Reviewerly/exHarmony huggingface dataset:
Farsi Speech Synthesis Using Pitch Frequency in Flite Software

This survey introduces a model and the implementation of a speech synthesizer in Farsi language using Flite software. In this approach, the mean and the standard deviation of pitch frequency of each voiced phoneme are first calculated by a database of Farsi sentences (Fars Dat). Then, the changes of each phoneme of the desired phrase are inserted into the software through the calculation of a value. The main feature of this synthesizer is its ability to change text to speech within Farsi pronunciation and in Farsi dialect. At the end of this paper, the results of this algorithm are compared to the changes of pitch frequencies extracted from the database of Farsi sentences. Some examples of the sentences from the database are also synthesized using our proposed method on Flite Software. The value of MOS test for understandability, naturalness and good sounding of those sentences are 4.4, 4.2, and 4.6 for the training set, respectively, and 4.2, 4.1, and 4.3 for the test set, respectively.
A Study of Plans of Cultural Contents Literacy Education as a College Subject of Liberal Arts through a Case Analysis : A Case Study on the “Cultural Contents Literacy” Class at D University

It is required to extend the scope of cultural contents literacy education and establish a systematic methodology in accordance with features and environment of contents that diversify day by day. In light of such necessity, this study was intended to reconsider educational possibilities of cultural contents literacy and propose practical curriculum design and operation plan.<BR> To this end, firstly, this study inquired into the necessity of course establishment and main elements of curriculum design focused on “Cultural contents literacy” class, which was established and effectively operated at D University during the first semester of 2020. Secondly, based on the results, this study aimed to propose class activities that can be applied to real cultural contents literacy education.<BR> This study expects that cultural contents literacy education, which is still in the initial stage, can be systematically established and settled in earnest at colleges, by achieving discussion on design and operation of a variety of relevant courses other than the subject proposed as a case of this study.
ESPLORAZIONE DEL CONCETTO DI FORZA CON L’UTILIZZO DI DESMOS IN UN PERCORSO DIDATTICO

Teachers have been asked to integrate new technologies with didactic education as it happened during COVID-19 times; this has been a real opportunity to review disciplinary and methodological approaches and to enhance features that usually traditional teaching does not use. The learning and the epistemological constructions are promoted also by the use of targeted software that may support the conceptual difficulties in Physics Education through high level of students’ interaction. Our work proved to be quite successful in achieving this support in learning: during the first lockdown period, we proposed a learning unit on the concept of force according to the Newtonian Dynamics using the Desmos software to students in the secondary school. The technological integration is crucial to complete the educational project and it could also be promoted in a non-emergency teaching setting.
Smart Reader Al-Quran Sensor / Muhammad Fauzan Hazim Mohd Nazri

The product that my company created is Smart Al-Quran Reader Sensor. This product is suitable for all kind generation Muslim person. This product also suitable for non-muslim person for who try to learn about Al- Quran, Hadith, Sirah and more about Islam. This is because person who do not know how to read Al-Quran and want to learn about Islam will easy learn with this product. Why did I say it was suitable? This is because the product comes with many materials, for example Digital Al.Quran, Sirah book, Hadith book, Tafsir, pen reader and many more. Customers who do not know how to read and want to learn just put the pen reader point at the Digital Al-Quran and other materials. This pen reader will emit sound the content of the Digital Al-Quran and the other materials. If they do not know, they will learn a lot there. There are many companies that have produced this product that are similar to our product but we have already created some differences in this product that other companies do not have. We improve by placing sound sensors on our products that other companies do not have. The customer or reader can challenge or test themselves to recite Al-Quran. The sensor will detect the reader's voice when they recite the Al-Quran. If they read the Quran wrongly, the pen will give a signal that the reader is misreading. Thus, they can evaluate their reading level.
No Child Left Behind’s ‘Laptops for Learning’ campaign launches

Can you help every child in Cheltenham access digital learning by donating your old laptops, tablets, ipads or by giving some money to #LaptopsForLearning?
APPRECIATE ENSERA USING ACTING TECHNIQUES IN THE CLASSROOM

The influence of the classroom environment is a very important element because it can influence students' interest in Iban Language subjects in school, especially interest in Iban literature. Fun activities such as using acting techniques in teaching and learning ensera (Iban folklore), able to hone students' talents from the field of acting and can form a balanced human being in terms of intellectual, spiritual, emotional, and physical. Acting technique is a very popular activity because students can learn while entertaining students. This technique can be carried out if the teacher is able and able to provide an acting script or short dialogue in ensera with an interesting storyline and ask students to read and remember the dialogue. This activity can give birth to elements of appreciation including character, language style, values, beauty, cultural elements, and the like. Thus, Iban students can appreciate ensera well and are able to master it. The research method using the field method utilizes three types of research methods namely semi-structured interview method, observation, and video recording. The findings of the study show that the role of ensera appreciation through acting techniques in the context of teaching and learning is fully used in the classroom. The implication is that students can give very thoughtful opinions in terms of knowledge, existing experience, enjoyment, and appreciation, and encourage students' interest in teaching the Iban language with an appreciation of ensera.
Best Computer For Android Development

There is no doubt that HTML, PYTHON, and JAVASCRIPT will run perfectly on a simple computer and afford you much time, and effort as your code your way ...
Composite Adversarial Training for Multiple Adversarial Perturbations and Beyond

One intriguing property of deep neural networks (DNNs) is their vulnerability to adversarial perturbations. Despite the plethora of work on defending against individual perturbation models, improving DNN robustness against the combinations of multiple perturbations is still fairly under-studied. In this paper, we propose \underline{c}omposite \underline{a}dversarial \underline{t}raining (CAT), a novel training method that flexibly integrates and optimizes multiple adversarial losses, leading to significant robustness improvement with respect to individual perturbations as well as their ``compositions''. Through empirical evaluation on benchmark datasets and models, we show that CAT outperforms existing adversarial training methods by large margins in defending against the compositions of pixel perturbations and spatial transformations, two major classes of adversarial perturbation models, while incurring limited impact on clean inputs.
The Role of Organizational Culture in the Implementation of E-Administration: A Field Study at Banks in Hodeidah

The study aimed to identify the organizational culture practice and its impact on the application of e-administration in the banks operating in Hodeidah. The study used the descriptive analytical method. Since the study population consisted of only (146) administrative staff members, (126) members were selected by the complete census method to whom the questionnaire was distributed to collect relevant data. Major findings showed various degrees in the level of organizational culture and e-administration in favor of the independent variable (organizational culture). Findings also showed statistically significant positive impact of organizational culture represented by its four dimensions (organizational norms, organizational expectations, organizational values, and organizational beliefs) on the application of e-administration. Furthermore, it was found that there were no statistically significant differences of the mean scores among sample's responses on the level of application of e-administration attributed to their demographic variables. However, there were statistically significant differences in the level of organizational culture attributed to gender and courses of computer skills, but there were no differences in other demographic variables. The study recommends that organizational culture in banks regulations should be promoted in order to help them introduce modern technology (e-administration) in all their activities.
Reform and practice of innovation and entrepreneurship practice education system for electronic information college students under the perspective of new engineering

With the continuous deepening of Chinese innovation-driven development strategy, the demand for innovative talents is increasing rapidly. As the main force of innovation and entrepreneurship, college students are essential to cultivating their scientific and technological innovation capabilities. First, the innovation and entrepreneurship education system is elaborated. Then, starting from “training mode, curriculum reform, teacher education, resource platform, quality evaluation,” we set up a multidimensional innovative talent training mode, construct a two-way integration curriculum system of professional education and innovative education, and create “three-dimensional” high-quality school-based curriculum resources. We should set up a high-quality education practice platform, then achieve organic integration between professional education and innovation and entrepreneurship education. After continuous reform, we have achieved remarkable results, and put forward future reform strategies.
The Absolute Smallest Possible Money Unit! When Money Crashes into the Laws of Physics

In this paper, we demonstrate that there is an absolute physical limit on how small the smallest money unit can be, no matter how much we are able to improve our technology. The smallest money unit seems to be directly linked to the smallest possible energy unit needed to store one bit. If the smallest money unit is smaller than the cost of energy of storing one bit then there seems to be an arbitrage, which will also constrain money producers such as central banks from issuing money with a smaller denomination than this minimum money unit.
An Efficient Support Vector Machine Algorithm for Age and Gender Detection from Face Pictures

In this paper, a novel kernel function is proposed to perform an efficient Support Vector Machine, SVM, classification for age and gender estimation and detection. A robust, easy-to-execute algorithm is proposed based on the SVM as a core method to simultaneously predict the age and gender of highly variable pictures. Owing to its efficiency because of kernel function proposed in this paper, the SVM based algorithm is able to powerfully classify the features, leading to more accurate and precise estimation of age and gender. The algorithm is modified to solve the simple problems as well as complex situations, estimating age and gender simultaneously. The mean error of proposed method is between 5.2% – 7.3% that the less accurate results higher ages are due to lack of sample pictures in training phase. To be fair, all of the comparisons with other methods were done on the same database, FG-NET, including 1002 pictures with different qualities, diverse styles, and various rate of face coverage. The simulation results show that the proposed method has lower mean error in comparison with other recent related works.
FORMATION OF THE ELECTRONIC INFORMATIONAL AND EDUCATIONAL ENVIRONMENT AT SCHOOL UNDER CURRENT CONDITIONS

The article considers the issues of formation and development of electronic informational and educational environment of the school. The authors carried out the analysis of the definitions related to the electronic informational and educational environment concept, found in the works of researchers and educational practitioners. The structure of the electronic informational and educational environment was given andits components were described. An activity plan for the creation, development and implementation of the electronic informational and educational environment and the regulatoryframework for its formation and development were considered. Recommendations for the improvement and development of the electronic informational and educational environment were given.
Predicting user behavior based on informative lifelogging

From 2011 to now, the authors of this paper have published the personal Geotagged photo dataset named Informative Lifelogging on the Internet, which has a total of 6000 personal life records. Each dataset includes photos, GPS information, time, description, and address information. At the same time, the authors tagged each dataset to distinguish the behavior classification of these data. In this paper, we introduce the dataset for more researchers, and then the authors mainly discuss how to predict the behavior of individual users based on the dataset collected.
Research on the Types and Legal Basis for Biosecurity Crimes under the New Situation

Today, China is facing many risk factors and great challenges in biosecurity crimes. Biosecurity-related crimes generally include biological weapon attack, bioterrorism, destruction of biological genetic resources and biodiversity, and finally, interference with infectious disease prevention and control. Crimes related to biosecurity in the Criminal Law of China are mainly stated in the chapters about crimes jeopardizing state security, against public security, social administration, and crimes of dereliction of duty.
A Phishing URL Classification Technique using Machine Learning Approach

The phishing attack is one of the very common attacks deployed using the social engineering techniques. The attack tries to capture the victim’s personal and sensitive information to trick and can results in terms of financial and social reputation loss. In this presented work the main focus is to investigate the phishing techniques and their detection approaches. In this context first a review on recently contributed URL based phishing attack detection and prevision techniques is prepared. Further based on the suitable techniques a new data mining based model is proposed for implementation. The proposed model first take training on phish tank database URLs and then identify the similar pattern based URLs in two classes legitimate and phishing. First the dataset is preprocessed and the features are computed. The computed features are then transformed in terms of transactional database and association rules are prepared. To generate the association rules the apriori algorithm and FP-Tree algorithm is employed. Based on conducted experiments, the performance the FP-Tree based classification technique much efficient and accurate as compared to apriori algorithm, because the apriori algorithm is much time expensive then the FP-Tree. Finally the future extension of the work is also suggested.
The Virtual Simulation Experiment of Chloroacetic Acid Production Process Helps Students Improve Comprehensive Ability

The integration of information technology and education promotes the wide application of virtual simulation experiment in teaching activities. The 3D virtual simulation experiment of chloroacetic acid production process is set based on the preparation, separation and tail gas recovery of chloroacetic acid. This project integrates the basic chemical theory, chemical unit operation, typical chemical equipment principles and operations into two parts: cognition practice and production practice. The paper gives a detail description about the construction and implementation of virtual simulation experiment of chloroacetic acid production process in chemical engineering experiment teaching. It can not only help students apply the chemical unit operation and corresponding equipment to chemical production, but also review the basic chemistry theories such as reaction mechanism, reaction kinetics and thermodynamics. A teaching model based on studentsâ€™ self-directed learning and teacher guidance is adopted, and the quality management and evaluation can be accurate to before, in and after class through simulation software platform. Application of this system has proved that the virtual simulation experiment teaching cannot only help students master the application of momentum transport, energy transport, quality transport, reaction engineering chemical engineering unit operations and the corresponding typical equipment, but also provides a powerful guarantee for students to effectively combine them with practice, and cultivates the safety production consciousness.
Physical Sciences: An Inspiration to the Neural Network Training

Behind every discovery, observation plays a vital role. The neural networks (NNs) are the result of a very minute neuron observation. This led to a revolution in the field of artificial intelligence. On the contrary of the biological inspirations, we present some of the physical sciences models that could be further related to neural network training phase. These relations are the momentum, solar orbits and the shape of a water droplet. Momentum is related to the weight optimization during NNs training phase and Solar orbits helps to understand the epoch’s concept. At the end, shape of a water droplet concept gives us the motivation behind the loss function optimization. These three are just some of the many inspirations that we can obtain from physical sciences. This paper can be the beginning of a whole new theory to the neural networks.
A Siamese Neural Network for Behavioral Biometrics Authentication

The raise in popularity of personalized web and mobile applications brings about a need of robust authentication systems. Although password authentication is the most popular authentication mechanism, it has also several drawbacks. Behavioral Biometrics Authentication has emerged as a complementary risk-based authentication approach which aims at profiling users based on their behavior while interacting with computers/smartphones. In this work we propose a novel Siamese Neural Network to perform a few-shot verification of user's behavior. We develop our approach to identify behavior from either human-computer or human-smartphone interaction. For computer interaction our approach learns from mouse and keyboard dynamics, while for smartphone interaction it learns from holding patterns and touch patterns. We show that our approach has a few-shot classification accuracy of up to 99.8% and 90.8% for mobile and web interactions, respectively. We also test our approach on a database that contains over 100K different web interactions collected in the wild.
Growth of Indian library and information science literature: A study of Annals of Library and Information Studies

The growth of the LIS literature of 1985-90 and 2005-2010 as reflected through Annals of Library and Information Studies is studied. The paper examines the year-wise growth of the library and information science literature, subjects covered during the specified periods, the most used form of literature, authorship pattern, and most cited journals. Among other things, the study finds that a few areas of research such as ICT applications in LIS are more during the period 2005-2010.
ALFA: Adversarial Feature Augmentation for Enhanced Image Recognition

Adversarial training is an effective method to combat adversarial attacks in order to create robust neural networks. By using an auxiliary batch normalization on adversarial examples, it has been shown recently to possess great potential in improving the generalization ability of neural networks for image recognition as well. However, crafting pixel-level adversarial perturbations is computationally expensive. To address this issue, we propose AdversariaL Feature Augmentation (ALFA), which advocates adversarial training on the intermediate layers of feature embeddings. ALFA utilizes both clean and adversarial augmented features jointly to enhance standard trained networks. To eliminate laborious tuning of key parameters such as locations and strength of feature augmentations, we further design a learnable adversarial feature augmentation (L-ALFA) framework to automatically adjust the perturbation magnitude of each perturbed feature. Extensive experiments demonstrate that our proposed ALFA and L-ALFA methods achieve significant and consistent generalization improvement over strong baselines on CIFAR-10, CIFAR-100, and ImageNet benchmarks across different backbone networks for image recognition.
Revisiting the Stability of Stochastic Gradient Descent: A Tightness Analysis

The technique of algorithmic stability has been used to capture the generalization power of several learning models, especially those trained with stochastic gradient descent (SGD). This paper investigates the tightness of the algorithmic stability bounds for SGD given by~\cite{hardt2016train}. We show that the analysis of~\cite{hardt2016train} is tight for convex objective functions, but loose for non-convex objective functions. In the non-convex case we provide a tighter upper bound on the stability (and hence generalization error), and provide evidence that it is asymptotically tight up to a constant factor. However, deep neural networks trained with SGD exhibit much better stability and generalization in practice than what is suggested by these (tight) bounds, namely, linear or exponential degradation with time for SGD with constant step size. We aim towards characterizing deep learning loss functions with good generalization guarantees, despite being trained using SGD with constant step size. We propose the Hessian Contractive (HC) condition, which specifies the contractivity of regions containing local minima in the neural network loss landscape. We provide empirical evidence that this condition holds for several loss functions, and provide theoretical evidence that the known tight SGD stability bounds for convex and non-convex loss functions can be circumvented by HC loss functions, thus partially explaining the generalization of deep neural networks.