Reviewerly/exHarmony huggingface dataset:
DynGraspVS: Servoing Aided Grasping for Dynamic Environments

Visual servoing has been gaining popularity in various real-world vision-centric robotic applications. Autonomous robotic grasping often deals with unseen and unstructured environments, and in this task, Visual Servoing has been able to generate improved end-effector control by providing visual feedback. However, existing Servoing-aided grasping methods tend to fail at the task of grasping in dynamic environments i.e. - moving objects.In this paper, we introduce DynGraspVS, a novel Image-based Visual Servoing-aided Grasping approach that models the motion of moving objects in its interaction matrix. Leveraging a single-step rollout strategy, our approach achieves a remarkable increase in success rate, while converging faster and achieving a smoother trajectory, while maintaining precise alignments in six degrees of freedom. By integrating the velocity information into the interaction matrix, our method is able to successfully complete the challenging task of robotic grasping in the case of dynamic objects, while outperforming existing deep Model Predictive Control (MPC) based methods in the PyBullet simulation environment. We test it with a range of objects in the YCB dataset with varying range of shapes, sizes, and material properties. We report various evaluation metrics such as photometric error, success rate, time taken, and trajectory length.
Secure Computation Meets Distributed Universal Optimality

We present a new algorithmic approach to distributed secure algorithms that is based on combining two independent lines of research: secure computation and distributed universal optimality. Our end result provides round-efficient distributed algorithms that protect the privacy of the graph vertices against a (possibly large) coalition of semi-honest adversaries.Secure Computation: The notion of perfect privacy dates back to Yao [FOCS ’82], and has been extensively addressed by the Cryptographic community over the years. Most of the prior work considers the Multi-Party-Communication (MPC) model, in which the parties are fully connected. Considerably less is known on the (round) complexity of secure algorithms for general graphs, especially under the classical message passing models, such as the CONGEST model. For any biconnected D-diameter graph, a recent line of works [Parter and Yogev, SODA 19, ICALP 19, PODC 19] presented a simulation result that protects against a single semi-honest corruption, by paying an overhead of $D \cdot \mathsf{poly}(\Delta)$ CONGEST rounds, where $\Delta$ is the maximum degree. Due to an inherent structural barrier, the generalization of the current framework to handling f corruptions, provably leads to an overhead of $O(\Delta D)^{\Theta(f)}$ rounds. This can also be shown to be tight for the class of store-and-forward algorithms <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> . <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> In which nodes can only propagate messages as atomic units, without the ability to mix multiple messages together.Secure Computation & Universal Optimality. We present an improved framework for secure computation which bypasses the current exponential in f barrier. For every graph $G=(V, E)$ with vertex-connectivity $\widetilde{\Omega}(f)$, our simulation provides a round overhead of $\mathsf{poly}(\Delta) \cdot \widehat{O}(\mathbf{S Q}(G))$. <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> The graph measure $\mathbf{S Q}(G)$ (Shortcut Quality) captures the universal optimal complexity of many network optimization tasks in the (non-secure) CONGEST model, as demonstrated in a recent breakthrough result of [Haeupler, Wajc and Zuzic, STOC 2021]. We are hopeful that the extended graph-theoretic machinery provided in this paper will find further applications in secure computation and beyond. <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> The notation $\widehat{O}(\cdot)$ hides $2^{O(\sqrt{\log n})}$ factors.
Kalman Hidden Markov Model Detect User Gesture on Proximity Capacitive Sensor

This paper presented the Kalman Hidden Markov Model detect user gesture on proximity capacitive sensor. The human interactive gesture signal analyses have been a research topic smart home fields that algorithms build in local device to recognize real time. The Kalman filter algorithms have been a research topic in prediction signal, and Hidden Markov Model also is a dynamic recognition model to object identification and classification. This paper integrated Kalman filter and Hidden Markov Model to detect user gesture in proximity capacitive sensor. The features of Hidden Markov Model used probability concept train and learn identification model, and Kalman filter optimal predicted Hidden Markov Model results. Therefore, the Kalman Hidden Markov Model methods to identify user gesture has satisfactory response.
¿Preparados o vulnerables? Conocimiento sobre fake news en docentes universitarios

Given the growing presence of fake news associated with the increasing access to communication technologies, it is necessary to be able to detect them so as not to fall victim to them and not to contribute to their propagation.Aim:&nbsp;To explore the knowledge about fake news among university teachers in Lima.Methods:&nbsp;It was a non-experimental, cross-sectional, and exploratory survey with a sample of 123 out of a population of 160 university teachers who responded to a self-administered questionnaire.Results:&nbsp;Although teachers claim to be able to recognize fake news, most failed to identifying its definition and stated that they need media and informational training. Facebook was considered the digital social network that most distributes fake news. Participants identified politics as the context with more fake news.Conclusions:&nbsp;instructors’ knowledge of fake news is not enough, so they are vulnerable. It is evident the necessity to identify specific needs to propose a media and information education plan with a practical approach that favors the development of the necessary skills.
Diseño de contenidos de aprendizaje de competencias digitales básicas para mujeres migrantes en la región de Murcia, España

This paper describes a content-based digital competences training programme aimed at a sample of 699 migrant women living in the Region of Murcia (Spain) who receive the Minimum Vital Income, as part of the «+que Emple-A» project financed by the Spanish Government through the Next Generation European funds granted to alleviate the consequences of the Covid 19 pandemic. The programme design methodology is based on a comprehensive approach to digital competence according to the European Framework DigComp 2.2 of Digital Competences for Citizenship, from which 17 didactic units have been developed. The programme is taught with the support of an online training platform in twelve municipalities of the Region of Murcia, and particularly in their public libraries whenever possible. Based on the psycho-pedagogical model of the e-IRIS Project (Vera-Baceta y Gómez-Hernández, 2021), the contents are distributed in four areas: a) Use of information in the digital context, and basic digital tools; b) Use of digital resources in life contexts; c) Development and exercise of citizenship in the digital context; and d) Use of digital resources for digitally excluded groups. The results will be obtained through a pre- and post-test questionnaire as well as a qualitative assessment by learning mediators and the participant women.
Wild Animal Intrusion Detection

Animal Vehicle Collision, commonly called as roadkill, is an emerging threat to humans and wild animals with increasing fatalities every year. Amid Vehicular crashes, animal actions (i.e. deer) are unpredictable and erratic on roadways. This paper unveils a newer dimension for wild animals’ auto-detection during active nocturnal hours using thermal image processing over camera car mount in the vehicle. To implement effective hot spot and moving object detection, obtained radiometric images are transformed and processed by an intelligent system. This intelligent system extracts the features of the image and subsequently detects the existence of an object of interest. The main technique to extract the features of wild animals is the Histogram of Oriented Gradient transform. The features are detected by normalizing the radiometric image and then processed by finding the magnitude and gradient of a pixel. As human populations expand and encroach upon natural habitats, conflicts between humans and wildlife become increasingly common. To mitigate the risks associated with wild animal intrusions into human settlements, an intelligent and proactive intrusion detection system is essential. This study proposes a novel approach to wild animal intrusion detection using deep learning techniques. The proposed system leverages Convolutional Neural Networks (CNNs) to analyze images captured by surveillance cameras placed in strategic locations. The deep learning model is trained on a diverse dataset of wildlife images to enable accurate identification and classification of different species. Transfer learning is employed to fine-tune the model for specific regions and scenarios, enhancing its adaptability and performance. Furthermore, the system integrates real-time image processing and edge computing to minimize latency and enable swift response to potential intrusions. The use of edge devices ensures that the intrusion detection system operates autonomously, reducing the need for constant human intervention. The effectiveness of the proposed approach is evaluated through extensive testing in real-world environments, including wildlife reserves, suburban areas, and agricultural landscapes. Performance metrics such as accuracy, precision, recall, and F1 score are employed to assess the system's ability to reliably detect and classify wild animal intrusions. The findings of this study demonstrate the feasibility and effectiveness of employing deep learning for wild animal intrusion detection. The proposed system not only enhances the safety of human populations but also contributes to wildlife conservation efforts by minimizing negative interactions between humans and animals. The scalability and adaptability of the system make it suitable for deployment in various geographic regions, thereby addressing the global challenge of human-wildlife conflicts.
Convolutional Neural Network-Based Automatic Speech Emotion Recognition System for Malayalam

Objectives: This research work focuses on developing a SER system using CNN and deep learning techniques for a low-resourced Dravidian Indian Language, Malayalam. The importance of speech as a powerful and natural medium of communication, capable of conveying a wide range of information about an individual\'s mental, behavioral, and emotional characteristics. With the increasing prevalence of human-machine interactions, the study of speech analysis has played a crucial role in bridging the gap between the physical and digital realms. Particularly, the field of emotion identification has gained popularity, as emotions are frequently expressed through speech cues. However, the scarcity of suitable datasets poses a challenge for researchers conducting experiments. Methods: In this paper, we address this challenge by employing Long Convolutional Neural Networks (CNN) to effectively recognize sentiments in voice recordings of Malayalam, a low-resource language. We manually construct datasets from audio clips of Malayalam movies and employ the Mel Frequency-Cepstral-Coefficient (MFCC) approach to extract features from the audio signals. Findings: By training, classifying, and testing our model using raw speech data from the dataset, the paper proposes a novel approach for recognizing emotions from voice signals processed in Malayalam with an average accuracy of 71%, indicating its ability to correctly predict emotions from vocal utterances in this under-resourced Language. Novelty: The novelty of this work lies in its dedication to addressing the challenges of emotion recognition in a low-resource language, the manual creation of datasets, and the successful adaptation of established techniques to a linguistic context where research is relatively scarce. These contributions collectively advance the field of speech emotion recognition and pave the way for further exploration in underrepresented languages. Keywords: Speech emotion recognition, Malayalam, Natural Language Processing, MFCC, CNN
Research of Innovative Library Technologies and Activities of Libraries for Children in Dissertation Works of Ukrainian Scientists

The purpose of the article is to analyze the main directions of dissertation research by Ukrainian scientists regarding the use of innovative technologies in libraries, with an emphasis on libraries for children. The research methodology is based on the use of general scientific (analysis, synthesis, generalization, etc.) and special research methods based on the specifics of the scientific task (bibliographic, information analysis, descriptive content analysis, etc.). The scientific novelty of the study consists in highlighting the main directions of dissertation work on the use of information technologies in libraries for children, with an outline of the prospects for further research. Conclusions. The main task of the modern library is the constant expansion of its activities. In the conditions of digitization of society, access to them should be obtained by anyone who has a computer or other technological device connected to the Internet, and accordingly - to the library network. Therefore, in a modern library, in particular, a children's library, a wide variety of digital elements and resources are increasingly offered for use, all that is necessary for adaptation to new technologies and to meet the dynamic needs of users. The library should not oppose digitalization, but on the contrary - unite with it, the use of digital technologies should become a normal and necessary condition of its services. All these aspects of transformational changes should not only be taken into account in the activities of the library for children, but also actively studied within the framework of librarian science. At the moment, it is possible to note sufficient articulation in the dissertation works of Ukrainian scientists of the main aspects of informatization, which is considered the foundation of the development of digital technologies. However, the latter has not yet received significant attention in the work of librarians. In addition, it is worthy of attention to study the main directions, functions and components of digitalization of libraries for children, which, in our opinion, as high-tech multimedia environments involving the tools of the information and communication approach are able to implement the main tasks of the socio-cultural mission - socialization, inculturation, formation of interest in reading and teaching.&#x0D; Keywords: information technologies, library, children's library, digitization, dissertation research, Ukrainian scientists.
James Joyce Flann O’Brienre gyakorolt hatásának felmérése

This paper examines the stylometric similarities between James Joyce and Flann O’Brien, demonstrating which works from the latter’s oeuvre are stylistically the most Joycean. We will outline the results of a series of quantitative enquiries focused specifically on Joyce and O’Brien, before offering a number of literary interpretations. It has long been argued that Brian O’Nolan, operating under the pseudonym of Flann O’Brien, is a disciple of James Joyce. This relationship remains a concern for scholars, and so our purpose here is to contribute some computational evidence to the discussion. We pinpoint those exact moments where O’Brien’s style is quantitatively similar to that of Joyce, using our results to re-engage existing arguments with renewed statistical precision.
Site strategy review for one of the leading tech companies worldwide as an example of the ‘Organisational Behaviour’ issue

As an Engagement Manager at my previous employer, I faced the ‘Organisational Behaviour’ issue to develop and deliver the site strategy consulting project for my client, one of the leading tech companies worldwide. The project aimed at advancing the Operating Model of the German site and deriving recommendations for the Site Strategy. In the following essay, I first describe the issue that I have faced at my previous employer, second develop approaches to deal with the issue, and third derive a recommendation.Firstly, the initial situation was that the company’s Safety Engineering Center, the German site, was the global hub for the company’s Internet safety work. Its strategic programs span understanding the Internet safety problem, developing solutions, and partnering with other partners and empowering users. The strategic challenge was to grow the German site by 1,500 new jobs in the next years. The focus was on current teams who were working on the Browser product, data security, and internal systems.Secondly, the project goals were to generate an understanding of the markets, clients and channels, and proposition and brands for the company’s Safety Engineering Center. In addition, the goal was to prepare a decision basis regarding the Site Strategy review. This included operational infrastructure, governance and structure, people and culture, as well as measures and incentives. The objective was to derive actionable strategic recommendations for the Site Strategy based on the Business and Operating Model.
Resonances of the Global Sanitary Crisis on the Development of Cloud Accounting. The Impact on the Accounting and Tax Fields (II)

The effects on the economy generated by the global sanitation crisis that the whole humanity recently went through prove to be unprecedented. By means of the work hereby, we aim to outline the conceptual and pragmatic universe with regard to the impact created by the speed-up of accounting digitalization under the effect of technological changes occurred following the sanitation crisis. Thus, the research implies three stages: the description of the business digitalisation framework in terms of the implementation of modern technologies in its processes, succeeded by the adoption of cloud technology at the level of the financial-accounting department and completed with the impact of cloud phenomenon regarding the digitalization of several issues related to the taxation of processes within the companies. After following these steps, the results of the research are logically correlated with the unquestionable speed-up of business processes digitalization as a result of the crisis generated by COVID-19, an issue which determines a shift in the interest of the accounting area towards cloud accounting, facilitating the transition of phenomena corresponding to fiscality in cloud mode in view of simplifying the collaboration between entities and state institutions. The research methods used for the purpose of fulfilling the work’s objective are the review of specialty literature, the analysis, synthesis and comparison, techniques assigned to bibliometrics.
A Systemic Review (2014–2023) on the Mobile-Assisted Blended Learning for English as a Foreign Language Education with a Focus on Empirical Studies

Over the past two decades, due to the rapid development of information and communication technologies (ICT), mobile learning (M-learning) and blended learning (BL) have emerged as new trends in sustaining English as a foreign language (EFL) education. The tumultuous COVID-19 pandemic has disrupted traditional teaching and learning, but it has also accelerated the integration of technology in EFL education. Mobile-assisted blended learning (MABL) combines mobile-assisted language learning (MALL) and BL into a single framework that effectively addresses their individual limitations when used in isolation. However, reviews of MABL, particularly in the context of EFL education, are scarce. Sourced from two major databases, namely Web of Science and Scopus, and two supplementary databases (Education Resources Information Center and Mendeley), 25 studies were extracted out of 205 in the latest decade, using specific exclusion and inclusion criteria. This review aims to shed light on the trend of utilizing advanced and effective pedagogy and teaching tools to benefit stakeholders in the sustainable development of English as a foreign language.
Working with Library and Archive Funds, Search and Collection of Scientific Information

The purpose of the article is research and analysis of the effectiveness of interaction with library and archival funds in the context of modern information and communication technologies. Not only the general aspects of using library resources, but also the methods of searching for scientific information are analysed. It is also expected to provide specific and detailed recommendations aimed at improving the quality and efficiency of interactions with scientific foundations. Current opportunities for using library resources are considered, considering modern requirements for information technologies and communication standards. The article sets itself the task of revealing not only general principles but also important details of working with these funds, in particular emphasising optimal strategies for searching for scientific information. The research methodology is based on the analysis of the spectrum of scientific literature, covering theoretical and practical foundations in the field of using library and archival resources. The methods used for finding scientific information are not limited to traditional sources, including various databases and catalogues, as well as innovative information and communication technologies. The scientific novelty of the article lies in the improvement of strategies and approaches to the use of library and archival funds, where the main emphasis is placed on the use of advanced information and communication technologies. The article reveals the potential of these technologies for effective search and use of scientific information, emphasising the importance of introducing innovations into the field of research. Conclusion. The results of the study indicate the need for constant adaptation of methods of working with library and archival funds to the requirements and capabilities of information technologies. The use of various databases and other information resources is key to improving the availability of scientific information and ensuring the efficient work of researchers and students. This approach contributes to the development of the scientific community, and its implementation helps to highlight the importance of innovation in ensuring successful work in the fields of scientific research and higher education.&#x0D; Keywords: library collections, archival collections, scientific information, information and communication technologies, research methods, recommendations.
Challenges Faced by Law Enforcement in the 21st Century, with a Special Focus on Specific Issues of Hybrid Threats – Security "of a Thousand Faces"

In this paper, I explore the challenges facing policing in the 21st century through a multifaceted approach to security. Herein, the idea of security is seen as being filled with the evolutionary determination of humans, which is expressed in the concept of security as it applies to the individual, the need to establish an internal order of social coexistence at the level of human communities, and the relations between certain community formations, i.e. states, as well as international relations. I will show how the creation of security today is becoming an increasingly complex issue, while ancient algorithms and instincts drive the psychological mechanisms that underpin this perception. The real challenge today is how to mitigate the security deficits referred to in this study so that their impacts legitimise everyday relations and satisfy our basic evolutionary needs.