Reviewerly/exHarmony huggingface dataset:
A Novel ICIC Scheme Combining 3D ML-SFR and CoMP

With the development of the fifth generation (5G) wireless networks, the dense, heterogeneous and irregular network architecture puts forward higher requirements for inter-cell interference coordination (ICIC) technology.How to combine the existing technology to suppress inter-cell interference has become a focus worthy of research.This paper proposes a novel ICIC scheme that combines three-dimensional (3D) multi-level soft frequency reuse (ML-SFR) and coordinated multi-point (CoMP) transmission technology.Based on the scheme, a model of ML-SFR and CoMP is built for different scenarios.Finally, the information rates of users at the cell edge and the entire cell are analyzed through simulation, respectively.The results show that the proposed scheme is superior to the traditional anti-interference technology in suppressing inter-cell interference.The proposed scheme can effectively improve the transmission performance of the 5G wireless networks.
Finding Meaning in Sound: Auditory Perception and Adaptation (Interview with Dr. Frederic Theunissen))

Berkeley and is the principal investigator of the Theunissen Lab.His work strives to understand how the brain recognizes and perceives natural sounds, such as human speech and animal vocalizations.In his research, he uses computational approaches as well as behavioral experiments to explain auditory phenomena and understand the neural representations of natural sounds.In this interview, we discuss his findings on auditory perception and adaptation in zebra finches and humans.
Research on the Realistic Manifestation of Cyber Terrorismand Its Governance Path

At present, the field of network information has become a new battlefield of global anti-terrorism. Cyber terrorism has the characteristics of low cost, covert behavior and wide radiation of criminal consequences, which makes the antiterrorism work more difficult. Counter-terrorism work is faced with pain points such as lack of implementation of overall national security concept, anomie of legal system regulation, poor information sharing mechanism, disorder of international cooperation against terrorism and so on. Functional departments should practice the overall national security concept, improve the anti-terrorism system, promote anti-terrorism intelligence sharing, strengthen international anti-terrorism cooperation, and take multiple measures to eradicate the network soil where terrorism breeds, so as to achieve effective governance of network anti-terrorism.
A Study on the Newly Introduced Provisions of Act On The Protection Of Children And Youth Against Sex Offenses

The Act on the Protection of Children and Juveniles against Sexual Offenses(which was promulgated on March 23, 2021) established a new provision to punish Cybergrooming(Article 15-2), and ‘Identity Concealment Investigation’ and ‘Undercover Investigation’ systems to eradicate Digital Sex Crimes against children and juveniles (Article 25-2 to 25-9). These provisions took effect on Sept. 24, 2021.<BR> The provisions on the Identity Concealment Investigation and Undercover Investigation can be evaluated positively in that the requirements and procedures for legality and effectiveness of the investigation are clearly stipulated in the act. However, these provisions couldn’t be used in abuse of investigative authority and infringe on the rights of citizens.<BR> Even if the investigation is initiated with the permission of the court, the risk of disguising identity can be transformed into an ‘illegal entrapment investigation’ depending on the nature of the crime and the circumstances of the investigation.<BR> In this regard, it is thought that it is necessary to make an effort to make a lawful investigation by specifying the enforcement ordinances and guidelines to prepare specific standards and permissible requirements, and by analyzing the investigation process and results.<BR> In addition, it is thought that further consideration will be given to the legality of the evidence collected through identity disguise investigations, etc.
Reliable Visualization for Deep Speaker Recognition

In spite of the impressive success of convolutional neural networks (CNNs) in speaker recognition, our understanding to CNNs' internal functions is still limited. A major obstacle is that some popular visualization tools are difficult to apply, for example those producing saliency maps. The reason is that speaker information does not show clear spatial patterns in the temporal-frequency space, which makes it hard to interpret the visualization results, and hence hard to confirm the reliability of a visualization tool. In this paper, we conduct an extensive analysis on three popular visualization methods based on CAM: Grad-CAM, Score-CAM and Layer-CAM, to investigate their reliability for speaker recognition tasks. Experiments conducted on a state-of-the-art ResNet34SE model show that the Layer-CAM algorithm can produce reliable visualization, and thus can be used as a promising tool to explain CNN-based speaker models. The source code and examples are available in our project page: http://project.cslt.org/.
Sequence-to-Sequence-Modelle

No AccessDeep Natural Language ProcessingApr 2022Sequence-to-Sequence-ModelleJochen HirschleJochen HirschleSearch for more papers by this authorhttps://doi.org/10.3139/9783446473904.010SectionsAboutPDF ToolsAdd to FavoritesDownload CitationTrack CitationsCopy LTI LinkPDF key 'share (en)' returned an object instead of string.FacebookTwitterEmailLinkedIn previous chapternext chapter FiguresReferencesRelatedDetails 2022Pages: 175-205Print ISBN: 978-3-446-47363-8eISBN: 978-3-446-47390-4 Copyright & Permissions© 2022 Carl Hanser Verlag GmbH & Co. KGPDF downloadLoading ...
Anomaly detection algorithm based on deep autoencoder ensembles

Autoencoder and deep autoencoder have been widely used for dimensionality reduction and anomaly detection. The ensemble learning method based on autoencoders further improves the accuracy of anomaly detection. However, neural networks are easy to overfit, and the current ensemble methods based on autoencoders cannot effectively make autoencoders diversified to avoid overfitting problems. For this reason, this paper proposes an ensemble method of autoencoders. The algorithm builds a cascaded model of deep autoencoders, and resample the training set of the next neural network by the anomaly detection results of the previous neural network, thereby improving the accuracy of the overall model. Experimental results show that the accuracy of the model is significantly improved compared to the current mainstream anomaly detection algorithms.
FORMATION OF PEDAGOGICAL CULTURE OF AN ENGLISH TEACHER IN PANDEMIC TIME

The topic of the pedagogical culture is multifaceted. This is a model of a teacher that requires full personal maturity and spiritual and moral competence of the teacher, showing speech skills and relationships with the child, as well as creative approach to solving pedagogical problems and high results in the field of education and upbringing. This study examines how to solve the problem of forming the pedagogical culture of teachers in the context of a pandemic. The distance learning process has made some changes in the education system. Teaching in a new format required patience and perseverance from teachers. While the formation and development of pedagogical culture is optimal among students and colleagues at school, during the pandemic the teacher is isolated and faced with a new system.And also, topical issues are considred, starting with the methods of conducting teachers` lessons in an online format and ending with the principle of building relationships with students. In supporting students and parents, special attention was paid to making the learning process easier, more accessible and more effective. During the pandemic, seminars and training were held for teachers through various platforms. As well as meeting where the structure and effectiveness of suitable platforms for distance learning were discussed. The main topic of educational organization was the problem of optimizing the education of students, the internal training of teachers and the ethics of communication. A survey of English language teachers were conducted, and the results were discussed.
Hubungan Tingkat Pendidikan Orang Tua dan Motivasi Belajar Siswa terhadap Hasil Belajar Kognitif Siswa Kelas V di MI Zumrotul Wildan Jepara

This study discusses the relationship between parents' education level and students' learning motivation on mathematics learning outcomes for the fifth grade students of MI Zumrotul Wildan. This study was conducted with the aim of knowing the relationship between parents' education level and students' learning motivation together with the mathematics learning outcomes of class V MI Zumrotul Wildan students. This study uses quantitative research methods to obtain the significance of the relationship between parental education level and student learning motivation on cognitive learning outcomes in mathematics, while the approach used in this study is correlation. The subjects of this study were 22 students of class V MI Zumrotul Wildan Jepara taken from a representative population. The data analysis technique used is statistical analysis with multiple correlation techniques. The results of this study indicate that 1) there is a positive and significant relationship between Parental Education Levels with Cognitive Learning Outcomes for Class V Mathematics Subjects at MI Zumrotul Wildan 2) there is a positive and significant relationship between Student Learning Motivation and Cognitive Learning Outcomes for Grade Mathematics Subjects. V MI Zumrotul Wildan 3) There is a positive and significant relationship between the education level of parents and students' learning motivation together there are cognitive learning outcomes of students in mathematics, it is shown from the test results through the F test that the F arithmetic value &gt; F table is 5,495 &gt; 3.52 and sig. 0.013 the value is smaller than 0.05. So Ha is accepted and Ho is rejected.
Peningkatan Kemampuan Membaca Intensif Bagi Siswa SMAN 2 Rumbio Jaya

The Science and Technology Program for the Community (IbM) that the team carried out was Improving the Intensive Reading Ability for Students of SMA N 2 Rumbio Jaya. The target to be achieved is to increase the intensive reading ability of the students of SMA N 2 Rumbio Jaya. As an additional value to be obtained, namely increasing the literary insight of the trainees because the reading material chosen by the team is the short story Helvy Tiana Rosa. The method used by the team to achieve this target is the lecture method, question and answer method and practice.
Contextualization Of Short Story Patterns In Indonesian Texbooks For Class IX SMP

Literary works of prose fiction has two main elements, i.e. the elements of the intrinsic and extrinsic elements. The elements of the intrinsic is the most important element to support the passage of the story. Extrinsic elements are outside elements that help build and support a story that is the background of the author of the story and the social conditions of a culture. The purpose of this research is to know is in the pattern of the elements contained in a short story in the book text Bahasa Indonesia kelas IX SMP. This study uses a qualitative method for solving the problem are investigated to describe or write down the circumstances in each story. The source of the data used for this study using the book text Book of Indonesian Language and Literature SMP/MTS class IX Revised Edition 2013 curriculum written by Endah Tri Priyanti-M. Thamrin - Hadi Widodo. The Publisher Of The Earth Script. Book Bahasa Indonesia (Electronic School Book) for SMP/MTS written by Atikah Anindryani-Yuwono-Suhartono, published in 2018. Book Bahasa Indonesia SMP/MTS class IX the Ministry of Education And Culture Republic of Indonesia Revised 2018. Book Language Independent Indonesia SMP/MTS Erlangga Publisher, written by Engkos Kosasish-Restudi, Curriculum revision 2013. The results of the analysis of contextual pattern of short stories in the book text Bahasa Indonesia kelas IX SMP includes elements, characters/characterizations, plot,setting, point of view, the mandate and the style of the language. The value of a character in a short story Bahasa Indonesia kelas IX SMP namely, curiosity, Responsibility, Friendly, Creative, Peace-loving, Religious, patriotism, Discipline, Social Care, Democratic Values, tolerance,hard Work,Social Care
Controlling competencies of future trainers-teachers and ways to improve them

At the present stage in the education system, great importance is attached to the control and evaluation of the course of study and learning outcomes. In the conditions of renewed education within the walls of the school, evaluation actions are a priority. Control is the main function of management and ensures the correct implementation of the assessment. Control work at school requires special training of the teacher, i.e. the competence of the controller, in order for it to be carried out in full. To this end, disciplines that provide general pedagogical training in control are studied in pedagogical universities (Pedagogy, criteria-based assessment technology) and in methodological disciplines corresponding to each specialty, little time is allocated for control and evaluation. These questions do not form a high level of supervising competence of teachers. Therefore, in order to provide training in this direction, there is a need to implement educational materials and skills through special disciplines and interdisciplinary connections. The article highlights the work carried out to determine the controlling competencies of future trainers-teachers of physical culture and the possibilities of the disciplines of the specialty that provide the direction of training being studied. The sequence of questions in the direction of determining the controlling competence is proposed. The ways (methods) of forming the observational competence of future trainers-teachers of the university are considered.
The Willingness of China University Students towards Virtual Reality Technology in Still Life Sketching

With the emergence of COVID-19 in 2019, virtual reality technology in education has gained new prominence.Numerous specialists anticipate the significant application of the technology in respective fields, most notably in art instruction.This study aimed to determine the extent to which Chinese university students majoring in art and design utilise virtual reality technology as a supplement to traditional classroom instruction.In this study, which was limited to still life sketching, the researcher examined students' readiness to use virtual reality technology.Oculus Quest2 was used as a teaching tool in the classroom.This study's objective was to create the framework for the subsequent research phase.A questionnaire survey was used to obtain data for the investigation.The study population included Chinese university students between 18 and 23.However, a study of 226 first-to third-year university students majoring in art or design was conducted.Tencent distributed the questionnaire via WeChat's mini-program.T-test was used to analyse the data collected.The findings showed most students expressed an interest in participating in virtual reality-based still life drawing classes.It entails advancing art education in China to facilitate future art instruction and learning.The findings can guide stakeholders in considering investments in virtual reality technology for still life sketching.
The crooked property

Crooked permutations were introduced twenty years ago to construct interesting objects in graph theory. These functions, over F2n with odd n, are such that their derivatives have as image set a complement of a hyperplane. The field of applications was extended later, in particular to cryptography. However binary crooked functions are rare. It is still unknown if non quadratic crooked functions do exist. We extend the concept and propose to study the crooked property for any characteristic. A function F, from Fpn to itself, satisfies this property if all its derivatives have as image set an affine subspace. We show that the partially-bent vectorial functions and the functions satisfying the crooked property are strongly related. We later focus on the components of these functions, establishing that the existence of linear structures is here decisive. We then propose a symbolic approach to identify the linear structures. We claim that this problem consists in solving a system of linear equations, and can often be seen as a combinatorial problem.
Deployment of Location Mapping Results Based on Application Programming Interface

All user mapping data that has been created in the gis web can also be displayed on the user's own web and can also be displayed through mobile gis. By applying for tokens first to the admin for validation so that the mapping data can be displayed through API-based tokens. When the user wants to display in his own web then the user must enter the mapbox token first and if the user does not have a mapbox token then the user is directed to create a mapbox token first. first into the mapbox whose link has been provided, the purpose of inputting mapbox tokens is to display html scripts / code that are just copy paste in hopes of making it easier for users to see the mapping that has been made.in the gis web to his personal web without creating any more scripts and can be run And for mobile we just copy paste the tokens that are already in the gis web then The mapping data can be displayed immediately.oute of the trip.
Optimized PID Controller based on Artificial Bee Colony Algorithm for Robot Arm

In this paper, an efficient method based on Artificial Bee Colony (ABC) metheuristic is implemented for tuning PID controllers In this paper, an efficient method based on Artificial Bee Colony (ABC) metaheuristic is implemented for tuning PID controllers In this paper, an efficient method based on Artificial Bee Colony (ABC) metaheuristic is implemented for tuning PID controllers.In this paper, an efficient method based on Artificial Bee Colony (ABC) metaheuristic is implemented for tuning PID controllers.This paper deals with design and optimization of a proportional, integral and derivative (PID) controller tuned by Ziegler-Nichols method (ZN) by using artificial bee colony (ABC) optimization algorithm.This algorithm was used to find the optimal parameters of the controller to have optimal performance of a robot arm.A comparative study has been made to highlight the advantage of using ABC-based controller over a ZN-based controller.The validity of the controller tuning algorithms was tested in process control where the optimal tuning procedure of PID controller has also been performed by ABC with different colony sizes.From the perspectives of time-domain performance criteria, such as rise time, overshoot, settling time and steady-state error, the controller tuned by ABC gives better dynamic performances than controllers tuned by the ZN.
Validation of automated malaria parasite diagnostic machines based on first principle: A pre-requisite for acceptable results and treatment monitoring in resource limited settings

Background: Following the very recent introduction of automated malaria parasite diagnostic machines; the need to validate these high technology machines based on the first principle protocol in malaria parasite density determination for acceptable results and treatment monitoring cannot be over-emphasized. The aim of this review is to update Medical Laboratory Scientists, Medical Laboratory Technicians, and researchers alike on the first principle in the diagnosis of malaria using Giemsa stained thick and thin blood films and to build their capacity on how to validate any automated malaria parasite diagnostic machine. Methods: The first principle protocol in malaria parasite density determination was used. With 8 µL of blood spread within 18 mm diameter of circle (thick film), the volume of blood in one thick film field (0.002 µL) is obtained; which when multiplied by a factor (500) gives 1 µL. The number of parasites seen per 100 thick film fields or average number per each thick film field multiplied by 500 gives the number of parasites / µL of blood. Results: Malaria parasites counts of 5 – 50 parasites (1+), 50 – 500 parasites (2+), 500 – 5000 parasites (3+), and (4+) &gt; 5000 parasites / µL of blood, and with the results obtained from the automated machine which when entered into a 2 x 2 table reveal the performance evaluation of automated machine. Conclusion: With several results obtained, any automated malaria diagnostic machine can be validated for its ability to detect disease (sensitivity, specificity, positive and negative predictive values). Commencement of the use of automated malaria parasites diagnostic machines in parasitology laboratory should not lead to discontinuity in the use of thick and thin blood films in malaria diagnosis as it remains the gold standard in resource limited settings.
Toward a multitask aspect-based sentiment analysis model using deep learning

Sentiment analysis or opinion mining is used to understand the community’s opinions on a particular product. This is a system of selection and classification of opinions on sentences or documents. At a more detailed level, aspect-based sentiment analysis makes an effort to extract and categorize sentiments on aspects of entities in opinion text. In this paper, we propose a novel supervised learning approach using deep learning techniques for a multitasking aspect-based opinion mining system that supports four main subtasks: extract opinion target, classify aspect, classify entity (category) and estimate opinion polarity (positive, neutral, negative) on each extracted aspect of the entity. We have used a part-of-speech (POS) layer to define the words’ morphological features integrated with GloVe word embedding in the previous layer and fed to the convolutional neural network_bidirectional long-short term memory (CNN_BiLSTM) stacked construction to improve the model’s accuracy in the opinion classification process and related tasks. Our multitasking aspect-based sentiment analysis experiments on the dataset of SemEval 2016 showed that our proposed models have obtained and categorized core tasks mentioned above simultaneously and attained considerably better accurateness than the advanced researches.
Fuzzy based sequential learning for HDD health status prediction in data center

Data center is the essential part in maintaining data stores and IT systems in an enterprise. HDD (Hard Disk Drive) plays a crucial role in datacenter.The reliability of HDD is to be considered as an important factor.Prevention of Failure in HDD is significant for enabling security over data.In this paper, an Ensemble based sequential learning model was proposed to predict the failure of HDD at earliest.Sequential model learned the history of data and predicts the failure.It learned the pattern and predict the failures.In our approach, LSTM and GRU learning models are used for sequential learning. Ensemble learning was combined with these sequential model for predicting disk failure.The continous data from HDD was observed as SMART data and is used for constructing learning models to predict the results with an accuracy of 89.3%&#x0D;
Outlier analysis for microarray gene

Pre-processing data is a critical component of data mining, as it comprises anomaly identification, outlier analysis, and dimensionality reduction utilising a distance-based technique. This research study demonstrates that in order to cope with scarcity difficulties in high dimensional spaces, computations should be limited to such data. A distance-based technique is seen more appropriate for the microarray-quality articulation of information delivered across many time zones.