Hasil untuk "Oratory. Elocution, etc."

M. A. Korolev

We give an elementary proof of some identities that express the squares of Riemann zeta function at integer points in terms of the series involving hyperbolic functions, digamma function, Bernoulli numbers etc. In this version, inaccuracies in the text have been corrected and one of the bibliographic references has been updated.

Abir Sen, Tapas Kumar Mishra, Ratnakar Dash

Hand gesture recognition (HGR) is a vital component in enhancing the human-computer interaction experience, particularly in multimedia applications, such as virtual reality, gaming, smart home automation systems, etc. Users can control and navigate through these applications seamlessly by accurately detecting and recognizing gestures. However, in a real-time scenario, the performance of the gesture recognition system is sometimes affected due to the presence of complex background, low-light illumination, occlusion problems, etc. Another issue is building a fast and robust gesture-controlled human-computer interface (HCI) in the real-time scenario. The overall objective of this paper is to develop an efficient hand gesture detection and classification model using a channel-pruned YOLOv5-small model and utilize the model to build a gesture-controlled HCI with a quick response time (in ms) and higher detection speed (in fps). First, the YOLOv5s model is chosen for the gesture detection task. Next, the model is simplified by using a channel-pruned algorithm. After that, the pruned model is further fine-tuned to ensure detection efficiency. We have compared our suggested scheme with other state-of-the-art works, and it is observed that our model has shown superior results in terms of mAP (mean average precision), precision (\%), recall (\%), and F1-score (\%), fast inference time (in ms), and detection speed (in fps). Our proposed method paves the way for deploying a pruned YOLOv5s model for a real-time gesture-command-based HCI to control some applications, such as the VLC media player, Spotify player, etc., using correctly classified gesture commands in real-time scenarios. The average detection speed of our proposed system has reached more than 60 frames per second (fps) in real-time, which meets the perfect requirement in real-time application control.

Shrey Satapara, Parth Mehta, Debasis Ganguly et al.

The recent success in language generation capabilities of large language models (LLMs), such as GPT, Bard, Llama etc., can potentially lead to concerns about their possible misuse in inducing mass agitation and communal hatred via generating fake news and spreading misinformation. Traditional means of developing a misinformation ground-truth dataset does not scale well because of the extensive manual effort required to annotate the data. In this paper, we propose an LLM-based approach of creating silver-standard ground-truth datasets for identifying misinformation. Specifically speaking, given a trusted news article, our proposed approach involves prompting LLMs to automatically generate a summarised version of the original article. The prompts in our proposed approach act as a controlling mechanism to generate specific types of factual incorrectness in the generated summaries, e.g., incorrect quantities, false attributions etc. To investigate the usefulness of this dataset, we conduct a set of experiments where we train a range of supervised models for the task of misinformation detection.

Hitesh Gudwani

We consider a system of multiple sources, a single communication channel, and a single monitoring station. Each source measures a time-varying quantity with varying levels of accuracy and one of them sends its update to the monitoring station via the channel. The probability of success of each attempted communication is a function of the source scheduled for transmitting its update. Both the probability of correct measurement and the probability of successful transmission of all the sources are unknown to the scheduler. The metric of interest is the reward received by the system which depends on the accuracy of the last update received by the destination and the Age-of-Information (AoI) of the system. We model our scheduling problem as a variant of the multi-arm bandit problem with sources as different arms. We compare the performance of all $4$ standard bandit policies, namely, ETC, $ε$-greedy, UCB, and TS suitably adjusted to our system model via simulations. In addition, we provide analytical guarantees of $2$ of these policies, ETC, and $ε$-greedy. Finally, we characterize the lower bound on the cumulative regret achievable by any policy.

Argha Sen, Anirban Das, Swadhin Pradhan et al.

Continuous detection of human activities and presence is essential for developing a pervasive interactive smart space. Existing literature lacks robust wireless sensing mechanisms capable of continuously monitoring multiple users' activities without prior knowledge of the environment. Developing such a mechanism requires simultaneous localization and tracking of multiple subjects. In addition, it requires identifying their activities at various scales, some being macro-scale activities like walking, squats, etc., while others are micro-scale activities like typing or sitting, etc. In this paper, we develop a holistic system called MARS using a single Commercial off the-shelf (COTS) Millimeter Wave (mmWave) radar, which employs an intelligent model to sense both macro and micro activities. In addition, it uses a dynamic spatial time sharing approach to sense different subjects simultaneously. A thorough evaluation of MARS shows that it can infer activities continuously with a weighted F1-Score of > 94% and an average response time of approx 2 sec, with 5 subjects and 19 different activities.

Beatrice Latini

Se il Web dei primordi aveva permesso agli autori letterari di assumere liberamente forme diverse (anonima, collettiva, pseudonima), oggi l’avvento dei social network e del web 2.0 impone la costruzione di una postura letteraria virtuale il più aderente possibile a quella reale. In questo articolo ci si propone di analizzare, a partire da Instagram, la postura letteraria di Édouard Louis e Jonathan Bazzi, le cui opere sono estremamente simili nei temi e nella forma. L’analisi cercherà di comprendere come i social intervengano nel processo di costruzione della postura letteraria e se, a partire da essi, vi sia la possibilità di una sua ricomprensione.

Andrea Palermitano

Recensione di Cecilia Schwartz, La letteratura italiana in Svezia. Autori, editori, lettori (1870-2020) (Carocci, 2021)

Amar Kumar Banerjee, Sukila Khatun

In this paper we have studied the notion of rough convergence of sequences in a partial metric space. We have also investigated how far several relevant results on boundedness, rough limit sets etc. which are valid in a metric space are affected in a partial metric space.

Thong Nguyen, Cong-Duy Nguyen, Xiaobao Wu et al.

With the burgeoning amount of data of image-text pairs and diversity of Vision-and-Language (V\&L) tasks, scholars have introduced an abundance of deep learning models in this research domain. Furthermore, in recent years, transfer learning has also shown tremendous success in Computer Vision for tasks such as Image Classification, Object Detection, etc., and in Natural Language Processing for Question Answering, Machine Translation, etc. Inheriting the spirit of Transfer Learning, research works in V\&L have devised multiple pretraining techniques on large-scale datasets in order to enhance the performance of downstream tasks. The aim of this article is to provide a comprehensive revision of contemporary V\&L pretraining models. In particular, we categorize and delineate pretraining approaches, along with the summary of state-of-the-art vision-and-language pretrained models. Moreover, a list of training datasets and downstream tasks is supplied to further polish the perspective into V\&L pretraining. Lastly, we decided to take a further step to discuss numerous directions for future research.

Nicola Picchiotti, Marco Gori

In recent years, Artificial Intelligence (AI) algorithms have been proven to outperform traditional statistical methods in terms of predictivity, especially when a large amount of data was available. Nevertheless, the "black box" nature of AI models is often a limit for a reliable application in high-stakes fields like diagnostic techniques, autonomous guide, etc. Recent works have shown that an adequate level of interpretability could enforce the more general concept of model trustworthiness. The basic idea of this paper is to exploit the human prior knowledge of the features' importance for a specific task, in order to coherently aid the phase of the model's fitting. This sort of "weighted" AI is obtained by extending the empirical loss with a regularization term encouraging the importance of the features to follow predetermined constraints. This procedure relies on local methods for the feature importance computation, e.g. LRP, LIME, etc. that are the link between the model weights to be optimized and the user-defined constraints on feature importance. In the fairness area, promising experimental results have been obtained for the Adult dataset. Many other possible applications of this model agnostic theoretical framework are described.

Nicole Yunger Halpern, Shayan Majidy

Noncommuting conserved quantities have recently launched a subfield of quantum thermodynamics. In conventional thermodynamics, a system of interest and an environment exchange quantities -- energy, particles, electric charge, etc. -- that are globally conserved and are represented by Hermitian operators. These operators were implicitly assumed to commute with each other, until a few years ago. Freeing the operators to fail to commute has enabled many theoretical discoveries -- about reference frames, entropy production, resource-theory models, etc. Little work has bridged these results from abstract theory to experimental reality. This paper provides a methodology for building this bridge systematically: We present a prescription for constructing Hamiltonians that conserve noncommuting quantities globally while transporting the quantities locally. The Hamiltonians can couple arbitrarily many subsystems together and can be integrable or nonintegrable. Our Hamiltonians may be realized physically with superconducting qudits, with ultracold atoms, and with trapped ions.

Houxiang Fan, Binghui Wang, Pan Zhou et al.

Link prediction in dynamic graphs (LPDG) is an important research problem that has diverse applications such as online recommendations, studies on disease contagion, organizational studies, etc. Various LPDG methods based on graph embedding and graph neural networks have been recently proposed and achieved state-of-the-art performance. In this paper, we study the vulnerability of LPDG methods and propose the first practical black-box evasion attack. Specifically, given a trained LPDG model, our attack aims to perturb the graph structure, without knowing to model parameters, model architecture, etc., such that the LPDG model makes as many wrong predicted links as possible. We design our attack based on a stochastic policy-based RL algorithm. Moreover, we evaluate our attack on three real-world graph datasets from different application domains. Experimental results show that our attack is both effective and efficient.

Anastasiya Gorodilova, Natalia Tokareva, Sergey Agievich et al.

NSUCRYPTO is the unique cryptographic Olympiad containing scientific mathematical problems for professionals, school and university students from any country. Its aim is to involve young researchers in solving curious and tough scientific problems of modern cryptography. From the very beginning, the concept of the Olympiad was not to focus on solving olympic tasks but on including unsolved research problems at the intersection of mathematics and cryptography. The Olympiad history starts in 2014. In 2019, it was held for the sixth time. In this paper, problems and their solutions of the Sixth International Olympiad in cryptography NSUCRYPTO'2019 are presented. We consider problems related to attacks on ciphers and hash functions, protocols, Boolean functions, Dickson polynomials, prime numbers, rotor machines, etc. We discuss several open problems on mathematical countermeasures to side-channel attacks, APN involutions, S-boxes, etc. The problem of finding a collision for the hash function Curl27 was partially solved during the Olympiad.

Livio Lepratto

Recensione a Bertoni, Clotilde, e Chiara Lombardi (a cura di). Alberto Moravia. L’attenzione inesauribile. Mimesis, 2018.

Stefano Garzonio

Nel presente saggio l'autore propone un'analisi tematica e di genere del recentissimo romanzo dello scrittore russo Oleg Zobern, Autobiografia di Gesù Cristo, alla luce delle tendenze più recenti della letteratura russa contemporanea e dell'atteggiamento verso di essa del lettore di oggi.

Enzhi Li, Zhengyi Le

Researchers have designed many algorithms to measure the distances between graph nodes, such as average hitting times of random walks, cosine distances from DeepWalk, personalized PageRank, etc. Successful although these algorithms are, still they are either underperforming or too time-consuming to be applicable to huge graphs that we encounter daily in this big data era. To address these issues, here we propose a faster algorithm based on an improved version of random walks that can beat DeepWalk results with more than ten times acceleration. The reason for this significant acceleration is that we can derive an analytical formula to calculate the expected hitting times of this random walk quickly. There is only one parameter (the power expansion order) in our algorithm, and the results are robust with respect to its changes. Therefore, we can directly find the optimal solution without fine-tuning of model parameters. Our method can be widely used for fraud detection, targeted ads, recommendation systems, topic-sensitive search, etc.

Stefania Sini

Editoriale per la celebrazione del decimo anniversario della rivista Enthymema.

Galip Aydin, Ibrahim Riza Hallac

In this paper we describe our work on designing a web based, distributed data analysis system based on the popular MapReduce framework deployed on a small cloud; developed specifically for analyzing web server logs. The log analysis system consists of several cluster nodes, it splits the large log files on a distributed file system and quickly processes them using MapReduce programming model. The cluster is created using an open source cloud infrastructure, which allows us to easily expand the computational power by adding new nodes. This gives us the ability to automatically resize the cluster according to the data analysis requirements. We implemented MapReduce programs for basic log analysis needs like frequency analysis, error detection, busy hour detection etc. as well as more complex analyses which require running several jobs. The system can automatically identify and analyze several web server log types such as Apache, IIS, Squid etc. We use open source projects for creating the cloud infrastructure and running MapReduce jobs.

Ganji Sreeram, Kunal Dhawan, Rohit Sinha

Code-switching refers to the usage of two languages within a sentence or discourse. It is a global phenomenon among multilingual communities and has emerged as an independent area of research. With the increasing demand for the code-switching automatic speech recognition (ASR) systems, the development of a code-switching speech corpus has become highly desirable. However, for training such systems, very limited code-switched resources are available as yet. In this work, we present our first efforts in building a code-switching ASR system in the Indian context. For that purpose, we have created a Hindi-English code-switching speech database. The database not only contains the speech utterances with code-switching properties but also covers the session and the speaker variations like pronunciation, accent, age, gender, etc. This database can be applied in several speech signal processing applications, such as code-switching ASR, language identification, language modeling, speech synthesis etc. This paper mainly presents an analysis of the statistics of the collected code-switching speech corpus. Later, the performance results for the ASR task have been reported for the created database.

Giovanni Bottiroli

Che cosa significa leggere un classico? Quest’articolo distingue due modi, o due vie. Per i contestualisti è sufficiente collocare l’opera nella sua epoca storica, e sottolineare eventualmente la novità che quell’opera ha introdotto. Per la teoria dell’interpretazione, un classico vive nel «tempo grande» (Bachtin), cioè oltrepassa i confini della sua epoca. In questo senso, i grandi scrittori sarebbero ‘universali’. Per l’autore di quest’articolo sarebbe più corretto riconoscere la densità semantica dell’opera d’arte, cioè l’insieme delle sue virtualità. Ma per riconoscere e indagare le virtualità di un classico occorre far riferimento alla teoria, o meglio alle teorie. Nel caso di Le Rouge et le Noir, ci si può limitare ad analisi parziali, che, nella loro consapevole limitatezza, sono legittime. Tut-tavia, chiunque pretenda di offrire un punto di vista complessivo su questo romanzo di Stendhal non può (o meglio non dovrebbe) ignorare, per esempio, le teorie del desi-derio. Le Rouge et le Noir rappresenta un momento fondamentale per la nascita del realismo moderno («serio», come lo ha chiamato Auerbach): ma si può ridurre la rappresentazione della realtà, che esso offre, quasi unicamente al contesto storico-sociale? La verità (l’âpre vérité) che Stendhal promette ai suoi lettori nell’esergo del romanzo è la verità di quegli esseri flessibili che noi siamo: è la verità delle diverse possibilità, o versioni, dell’amore. Non si può leggere un classico senza incontrare il desiderio di essere. What does ‘reading the classics’ mean? This paper identifies a twofold approach to this act. Contextualist critics believe that setting the text within its historical context and shedding light on its innovative aspects suffice to understand it. According to the theory of interpretation, classics embody Bachtin’s «great time», exceeding the limits of their epoch. Great writers would be therefore universal figure. For the author of this paper, a correct approach to literary works acknowledges the density of texts, that is to say the combination of virtual components. In order to investigate classics’ ‘virtuality’, one has to refer to theory, or rather theories. Dealing with Le Rouge et le Noir, critics can provide partial analyses that, in being consciously limited, are certainly legit. However, whoever might want to offer a complete view of Pascal’s novel cannot – or rather should not – ignore, for instance, theories of desire. Le Rouge et le Noir stands out as a fundamental step towards the birth of modern realism («serious», as Auerbach named it). Nonetheless, is it possible to reduce the portrayal of reality it offers to, almost exclusively, its socio-historical context? The truth (l’âpre vérité) Stendhal promises to his readers in the novel’s exergue is the truth about us as flexible beings. In other words, it is the truth about the several possibilities, or potentialities, intrinsic to love. One cannot read classics without discovering the desire to be.