignments in project management

When describing projects and tasks, consisting of a set of sequential and interconnected operations, dynamic models are used. A network diagram is used to visually represent the structure of the projects under consideration and the interaction of work during the project. The network diagram is represented as a graph. The components of the graph are interpreted in two ways. If the vertices are events, and the arcs between them are the duration of their occurrence, in this case the problem of project management is considered. If the vertex is the work, and the arcs are the time of their execution, then the problem of finding the optimal (or critical) path is solved. In both variants of the tasks under consideration, it is important to allocate resources or performers to commit events or perform tasks. The optimality criterion for such a formulation of tasks will be an expression for calculating the total time for the execution of work. As restrictions, expressions will be used that determine the individuality of the choice of work and the assignment of performers to them, as well as the expression on the target dates for the implementation of the project in full. The total time for the execution of work and compliance with the deadlines for the implementation of the project can be considered as two main criteria for project management. This article attempts to improve the algorithm for solving the project management problem by introducing a more flexible system of weights.
Mineralogy of Recent Sediments of Al-Teeb River Basin-East Missan Governorate, Southeastern Iraq

This research aims to define the mineralogical composition of recent sediments that were deposited around the Al-Teeb River basin in the east Missan Governorate and try to determine the provenance or the source of these sediments. The study area represents the southeastern edge of the Mesopotamian Plain and is part of it. 15 samples were collected from eight stations of recent sediment that was deposited around the Al-Teeb River; two field works are covered (December 2019 and August 2021). Mineralogical study of the sediment after separating the light and heavy minerals by heavy liquid Bromoform in order to determine the mineralogical composition of the studied samples by using the petrographic microscope the light mineral fraction composed (95.5%) of the total mineralogy. The light components of these sediments consist mainly of quartz about 25.31%, feldspars (potash and plagioclase feldspar) about 9.53%, sedimentary rock fragments (carbonate rock fragments up to 33.39%, chert rock fragments 7.65%, evaporates fragments, 7.31%), (igneous rock fragments, and metamorphic rock fragments about 6.94%). The major component of the heavy minerals residue is opaque minerals with a range of 36.76% and non-opaque minerals with a range of 63.24%. The non-opaque minerals are mainly of chlorite 7.42%, pyroxenes composed of both orthopyroxene and clinopyroxene 6.37%, amphiboles composed of hornblende, glaucophane, and tremolite 7.02%, (mica: biotite and muscovite) 9.81%, zircon 7.54%, tourmaline 5.1%, epidote group 5.91%, rutile 4.5%, kyanite 2.2%. The sediments have two types of stability: moderately stable and ultra-stable. The mineralogical composition shows that the major sources of these sediments are; the river terraces and flood plain of the river in the Mesopotamian Plain, another source of these sediments is the aeolian deposits that separated from sand dune fields in the studied area, and outcrops of ancient sedimentary formations in the southeastern of Iraq as specified by the incidence of the carbonate rock fragments.
Quantum MAC: Genuine Entanglement Access Control via Many-Body Dicke States

Multipartite entanglement plays a crucial role for the design of the Quantum Internet, due to its peculiarities with no classical counterpart. Yet, for entanglement-based quantum networks, a key open issue is constituted by the lack of an effective <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">entanglement access control</i> (EAC) strategy for properly handling and coordinating the quantum nodes in accessing the entangled resource. In this paper, we design a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">quantum-genuine</i> entanglement access control (EAC) to solve the contention problem arising in accessing a multipartite entangled resource. The proposed quantum-genuine EAC is able to: i) fairly select a subset of nodes granted with the access to the contended resource; ii) preserve the privacy and anonymity of the identities of the selected nodes; iii) avoid to delegate the signaling arising with entanglement access control to the classical network. We also conduct a theoretical analysis of noise effects on the proposed EAC. This theoretical analysis is able to catch the complex noise effects on the EAC through meaningful parameters.
Enhanced signal-to-noise ratio of array imaging using quantum state engineering

Laser active detection is a remote sensing technology that utilizes laser beams to detect various attributes of a target such as distance, orientation, height, and speed. The direct detection Signal-to-Noise Ratio (SNR) achieved by traditional array imaging systems is usually unsatisfactory because of different types of interferences, including backscattering effects and background noise. Related to this, the performance of existing methods for noise filtering are bounded by the classical detection signal-to-noise ratio. In particular, and there is no effective filtering method when the wavelength of the signal and noise is the same. To address this challenge, this study presents a novel approach to enhancing the Signal-to-Noise Ratio (SNR) of array imaging through the use of quantum state engineering. At the transmitter, we modulate the signal photons with orbital angular momentum to distinguish them from the photons of noise without orbital angular momentum. This modulation makes the signal and noise have differences in spatial intensity distribution. Due to this spatial difference, the signal and noise can be non-destructively separated after passing through the filter at the receiver, which gives enhanced SNR. The results show that this method can effectively filter out the noise with the same wavelength as the signal, and can improve the performance of array imaging detection.