Reviewerly/exHarmony huggingface dataset:
Performance Appraisal Recommendation System for Private IT Organizations using Machine Learning Approach

Performance appraisal is one of the crucial decision-making and time-consuming processes in private organizations which needs to be executed systematically and effectively to evaluate their most important asset - employees. Developing an effective performance appraisal system requires identifying, defining and measuring the employees’ performance factors in organizational context.In view of carrying out a fair and unbiased performance appraisal, the appraisal process must be combined with an assistive framework to recommend an equitable salary raise to reward the employee based on their performance. Therefore, in the light of this research, we select the prevalent factors which significantly influence employee performance appraisal determining the appraisal amount to assist decision makers in the process. We propose a performance appraisal recommendation system using the Machine Learning model by investigating the common practices followed in IT companies in order to make the process more effective. From a sample of 1066 employee’s data from various private sector organizations, the results indicate 89.5% of the recommended appraisal is close to the manager’s amount. This shows the applicability of the proposed recommendation system as an effective tool in the appraisal process.
Reviewing a year of ARC White Papers: Covering Cyber Scenarios, Estimative/Probabilistic Language and Gen-AI evaluation

Reproduced here throughout this ARC White Paper, all of the previous ARC White Paper ‘Executive Summaries’/‘Introductions’ to their ‘Key Conclusions and Takeaways’ are revisited. These have all been brought together in one document so that the core findings from the ARC series of exercises and research work over the past year, spanning from October 2022 to September 2023, are presented collectively alongside one another.This concluding White Paper also offers ready comparative and building insights relating to topics as diverse as the developing multi-methodologies of Intelligence Engineering (IE) to Strategic Options Analysis (SOA), as well as how they can be effectively used in combination. Communicated insights include how IE and SOA methodologies and approaches figure in relation to currently rapidly evolving Generative-Artificial Intelligence (Gen-AI) technologies, involving especially OpenAI’s ChatGPT and Google’s Bard.Collective ARC White Paper findings in the present series go further. Gen-AI technologies are simultaneously tested, helping uncover novel takeaways, such as relating to Gen-AI use and value (and, equally, not) in contexts as diverse as strategic foresight scenario development through to ‘Red Team(ing)’ activities. Distinct limitations from shortcomings through to discernible operational parameters soon emerge with regard to Gen-AI systems and their closely associated technologies. Most notably, substantial preparation is required in the form of much effort being devoted to ‘prompt-engineering’ tasks, which is currently seen as a growth area. Classic ‘Cost vs. Value’ questions quickly arise relating as to where resources are best allocated and are most absorbed, raising many ‘return on investment’ queries when processes are taken as a whole. More and substantially improved key performance indicators in relation to Gen-AI systems continue to be required in their fashioning. Ultimately, as we find time and again, much remains open to being closely watched into rapidly advancing and continuing futures.
Validity Claims in Children-AI Discourse: Experiment with ChatGPT

Large language models like ChatGPT are increasingly used by people from all age groups. They have already started to transform education and research. However, these models are also known to have a number of shortcomings, i.e., they can hallucinate or provide biased responses. While adults might be able to assess such shortcomings, the most vulnerable group of our society – children – might not be able to do so. Thus, in this paper, we analyze responses to commonly asked questions tailored to different age groups by OpenAI’s ChatGPT. Our assessment uses Habermas’ validity claims. We operationalize them using computational measures such as established reading scores and interpretative analysis. Our results indicate that responses were mostly (but not always) truthful, legitimate, and comprehensible and aligned with the developmental phases, but with one important exception: responses for two-year-olds.
Documentation and Educational Materials for a 2nd Edition of the Java Modeling Language

JML is an ambitious project in formal specification and verification, ongoing since 1997, that has aimed to bring value to Java programmers. Participants in the project are now undertaking a significant revision of the language itself (Cok, Leavens, Ulbrich) and accompanying that with educational materials (Cok, Meija, Leavens), documentation rewrites and tool upgrades (Cok). The current state of this work-in-progress is presented here in order to encourage wide-spread contribution and comment on the language revisions, its semantics, the educational tutorial, and related tools.
On the Need for a Common API for Abstract Domains of Object-Oriented Programs

In the last years almost all families of programming languages, from imperative to functional, logic, object-oriented and machine code, have been subject to static analysis by abstract interpretation. The use of a principled approach to static analysis based on the theory of abstract interpretation provided mathematical tools to reason about program properties and allowed for the rigorous and incremental design of precise and scalable static analyzers, ensuring soundness by construction. The large variety of abstract domains for many different programming languages, the ability to combine and refine them with standard abstract interpretation tools and the availability of mature abstract domain libraries allowed easily porting, reusing and experimenting with techniques born in a specific family to other programming languages and properties.
Book of Proceedings of the First International Congress of the HBTSSN 2020

The Book of proceedings of the first international congress of the Haematology and Blood Transfusion Scientists Society of Nigeria is a compendium of the academic contents of the events that transpired during the congress tagged HBTSSN 2020 with the theme Healthy Blood, Healthy Nation: The haematology Scientists perspective. It is a collection of papers presented from the 17th to 19th of March 2020 at the Hotel Presidential, Port Harcourt, Nigeria. The publication of this congress proceedings is meant to serve the following purposes: Providing a great place for participants to present their research findings, novel approaches or new methodology. Allowing researchers to engage with the research teams and community doing research on the same subject. Staging and spreading the new ideas to the scientific community. The HBTSSN benefits from publishing the proceedings as it creates awareness and adds value to our great society. Attracts more authors to participate in future conferences. It’s a faster way of making your results available to the wider world Citable for academic appointments and promotions This congress proceedings is having a unique ISBN number and is catalogued in the National Library. It comprises of three parts: 1) Keynote and plenary lectures. 2) Abstracts of original articles for oral and poster presentations and 3) Workshop papers on Building a successful research career in Haematology and Blood Transfusion I wish to acknowledge the efforts of the Chairman of Scientific committee, Prof Osaro Erhabor and other distinguished members of the scientific committee for their diligence in reviewing the abstracts submitted to this congress. I also thank the speakers who made their papers available for publication. This is the maiden edition and we hope to improve in the subsequent editions. I sincerely wish that every participant will find this book of proceedings useful. Prof Z. A. Jeremiah President
Music, Musical Semiology, Musicology: Contribution of the Philosophy of Complexity and Musical Heuristics

Abstract My contribution postulates the need to include Edgar Morin's principles of philosophy and complexity as additions to musical semiology and musicology so as to be able to tackle analyses basing oneself on a polysemic attitude that is most likely to convey all the riches of the musical phenomenon especially regarding its fluidity and dynamics. The first part of the article aims at approaching Jean-Jacques Nattiez's musical semiology as well as the analyses that stem from it. The second part attempts to make the notion of musical work intelligible as its systematic complexity is examined while the difference between the score and the work is defined. The re-structuring of a work that is made possible by musical heuristics gives way to an "embodied" approach of reference pieces thus giving Nattiez's analyses the follow-up that is necessary for them to come to fruition. The last part of my communication attempts a musicological implementation of the three underlying principles of the philosophy of complexity. Keywords: Music, musicology, semiology, complexity, heuristics.
Impact of Digitalization in Higher Education and Smart Learning Techniques

In higher education, computers have been utilized for many years. In the last few years, education has become digitalized, where faculty/lab technicians use advanced technology to teach students and provide deep knowledge. In higher education, new pedagogy techniques were brought into the possibility of effectively conducting online/offline classes. In this chapter, the authors have analyzed the impact of digitalization in higher education and intelligent learning techniques. The authors will discuss how new digitalization techniques and development anticipate student performance. Advanced machine learning and deep learning techniques could extract and provide more knowledge to the students. Virtual simulation is becoming increasingly popular in the education and training sector. It involves using software programs and virtual environments to create simulated experiences which allow learners to practice and learn new skills in a safe and controlled environment.
English Language Teachers' Perceptions on AI's Role in Alleviating Digital Burnout

This chapter delves into the viewpoints and experiences of current English language teachers regarding digital burnout in second language acquisition (SLA) and the possible role of artificial intelligence (AI) in reducing its negative impacts. Content analysis was used to extract themes and patterns from data gathered through interviews and journals. Increased screen time and emotions of being overwhelmed are only two of the issues the report cites as obstacles to online learning. Significant difficulties include learning to use different platforms and dealing with feelings of isolation. The study also highlights the potential advantages of using AI technologies in SLA, including tailor-made learning paths, instantaneous feedback, diversifying activities, and engagement and fun. This research helps expand the knowledge of digital burnout and sheds light on the usefulness of AI resources for teaching foreign languages.
Understanding Robotics in the Tourism and Hospitality Industry

This chapter aims to explore the perceptions and attitudes of people regarding the utilization of robots in the hospitality and tourism industries. The objective is to gain insight into how these industries may need to adapt to meet the expectations and preferences of consumers in this emerging technological landscape. The study focuses on various domains within the hospitality and tourism sectors, hotel operations, museums, airports, and other transportation stations. The outcomes of this research will provide valuable insights for industry stakeholders, policymakers, and service providers in designing and implementing effective strategies to meet the evolving expectations of consumers. Ultimately, this study seeks to bridge the gap between technological advancements and consumer preferences in the Indian context. Furthermore, it will contribute to the body of knowledge in the field of robotics and hospitality, serving as a foundation for future studies and initiatives aimed at enhancing customer experiences and satisfaction leading to consumer happiness in these industries.
Clausal types and syntactic subjects

In previous work (Di Domenico, 2020), I have analyzed the narrative productions of a group of Italian native speakers, in order to investigate whether the core assumption of the Position of Antecedent Hypothesis, proposed by Carminati (2002) for the resolution of intra-sentential pro in Italian, could be extended to the discourse level despite Carminati’s (2002, p. 306) claim to the contrary. The data suggested that, while pro was overwhelmingly the most attested anaphoric device, Discourse Referents were never introduced pre-verbally; the data, however, also revealed that Discourse Referents introduced as non-subject constituents were restated in subject position for subsequent resumption (through a pseudo-relative, a subject relative or an Accusative + Infinitive clause). This led to the conclusion that the core assumption of the Position of Antecedent Hypothesis could be maintained at the discourse level as well: in Italian pro looks for an antecedent in Spec, IP also inter – sententially. The present work addresses the same question in Greek, which is, as Italian, a null-subject language, and compares the Greek results to the Italian ones of the previous work. The analysis reveals that things work in part differently in the two languages, given that the pre-verbal subject position is frequently employed for the introduction of brand new Discourse Referents in Greek, contrary to Italian. Restatement in subject position, however, modulo some differences concerning the clausal types attested in the two languages, still holds whenever Discourse Referents are introduced as non-subject constituents, suggesting that pro looks for an antecedent in Spec, IP in Greek as well as in Italian.
The impact of information security management guide utilization on technological and institutional information security measures in university libraries in Türkiye

The study examined whether the levels of technological and institutional information security measures implemented in university libraries in Türkiye differ based on the usage of a corporate information security management guide. The study was conducted through a literature review and survey method in a total of 199 university libraries in Turkey actively operating in 2023, comprising 124 state universities and 75 private universities. To ensure the contributions of all university libraries population was obtained in a homogeneous manner, a purposive sampling method was used, collecting data from one staff member from each university library. The findings reveal that there are significant differences (p < 0.05) in the levels of both technological and institutional information security measures, depending on the presence and utilization of a corporate information security management guide in university libraries. These findings demonstrated that an enterprise information security management tool is effective in influencing information security practices in university libraries. This result confirmed the hypothesis that there are significant differences in the implementation levels of technological and institutional information security measures based on the presence and usage of an enterprise information security management tool in university libraries in Turkey. Considering the lack of comprehensive studies on information security management in university libraries in Turkey, this research demonstrates its uniqueness by approaching the topic with a holistic approach.
New realities, spaces and times for play and learning: The integration of the internet of toys in early childhood education

As technology continues to become more ubiquitous in our lives, the internet of toys (IoToys) is providing new opportunities in education. Dr. Ioanna Palaiologou, Sarika Kewalramani and Maria Dardanou, explain more about the IoToys and how this can be incorporated into early years settings in a constructive and beneficial way, while still keeping the individual child at the forefront.
A Calculus of Delayed Reductions

We introduce the Calculus of Delayed Reduction (cdr), that expresses that redexes can only be contracted when brought to the right position in a term, and will show that Call by Name or Value (cbn, cbv) reduction for the λ -calculus can be modelled through reduction in cdr, and that the cbn fragment of the -calculus can model reduction in cdr. cdr is a Call by Push Value calculus (cbpv) in that it separates terms in computations and values, with their corresponding types. Some simulation results were already achieved by others for cbpv, but only up to equality for cbv; for cbn past results are rather weak.
Connecting AI: Merging Large Language Models and Knowledge Graph

Combining the generative abilities of large language models with the logical and factual coherence of knowledge graphs using a connected artificial intelligence architecture minimizes each system’s shortcomings and amplifies their strengths across many real-world domains.
Impact and Limitations of AR-Based Guidance for Assembly Workers

To assess the extent to which augmented reality can displace traditional assembly instructions, we conducted a field study in a German manufacturing company. We documented the errors made by the workers and whether they were able to perform the process until the end without any additional assistance.
Is the Solution for Cybercrime Also a Path to Greater Productivity?

In today’s cybersecurity landscape, the primary goal is to protect against threats, but cybersecurity’s influence extends beyond mere defense. We highlight how cybersecurity practices can impact productivity in both software development and day-to-day operations.
AMCFNet: Asymmetric multiscale and crossmodal fusion network for RGB-D semantic segmentation in indoor service robots

Red-green-blue and depth (RGB-D) semantic segmentation is essential for indoor service robots to achieve accurate artificial intelligence. Various RGB-D indoor semantic segmentation methods have been proposed since the widespread adoption of depth maps. These methods have focused mainly on integrating the multiscale and crossmodal features extracted from RGB images and depth maps in the encoder and used unified strategies to recover the local details at the decoder progressively. However, these methods emphasized crossmodal fusion at the encoder, neglecting the distinguishability between RGB and depth features during decoding, thereby undermining the segmentation performance. To adequately exploit the features, we propose an efficient encoder-decoder architecture called asymmetric multiscale and crossmodal fusion network (AMCFNet) endowed with a differential feature integration strategy. Unlike existing methods, we use simple crossmodal fusion at the encoder and design an elaborate decoder to improve the semantic segmentation performance. Specifically, considering high- and low-level features, we propose a semantic aggregation module (SAM) to process the multiscale and crossmodal features in the last three network layers to aggregate high-level semantic information through a cascaded pyramid structure. Moreover, we design a spatial detail supplement module using low-level spatial details from depth maps to adaptively fuse these details and the information obtained from the SAM. Extensive experiments are conducted to demonstrate that the proposed AMCFNet outperforms state-of-the-art approaches.
Data-Dependent Confidentiality in DCR Graphs

We present DCRSec, a confidentially aware declarative process language with data that employs data-dependent security levels and an information flow monitor that prevents the violation of information flow policies. Data-dependent security levels have been used to shape precise information flow policies and properly identify security compartments. We use an illustrative example to show that it also models process instances in a flexible but precise way.
Strongly-Typed Multi-View Stack-Based Computations

High-level languages are often implemented by transforming them into a stack-based intermediate language. To ensure correctness of the implementation, it is desirable to have a type-system for the stack-based code that ensures that the required arguments are available on the stack. This is quite challenging since the stack contains values of mixed types. Moreover, a single stack is shared by all basic stack instructions and the functions implemented with those instructions. Just like basic instructions, function calls are expected to replace their arguments by the result and to leave the rest of the stack untouched.
Multicompatibility for Multiparty-Session Composition

Modular methodologies for the development and verification of concurrent/distributed systems are increasingly relevant nowadays. We investigate the simultaneous composition of multiple systems in a multiparty-session-type setting, working on suitable notions of interfacing policy and multicompatibility. The resulting method is conservative (it makes only the strictly needed changes), flexible (any system can be looked at as potentially open) and safe (relevant communication properties, e.g. lock-freedom, are preserved by composition). We obtain safety by proving preservation of typability. We also provide a sound and complete type inference algorithm.
Typed Equivalence of Labeled Effect Handlers and Labeled Delimited Control Operators

Algebraic effect handlers and delimited control operators are language facilities for expressing computational effects. Their labeled variations can express multiple kinds of exceptions, multiple states, and so on. We prove that labeled effect handlers and labeled control operators have equal expressive power. To show this, we develop a type-sound calculus for each facility and define macro translations between the typed calculi. The established equivalence can be used to understand and implement one facility in terms of the other.
Closure Conversion in Little Pieces

Closure conversion, an essential step in compiling functional programs, is traditionally presented as a global transformation from a language with higher-order functions to one without. Optimizing this transformation can be done at any of its three stages with various tradeoffs. After conversion, optimizations will be in the target language at the cost of a weaker equational theory. During conversion, optimizations may be embedded into the transformation itself at the cost of increasing its complexity and correctness. And before conversion, optimizations may be planned and anticipated in a specialized intermediate language (IL) where all the properties of the source program are still known, with the hope that they will survive the rest of the compilation process.
An Examination of the British Council’s Social Media Strategy in China: Insights and Implications

The rapid advancement of internet technology has ushered in the age of new media, significantly altering the means of language and cultural transmission. In this era, social media platforms demonstrate superior effectiveness, interactivity, timeliness, and convenience, outpacing traditional media outlets, and hence have amassed vast user populations. As a central player in the international promotion of English language and culture, the British Council keeps pace with these developments by employing social media for outreach. This paper scrutinizes the British Council's communication data on major Chinese social media platforms, analyzes its current practices and potential deficiencies based on the Lasswell's 5W communication model, and proposes potential strategies for improvement.