Reviewerly/exHarmony huggingface dataset:
A Qualitative Study on Relational Dialectics Among Teachers in The Workplace

This dissertation aims to determine the relational dialectics between and among teachers in the workplace. This qualitative phenomenological study was conducted at one of the tertiary institutions in Panabo City, participated by ten College teachers. The data were gathered from the participants’ responses based on the three research questions. Then, the core ideas were drawn from the participant’s responses and were grouped into major themes. The result of the study revealed that college teachers experienced tension, which was proven during the conversation. Competing discourses between teachers speak of relational dialectics. Different language events were observed, and arguments were determined by teachers’ conversations in every language event recorded. Based on the analysis of the result of the study, the three core values of the relational dialectics model, novelty vs. predictability, privacy vs. transparency, and autonomy vs. connectedness, are present among my co-teachers. With the insights elicited from the study, it is recommended that another study be conducted to assess the relational dialectics among teachers in the workplace with another model and core values.
Making sense of what you have: Developing a collection assessment program

For the second half of 2022, I had the privilege of taking a six-month sabbatical to develop a collection assessment plan for the Lamson Library at Plymouth State University. Plymouth State educates an average of 3,800 undergraduate and 900 graduate students in approximately 45 major disciplines. The Lamson Library is currently staffed by five faculty librarians, five full-time staff, and several student workers. Like most academic libraries, our materials budget has suffered from either flat or reduced funding during the past few years. Unfortunately, many of the cuts were last-minute emergencies that forced us to make decisions quickly, depending largely on cost per use data. Calculating cost per use is a valid assessment method discussed at length by Jacqueline Borin and Hua Yi. But without any other assessment, I feared the balance of subjects represented by our collection was becoming lopsided. We needed to assess our collection in other ways to determine if we were still meeting the needs of our students and faculty in their chosen disciplines. The Complete Collections Assessment Manual: A Holistic Approach by Madeline M. Kelly was immensely helpful in getting my project started. As I read the text, cited works, and recommended readings, I concluded there is one question that must lay the foundation of all assessment efforts: “What do we have?” It is important to define parameters. I focused on formats that compose the bulk of our expenses: physical books and electronic monographs and journals. Audio-visual media, the K-12 Curriculum Collection, the K-12 book collection, government documents, and special collections were excluded.
News from the Field

Cambridge University, UCSD partnership for East Asian collections awareness ACRL sets 2023 Legislative Agenda NISO announces Peer Review Terminology Standard Clarivate releases Journal Citation Reports 2023 New from ACRL—The Critical Librarianship and Pedagogy Symposium: Reflections, Revisions, and New Works FEDLINK awards recognize federal library community achievement ACRL releases Creators in the Academic Library Revised ACRL Standards, Guidelines, and Framework Companion Documents
Towards the Development of an Enhanced Certificate Verification System for West African Institutions

The current approach adopted for certificate verification in Nigeria and most West African countries rely on paper-based documentation, which makes the process extremely unreliable and clumsy, as employers need to contact the issuer of a certificate to confirm that the award is legitimate and up to date. Several researchers and vendors have come up with different approaches to using blockchain technology. However, preliminary surveys reveal that the adoption of blockchain technology could be hindered by an inadequate power supply, poor ICT infrastructure as well as poor funding. Therefore, this research explores the enhancement of the current solution to guarantee credibility and sustainability. Thus, this research seeks to propose an enhanced certificate verification system for higher educational institutions in West Africa. Keywords: Certificate, Verification, System, West Africa, Institutions, Nigeria Journal Reference Format: Nwaocha, V.O. &amp; Oloyede, A. (2022): Towards the Development of An Enhanced Certificate Verification System for West African Institutions. Journal of Behavioural Informatics, Digital Humanities and Development Research. Vol. 8.No. 3, Pp 79-85 Available online at https://www.isteams.net/behavioralinformaticsjournal. dx.doi.org/10.22624/AIMS/BHI/V8N3P7
Compression of Machine Dependent Colour Image by Colour Transformation Techniques

Aim of this paper is development of enhance-image compression techniqueformachine dependent imageusing colour transformation techniques. CMYK colour model image with .tif extension uses large amount of machine dependent data. YC b C r colour space image model is a machine independent image. Here, image conversion technique is used to convert CMYK image into RGB colour space image. Then transformation process followed by mathematical processing is used to obtain RGB to Luma and Chrominance, Intensity based image model, YC b C r ..This also results image compression.
Advancements in Optimizing Fuzzy Grid Partition for Enhanced Rule Generation Performance: Algorithms, Interpretability, and Scalability

This research focuses on optimizing fuzzy grid partitioning to enhance rule generation performance in fuzzy rule-based systems. A novel mathematical formulation is proposed, aiming to minimize the number of fuzzy grid cells while considering coverage, regularity, and overlap constraints. The study demonstrates the effectiveness of the approach through a case example in credit risk assessment. The optimized fuzzy grid partitioning scheme generates concise and interpretable fuzzy rules, improving the accuracy and interpretability of the rule-based system. The research highlights the significance of interpretability in rule-based systems and showcases the scalability and applicability of the approach across various domains. However, limitations include the lack of comprehensive comparisons, limited exploration of generalizability to different datasets, and the need for real-world implementation considerations. Nonetheless, this research provides valuable insights into optimizing fuzzy grid partitioning for rule generation and contributes to the advancement of fuzzy rule-based systems in decision support and problem-solving tasks. Future work should address the identified limitations and explore the practical implementation of the approach.
Scalable and Adaptive Fuzzy Grid Partitioning for Enhanced Rule Generation in Complex Decision-Making Systems

This research focuses on addressing the challenges of rule generation in complex decision-making systems by proposing a scalable and adaptive fuzzy grid partitioning approach. Traditional rule generation methods often struggle to handle large datasets and dynamic environments, leading to decreased accuracy and computational inefficiencies. In this study, we present a novel approach that integrates scalable and adaptive techniques to enhance the accuracy, efficiency, and interpretability of rule-based frameworks. The scalable fuzzy grid partitioning algorithm efficiently partitions the attribute space, allowing for the generation of rules in decision-making systems with a large number of data points. By incorporating data parallelization and dimensionality reduction techniques, the approach mitigates computational complexity while maintaining rule generation accuracy. Furthermore, the adaptive fuzzy grid partitioning algorithm dynamically adjusts the partitioning structure based on changing conditions, capturing evolving patterns and ensuring the relevancy and reliability of the generated rules over time. The generated rules are evaluated using fuzzy rule evaluation functions, which consider the degree of membership in the corresponding fuzzy grid cells. This evaluation process ranks and selects the rules based on their firing strengths, providing an interpretable decision-making framework for complex systems. The approach enhances the interpretability of the generated rules by capturing the uncertainties and complexities inherent in decision-making processes. To validate the effectiveness of the proposed approach, we conducted experiments using a credit risk assessment case example. The results demonstrate improved accuracy and efficiency compared to traditional rule generation methods. The generated rules offer transparency and insight into the factors influencing credit risk assessments, enabling informed decision-making. However, this research has some limitations, including potential dataset dependencies, the choice of fuzzy membership functions, computational complexity, and the need for further evaluation metrics and real-world implementation considerations. Future research should focus on addressing these limitations and exploring the applicability of the proposed approach in diverse domains. In conclusion, the scalable and adaptive fuzzy grid partitioning approach presented in this research offers a promising solution to the challenges of rule generation in complex decision-making systems. By addressing scalability, adaptability, and interpretability, this approach enhances the accuracy and efficiency of rule-based frameworks, paving the way for more effective decision support systems in various domains.
Indian Sign Language to Speech Conversion Using Deep Learning

Sign language recognition is a worldwide concern across the globe. The use of technology has a scope in aiding the necessary help in the recognition of sign language. The major challenge lies in detecting and understanding signs, as the language differs across the various geographical regions, and there are no specific rules for understanding them. Hence, this research article uses a transfer learning algorithm with TensorFlow object detection to recognize Indian sign language. The proposed model has achieved an accuracy of around 97.87% for different types of sentences used in the experimentation. The main advantage of the proposed model is that it is feasible to identify Indian sign language and produce the corresponding voice output using speech synthesis system. The system is helpful to the deaf and dumb community's society and encourages such people's upliftment.
Stochastic Compositional Kernel Estimation for Gaussian Process Models

In kernel-based learning, the choice of kernel can greatly impact the predictive performance of the model. Kernel selection is computationally intensive. However, various methods have been suggested for its optimal estimation. For example, exhaustive, grid, randomized and nonparametric search methods are few notable mentions. The effectiveness of these approaches is dependent on the intricacies of the data and the frameworks in which they operate. For instance, in Gaussian models, the dimension of the covariance matrix presents a challenge for suitable kernel assessment. In the case of variational and MCMC-based models, the time complexity required for the ELBO and posterior convergence hinders the implementation of optimal search. As such, in addition to the respective strategy, a computationally efficient exploration should take into account the limitations of the underlying model. This paper proposes a stochastic compositional kernel search algorithm. It follows a randomized point selection and cross validation in building the gaussian model. The root-mean squared error (RMSE) is applied as a criterion to evaluate the models and the optimality of the returned mixtures in explaining the given observations. We tested the algorithm on real and synthetic data. The experiments showed, the design iteratively offers possible kernel combinations by following the path with the least RMSE score. The sparsity in model building and the stochastic approach for kernel selection has afforded the algorithm a computational advantage over other exhaustive methods. As such, it can be used as an alternative technique for a suitable kernel selection that best explain the data.
Design and Implementation of a Small Program for Collecting Ethnic Voice

The Ethnic Language Collection Mini Program is an application based on mobile internet technology, designed to help users collect and record voice and text information of ethnic languages. The use of ethnic language collection mini programs can effectively promote the inheritance and protection of ethnic languages, helping users better understand and learn about ethnic culture. Language researchers can share their voice data with other users or research institutions to promote language research and protection.
Research and Development of Shared Chess and Card Room Based on Wechat Mini Program

Based on the investigation and research on the use of traditional chess and card rooms in the province, this paper proposes to change the phenomenon that the information of offline chess and card rooms is unclear and difficult to reserve by means of technical means and real-time technology. html+ technology is adopted as the front page technology, the main logic technology language is Java, and the background database is MySQL. Realized the basic management functions of chess and card room reservation, such as booking a room, friends group, comment. The above functions are reflected in this procedure, this system has an important role for chess and card lovers to achieve information. The use of this system can achieve the purpose of understanding the situation of chess and card room and improving the efficiency of management.
Proposal: Public Registry of Property supported by non-fungible tokens (NFT)

In this work a guide is proposed, introducing the idea of alternative implementation of blockchain technology to the popularized use as a currency. As an axis of the guide, the use and support of non-fungible token technology (NFT) for the Public Property Registry (RPP) is presented, as an example, which allows us to conceive the different technological and non-technological aspects that the use of this technology would involve in contexts such as the one explained. The research of the technological fund, the institutional-legal fund, and the techno-institutional-legal is exposed, this to holistically foresee the implications that would have the use of the registry transactions of the RPP through a blockchain supported by NFT tokens. Subsequently, and based on the set of variables, the interdisciplinary research problem is externalized, while summarizing the proposal and discussing its derivations and findings. Finally, it concludes by giving an account of the main challenges and guidelines in which any organization or institution with characteristics analogous to the RPP that seeks a digital transformation and innovation in the near future will have to work.
Design of Robot End Trajectory Tracking Controller

The most important point for the manipulator to run quickly and efficiently is that we must explore the trajectory tracking control technology, so we need to master the end trajectory operation law. This topic is mainly to analyze the structural characteristics and working principle of the manipulator, create the control law of the end node system model of the workspace, calculate the actual joint torque, and conduct Kinematics analysis of the end trajectory of the manipulator, Finally, MATLAB simulation was used to verify the designed controller. Studying trajectory tracking control technology will have a positive impact on future life and can be applied practically in production and daily life to meet the needs of modern production.
Determinants of Capital Flight and its Impact on Economic Performance: A Study of Developing Economies

Capital flight imposes a great danger to the developing economies by lowering their economic activity, devaluing the currency, and hindering growth. This paper contributes to the literature by investigating the determinants of capital flight of developing economies. Determinants are studied as indices, and these indices are calculated by using the Arithmetic Mean approach. There is a two-step model; in the first part,determinants are discussed, and in the second part, capital flight is used as an independent variable, and its impact on economic performance is measured in 57 Developing Economies. GMM (Generalized Method of Moments) is used for the determinants of capital flight, and panel GLS (Generalized least square) is used to check the impact of capital flight on economic performance. Macroeconomic variables (external debt, inflation, exports, interest rate, and exchange rate) are also part of the study with four indices as determinants (Country Risk Index, Economic Freedom Index, financial inclusion index, and Governance institution and corruption index). Results suggested that all included indices are significant along with all macroeconomicvariables. Country risk, external debt, and exports have a negative coefficient, and othershave a positive coefficient value. Capital investment, foreign direct investment, and Gross domestic product are used as proxies of economic performance. Results of GLS have shown there is a significant and negative impact of capital flight on economic performance. Capital flight is measured by using the residual methodology.
LiDAR Segmentation-based Adversarial Attacks on Autonomous Vehicles

Autonomous vehicles utilizing LiDAR-based 3D perception systems are susceptible to adversarial attacks. This paper focuses on a specific attack scenario that relies on the creation of adversarial point clusters with the intention of fooling the segmentation model utilized by LiDAR into misclassifying point cloud data. This can be translated into the real world with the placement of objects (such as road signs or cardboard) at these adversarial point cluster locations. These locations are generated through an optimization algorithm performed on said adversarial point clusters that are introduced by the attacker.
How to Construct Corresponding Anchors for Incomplete Multiview Clustering

Anchor based incomplete multiview clustering has grasped growing interest recently because of its great success in effectively partitioning multimodal data. However, due to the absence of label information, the constructed anchors could be mismatched. Such an Anchor Mismatching Problem (AMP) will cause the structure of generated bipartite graph to be chaotic, degrading the clustering performance. To tackle this issue, we design an algorithm termed Constructing Corresponding Anchors for Incomplete Multiview Clustering (CCA-IMC). Specifically, we first devise a permutation strategy to transform anchors on each view. Subsequently, we directly generate the consensus bipartite graph, which is shared for all incomplete views, by the transformed anchors rather than by fusing each view-specific bipartite graph. Afterwards, all anchors and permutation matrices as well as the consensus bipartite graph are jointly optimized in one common framework so as to promote each other. In such ways, anchors are rearranged towards correct matching relationship according to the consensus graph structure. In addition to these, our CCA-IMC has also been proven to be with linear time and memory overheads, which makes it able to scale up to work with large-scale tasks. Massive experiments implemented on ten popular datasets give evidence of our superiorities compared to current strong IMC competitors.
Cyberlearn

Cybersecurity is growing in importance, with recent cyberattacks showing an exceptional level of impact in organizations. This chapter presents a cybersecurity capability building proposal for organizations that the authors designate cybersecurity learning framework (CyberLearn). The chapter discusses cybersec initiatives in Portugal, in the European Union, in the North Atlantic Treaty Organization, and the United States of America, introducing the NICE framework as a basis to develop the CyberLearn framework and the concept representation considering functions, roles, and work roles and the knowledge units related to each role area. This framework has been applied in Portugal by Técnico to meet business needs on this domain.
Development Of Web-Based Information System For Promotion Of Kasongan Craft

. The development of a Web-Based Information System for the Promotion of Kasongan Pottery Handicrafts serves as a promotional medium for a number of Kasongan pottery company owners who want to promote their handicraft products through the internet. This website provides facilities for web visitors who want to know information about Kasongan pottery, both the products produced and the company that produces the pottery, news about Kasongan, links to Klik_BCA for foreign currency exchange rates, and polls for opinion polls. Information about products includes product photos, descriptions, sizes, colors and prices, so that web visitors can see and know the products produced by a company clearly. Company owners can register as a member of this web online. The facilities provided for members of this web are company product updates, edit company data and change passwords. Members may have their own website outside this website or not have a website at all. This website is built using the Xampp application software package which includes Apache as a web browser, MySQL for databases and PHP as a programming language. For web display design using Macromedia Dreamweaver 8, while for photo editing using Adobe Photoshop CS2 and ACDSee 8. MySQL for database and PHP as programming language. For web display design using Macromedia Dreamweaver 8, while for photo editing using Adobe Photoshop CS2 and ACDSee 8. MySQL for database and PHP as programming language. For web display design using Macromedia Dreamweaver 8, while for photo editing using Adobe Photoshop CS2 and ACDSee 8.
The characteristic equation of the matrix over min-plus algebra

Max-plus algebra is one of many idempotent semi-rings. The max-plus algebraic structure is semi field while the conventional algebra is a field. Because of their similar structure, various properties and concepts in the conventional algebra such as characteristic equations have max plus algebraic equivalence. The characteristic equation has been proved in the max-plus algebra. The other semi-field is min-plus algebra. Because of the structure in the min-plus algebra is also similar to the conventional algebra, the characteristic equation also has a min-plus algebraic equivalent. In this paper, it is discussed how to prove the characteristic equation of the matrix over conventional algebra into the min-plus algebra. The results are almost the same. The addition and multiplication operations in the conventional algebra are replaced by min and plus operations in the min-plus algebra. In addition, because of the min-plus algebra does not define the subtraction operation, the formulation of the characteristic equation of the matrix over min-plus algebra is not equal to zero.