Reviewerly/exHarmony huggingface dataset:
Improving Streaming End-to-End ASR on Transformer-based Causal Models with Encoder States Revision Strategies

There is often a trade-off between performance and latency in streaming automatic speech recognition (ASR). Traditional methods such as look-ahead and chunk-based methods, usually require information from future frames to advance recognition accuracy, which incurs inevitable latency even if the computation is fast enough. A causal model that computes without any future frames can avoid this latency, but its performance is significantly worse than traditional methods. In this paper, we propose corresponding revision strategies to improve the causal model. Firstly, we introduce a real-time encoder states revision strategy to modify previous states. Encoder forward computation starts once the data is received and revises the previous encoder states after several frames, which is no need to wait for any right context. Furthermore, a CTC spike position alignment decoding algorithm is designed to reduce time costs brought by the revision strategy. Experiments are all conducted on Librispeech datasets. Fine-tuning on the CTC-based wav2vec2.0 model, our best method can achieve 3.7/9.2 WERs on test-clean/other sets, which is also competitive with the chunk-based methods and the knowledge distillation methods.
Study of Recommendation System

Recommendation system (RS) has surfaced as a serious exploration interest that aims to help druggies to seek out particulars online by furnishing suggestions that nearly match their interest. This paper provides a study on the RS covering the colorful recommendation approaches, associated issues, and Ways used for information reclamation. because of its wide operations, it's convinced exploration interest among a big number of experimenters round the globe. the most purpose of this paper is to identify the exploration trend in RS. relatively, 000 exploration papers, published by ACM, IEEE, Sp ringer, and Elsevier since 2011 to the primary quarter of 2017, have been considered. Several intriguing findings have embark of this study, which will help this and unborn RS experimenters to assess and set their exploration road map. likewise, this paper also envisions the long run of RS which can open up new exploration directions during this sphere.
Privacy-Preserving Media Sharing with Scalable Access Control and Secure Deduplication in Cloud

In this study, role re-encryption is employed in a secure role re-encryption system to minimise data leakage and deduplication (SRRS). It also looks for evidence of ownership to see whether the user is an authorised one. This is for the sake of effectiveness. The role re encryption approach involves sharing the access key for the associated authorised user in order to access a specific file without exposing personal information. We use both the avoid use of text and digital visuals in our endeavour. Personal photographs, for example, are stored on our mobile phones, portable devices, computers, and other gadgets. As these photographs must be kept confidential, we are encrypting them. Nowadays, the text file is equally significant for users. It must be kept safe on a cloud server. Digital photographs must be safeguarded during transmission, but personal identity information such as copies of a pancard, passport, ATM card, and so on, should be stored on a single wnpc. To minimise duplication in our proposed system, we are securing the text file and picture data.
ALGORITHMS OF IMPROVING OF THE PROCESS OF PROFESSIONAL POTENTIAL REALIZATION BY UNIVERSITY PROFESSOR AS A BEARER OF BRAND

The article considers the professional potential of a university professor, which provides not only the formation of a personal brand but also its successful promotion in the market of educational and scientific services. Therefore, the professional potential is a fundamental component of the structure of a university professor’s personal brand. The algorithmic interconnection of the concepts of “personal potential”, “personal resources” and “human capital” is clarified. It is emphasized that the professor’s awareness of the professional potential necessary and sufficient to form a personal brand is determined primarily by the motivation of the specialist to identify their own intellectual, leadership, creative, communicative and other resources and reserves. The author specifies that in the structure of the university professor’s professional potential, the priority is constructs that are both in demand by the profession and relevant to the requests of the target audience. The real and potential determinants of slowing down the process of realization of the university professor’s professional potential are listed. It is proved that the intensification of readiness for effective realization of professional potential by university professor requires obligatory consideration of contextual and situational peculiarities of personal brand positioning and synergistic possibilities of co-branding with other university specialists as brand carriers or even university brand. Methods of counteracting the real and potential determinants of slowing down the process of university professor’s professional potential realization are highlighted. They are: the inability of a specialist to objectively assess the scope and probable prospects for the realization of their own potential; barriers in brand communication; the impact of previous failure stressors; the dominance of fear of image and/or reputational losses over the subjectively predicted attractiveness of the consequences of the professional potential realization; achieving a local maximum in professional self-realization, etc.&#x0D; Keywords: personal brand; branding; co-branding; university professor; professional potential; personal resources; algorithm; higher education institution.
Analysis Based on Social Media using Multi Modal Algorithm

Propose system tend to concentrate on analysis sentiment of text from social media, aim of system is to find whether piece of text is positive or negative. The goal of Sentiment Analysis is to harness this data in order to obtain important information regarding public opinion that would help make smarter business decisions, political campaigns and better product consumption. Sentiment Analysis focuses on identifying whether a given piece of text is subjective or objective and if it is subjective, then whether it is negative or positive. Sentiment analysis deals with the computational treatment of opinion, sentiment, and subjectivity of texts. Moreover, we tend to conjointly develop economical illation methodology for parameter estimation of sup- ported folded Gibbs sampling. We tend to judge SJASM extensively on real-world review knowledge, and experimental results demonstrate that the planned model outperforms seven well-established base- line strategies for sentiment analysis tasks.
ARRANGEMENT OF INCLUSIVE STUDYING IN THE MANAGEMENT SYSTEM OF THE EDUCATIONAL INSITUTIONS

Nowadays the training of future teachers working in the conditions of inclusive education belongs to the important components of the educational process at universities. However, a great number of teachers graduated from universities when the issue of inclusive studying was not paid proper attention, teachers’ training was aimed at the formation of professional competence to teach and educate children with common development. Along with the changes connected with an outside technological support of the architectural availability and the creation of appropriate infrastructure, the arrangement of a working process sets a goal to develop a high level of an inclusive culture in a teachers’ and students’ staff. In this regard, a manager of a contemporary institution faces the task to direct the managerial activity toward the efficient meeting of the requirements of inclusive studying.The purpose of the research is to suggest a management model for inclusive studying at educational institutions.The introduction of the inclusive studying implies a modification of a managerial system and a change of the configuration in the directions of a school’s working process which will provide the formation of a high-level inclusive culture in teachers’ and students’ staff.The creation of consultation centers in the general secondary institutions focused on several directions is suggested in this paper.An appropriate sector will be responsible for the working process of each direction. It is suggested to single out the following sectors based on a consultative center: the sector which is responsible for studying the inclusive learning practices; the sector of psychological assistance for inclusive studying; the sector of methodological support in organizing inclusive studying.To a certain extent, the division into sectors and directions is conditional; their configuration has a flexible nature and can be modified, and restructured due to the requirements which are relevant for each institution taken separately.&#x0D; Keywords: educational institution management; innovations; inclusion; inclusive studying; inclusive culture; specific educational needs; management model for inclusive studying.
FOREIGN LANGUAGE TEACHERS’ PREPARATION TO WORK WITH SEN CHILDREN IN NEW JERSEY

The article analyzes two university training programs for future teachers in New Jersey in accordance with the conditions of obtaining a diploma from the State Department of Education. As a result of the study, it was founded that the respondents’ understanding of the essence of working with students with special needs changed during the experiment. The university teacher’s training program General Program 101 (Gen Ed 101) does not provide adequate training, in contrast to the double degree program, which provides in-depth training, culminating in the defense of the diploma and teaching practice at school. Students in the double degree program had the opportunity to gain knowledge from two programs, compare them, and modify them to the specific cases they encounter during the internship under the guidance of teacher mentors. According to New Jersey Professional Standards for Teachers and School Leaders (2004), they felt ready to work with children with special educational needs only after employment and in the process of working together with teachers-mentors. And those students who did not have SEN students in their classes did not receive practical skills for such work at all. Thus, mentoring is a powerful tool to help future teachers develop skills in inclusive classrooms, only a double degree program can prepare future foreign language teachers to work adequately with children with special needs, only personal experience and understanding between a foreign language teacher and a special teacher can become a guarantee of the most comfortable and fruitful atmosphere for children with special educational needs in the classroom.&#x0D; Keywords: special educational needs; inclusive environment; inclusion; SEN student; inclusive education; foreign language teachers; state standards; general training program.
Empowering the Design of Reversible and Quantum Logic with Decision Diagrams

Reversible computation has received significant attention in recent years as an alternative computation paradigm which can be beneficial e.g. for encoder circuits, low power design, adiabatic circuits, verification—just to name a few examples. Aside from those applications in the design of (conventional) integrated circuits, reversible logic components are also a key ingredient in many quantum algorithms, i.e. in the field of quantum computing which by itself emerged as a very promising computing paradigm that, particularly these days, gains more and more relevance. All that led to a steadily increasing demand for methods that allow for an efficient and correct design of corresponding circuits. Decision diagrams play an important role in the design of conventional circuitry. In the recent years, also their benefits for the design of the newly emerging reversible and quantum logic circuits become evident. In this overview paper, we review and illustrate previous and ongoing work on decision diagrams for such circuits and sketch corresponding design methods relying on them. By this, we demonstrate how broadly decision diagrams can be employed in this area and how they empower the design flow for these emerging technologies.
An object tracking algorithm with adaptive template updating for visual tracking measurement system

This paper proposes a novel adaptive template updating method with continuous variational spatial-temporal characteristics, which is utilized as a part of visual object tracking in the measurement process of the vision measurement system. The measurement system is set up by cameras and turntables to catch the profile of a moving object in largescale space. Among all steps, the proposed method is applied to positioning the object. In order to enhance the spatial constraints of the tracking algorithm to make the measurement results more reliable, the Average Peak-to-Correlation Energy (APCE) whose property includes spatial information is used as a part of the learning rate in the template updating step. Experiments show that the results calculated by the proposed method have a smoother profile. With the comparison of the fixed distances measured by Leica T-Mac, the proposed method applied in the system performed higher accuracy.
Introduction

The motivation behind writing this book was the observed lack of theoretical cybersecurity in the field and the resulting gap in innovation, security, and cost-benefit. I have had the privilege several times in my maturing career within cybersecurity to be afforded the opportunity to serve in job functions where my role was largely to assess, evaluate, and postulate improvements to cybersecurity frameworks that mitigate risk for large organizations. This included both commercial Fortune 500 companies as well as government organizations with global enterprise and loss-of-life and critical mission systems.
Explaining and verifying the robustness of Visual Object Trackers to noise

2D tracking is an important computer vision task with important applications in autonomous embedded systems such as Unmanned Aerial Vehicles and autonomous cars that particularly attracted scientists in the past few years. Many new methods have aroused that significantly pushed the state-of-the-art performance in terms of tracking precision, success rate and execution speed, in well-designed and established existing publicly available benchmarks. Despite the fact that these benchmark datasets include as many application scenarios as possible, another commonly neglected yet important aspect is the robustness of tracking methods, notably to noise related with image acquisition, capturing storing and transmission. This paper presents a robustness evaluation toolkit for 2D Visual Object Tracking, that can exploit existing datasets in order to evaluate the robustness of 2D visual tracking methods to realistic image distortion scenarios, mostly encountered in embedded systems. The source code of this toolkit will be made publicly available upon paper acceptance.
The role of empathy in the formation of an anti-corruption standard of behavior of employees of the penitentiary system: the main contradictions

The main attention in the presented work is paid to the problem of identifying the causes of corrupt behavior and anti-corruption measures. The authors have identified groups of causes of corrupt behavior. Special attention is paid to the role of empathy in involvement in corruption crimes. Based on the theoretical analysis carried out, the authors note the insufficiency of studying the psychological, in particular the emotional, component of the formation of corrupt behavior. On the example of the specific professional activity of prison system employees interacting with persons convicted of various crimes, the presence of a contradiction is demonstrated, consisting, on the one hand, in the need for a correctional officer to have the ability to sympathize and empathize with convicts, and on the other — to counteract manipulative influences focused on the emotional sphere of the individual. The necessity of taking into account the role of empathy in the formation of an anti-corruption standard of behavior of employees of the penitentiary system is substantiated.
Home / Archives / Vol. 10 No. 4 (2022): European Journal of Applied Sciences / Articles Using Predictive Bayesian Methods to Measure the Probability of Finding Earth- Sized BodiesOne of the ongoing investigations involving NASA and other international agencies is an effort to find earth-like objects in space as they may be candidates for lif

One of the ongoing investigations involving NASA and other international agencies is an effort to find earth-like objects in space as they may be candidates for life.&nbsp; At present, these investigations are being undertaken via telescopic means by looking at changes in light intensity caused by transiting planets.&nbsp; As a result, the data available to make estimates of the number of these relatively bodies is currently limited.&nbsp; One means to find a solution to this challenge is to use the number of objects in our solar system, along with predictive Bayesian methods, to develop a probability distribution for the likelihood of finding “earths” in other solar systems in the galaxy.&nbsp; Predictive Bayesian statistical methods are designed to use limited, uncertain data to develop results.&nbsp; Such an analysis is similar to predicting incident size and probability for such unlikely events as hurricanes, oil spills, health risks from contaminants and train accidents.&nbsp; The result provided a probability curve distribution of the size of planets in the solar system which when integrated to include bodies that are deemed of the size to sustain life, yielded the ratio of earth sized objects per star of just over 3, and the number of Earth-sized objects in the galaxy as most likely 7 x 1011.&nbsp; Finding these planets is a bigger challenge.
Identifying Pitfalls in the Evaluation of Saliency Models for Videos

Saliency prediction has been extensively studied for natural images. In the area of video coding and video quality assessment, researchers attempt to integrate a saliency model to individual frames of a video sequence. In selecting best-performing saliency models for these applications, the evaluation only considers the average model performance over all frames of a video. This may mask the defects of a saliency model and consequently hinder further improvement of the model. In this paper, we present the identification of pitfalls in the evaluation of saliency models for videos. We demonstrate the importance of considering the video content classification and temporal effect. Building on the findings, we make recommendations for saliency model evaluation and selection for videos.
A Codec-Unified Deblurring Approach Based on U-Shaped Invertible Network with Sparse Salient Representation in Latent Space

Existing deep learning architectures usually use a separate encoder and decoder to generate the desired simulated images, which is inefficient for feature analysis and synthesis. Aiming at the problem that the existing methods fail to fully utilize the correlation of codecs, this paper focuses on the codec-unified invertible networks to accurately guide the image deblurring process by controlling latent variables. Inspired by U-Net, a U-shaped multi-level invertible network (UML-IN) is proposed by integrating the wavelet invertible networks into a supervised U-shape architecture to establish the multi-resolution correlation between blurry and sharp image features under the guidance of hybrid loss. Further, this paper proposes to use L1 regularization constraints to obtain sparse latent variables, thereby alleviating the information dispersion problem caused by high-dimensional inference in invertible networks. Finally, we fine-tune the weights of invertible modules by calculating a similarity loss between blur-sharp variable pairs. Extensive experiments on real and synthetic blurry sets show that the proposed approach is efficient and competitive compared with the state-of-the-art methods.
Game Theory Case Study: Ransomware

Game theory is an excellent tool for analyzing complex, competitive situations. Cybersecurity is concerned with just such situations involving attackers, defenders, and others like regulating entities. Within game theory, “a particular game is defined when the choices open to the players in each situation, the situations defining the end of play, and the payoffs associated with each play-terminating situation have been specified.” This does not apply to a general cybersecurity situation. We use the term “infinite game” to describe something like a game such that: players may start or stop playing the game at any time; the end of play may never be defined; and the rules governing play may change at any time without all (or any) players knowing about the changes. While infinite games do not meet the strict definition of a game, both games and infinite games can be analyzed with the rigor and tools of game theory.
Abstract Data Types: OOP Without Classes in Go

In the previous chapter, we discussed algorithm complexity and presented examples with and without the use of concurrency.
The Correlation between Students’ Writing Skills and Speaking Skills

Some English learners might be very good at speaking English but not optimal in writing English, and vice versa. However, there were also some English learners who have almost the same score between writing and speaking skills. As fellow productive language skills, researching the relationship between writing skills and speaking skills will be very interesting. Based on the phenomena that exist in the field when reviewing the results of foreign language skills, especially English, the researchers tried to map the relationship between writing skills and speaking skills in English owned by learners, especially English learners in universities. It became very interesting to reveal the relationship between two different English skills through research with a correlation research design. This research was conducted with the aim of knowing the correlation between English writing skills and English speaking skills possessed by students. The design of this research is correlation research. The subjects of this study were 49 fifth semester students of the English Education Study Program, Nurul Jadid University, Probolinggo, in the 2021-2022 academic year. In the fifth semester the students took advanced writing courses and advanced speaking courses. From the results of the calculation of correlation analysis could be revealed that the correlation coefficient (rxy) is 0.0776. With an alpha value between 0.05 and 0.95, the t-table value is 1.6779, and the t-count value was 0.5338. From the results of this study, it could be stated that English writing skills and English speaking skills possessed by students had a very weak positive correlation. In other words, it could be stated that the higher the value of writing skills, the higher the value of students' English speaking skills with a very weak correlation.