Reviewerly/exHarmony huggingface dataset:
State of the Art in Some Cloud Security Through Data Tracking

Today cloud computing helps small businesses and users who miss them powerful resources, a shared information system or data security, etc.Let's introduce through this article: cloud service models, cloud deployment models and essential features, computer security in general. The different solutions proposed in the field of cloud security.We finish with a conclusion and our proposal in this domain to strengthen the security of this new paradigm.
LibGuides: Schmidt Library: Reserves

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Multiple watermarking technique based on RDWT-SVD and human visual characteristics

With the increasing multimedia technology, digital watermarking technique is needed for copyright protection. The multiple watermarking technique is required for embedding more than one watermarks. A major challenge needs to be solved specially to recover multiple watermarks that may be destroyed due to JPEG compression. This paper proposed multiple embedding techniques for watermarks based on RDWT-SVD and human visual characteristics. The proposed scheme examines U(2,1) and U(3,1) components of RDWT-SVD. Our scheme uses Arnold transform to scramble the watermarks before embedding watermarks into the host image. The proposed scheme is tested under several attacks such as image compression, geometrical and image processing attacks. The experimental results show that our scheme can achieve a higher robustness for both recovered watermarks than the existing technique. Our scheme produces high robustness with the normalized-cross-correlation about 0.99 under noise additions. Â© 2005 â�� ongoing JATIT & LLS.
Memory Evaluation Through 360° Technologies: Preliminary Study with Spanish Population

Episodic memory is essential to effectively perform numerous everyday life activities. The current work is focus to investigate the potentiality of 360° technologies in memory evaluation. A preliminary study was developed to investigate if immersive 360° environment could facilitate encoding and recognition memory in comparison to no-immersive 360° one. Results showed that immersive condition could be a potential mechanism to strengthen memory ability.
Complete Addition Law for Montgomery Curves

Montgomery curves allow efficient and side-channel resistant computation of ECDH using the Montgomery ladder. But the addition law of a Montgomery curve derived from the chord-tangent method is less efficient than other curve models such as a short Weierstrass curve and an Edwards curve. So, the usage of a Montgomery curve is strictly limited to ECDH only, such as $$\mathsf {X25519}$$ and $$\mathsf {X448}$$ functions in IETF RFC 7748. For other operations including fixed-base and multiple scalar multiplications, their birationally-equivalent (twisted) Edwards curves are recommended for use since the conversions between Montgomery curves and their Edwards equivalents are simple. This conversion enables the use of the efficient complete addition law of the Edwards curve that works for all pairs of input points with no exceptional cases. As a result, the combination allows secure and exception-free implementations, but at the expense of additional storage for the two curve parameters and for the conversion between them. However, smart devices in IoT environments that mainly operate ECDH (for example, RawPublicKey mode of IETF RFC 7250) do not need to implement such a conversion if a complete addition law does exist for the Montgomery curves. To make such implementations possible, we provide a complete addition law on Montgomery curves. The explicit formulas for the complete addition law are not as efficient as those of Edwards curves, but they can make the Montgomery curve addition operation more efficient compared to using the conversion to the (twisted) Edwards equivalent. We also confirmed the validity of the comparison by implementing such two methods of realizing the addition operation on $$\text {Curve25519}$$.
한자능력시험 선정 한자 고찰

This paper concretely contemplates 3,500 Chinese letters, the first-grade in Chinese letter proficiency test, that are carefully selected by three institutions, The Society for Korean language & literature(한국어문회), Korea Association for the Promotion of Hanja Education(한자교육진흥회), Korea Test Association(대한검정회) respectively. Among those three institutions’ selection of first-grade letters, the following paper has identified 3,022 of common letters and found out each Chinese letter varied greatly in terms of level(grade). Also, explanation of the Chinese letter showed a difference from one institution to another in the extent of 12% to 30%. Such variations make the contents of learning differ severely depends on which institution the learner chose, and it is considered to affect learner’s Chinese letter proficiency ability heavily. Therefore it is inappropriate to be taken as nationally certified examination. The effort of the three institutions unifying the selection of Chinese letter and matching grades and explanation on each Chinese letter for diminishing confusion and increasing the reliability of the certified examination is needed.
Privacy-Preservation of Vertically Partitioned Electronic Health Record using Perturbation Methods

Privacy and security of health data becomes an important issue to be addressed with the advancement of application of ICT health sector. This paper proposed, a novel privacy-preservation hybrid technique using perturbation methods of PPDM on vertically partitioned of electronic health records. The proposed techniques compare with other machine learning methods. The applicability of the proposed techniques had been verified accuracy on UCI dataset.
Guided Layer-Wise Learning for Deep Models Using Side Information

Training of deep models for classification tasks is hindered by local minima problems and vanishing gradients, while unsupervised layer-wise pretraining does not exploit information from class labels. Here, we propose a new regularization technique, called diversifying regularization (DR), which applies a penalty on hidden units at any layer if they obtain similar features for different types of data. For generative models, DR is defined as divergence over the variational posteriori distributions and included in the maximum likelihood estimation as a prior. Thus, DR includes class label information for greedy pretraining of deep belief networks which result in a better weight initialization for fine-tuning methods. On the other hand, for discriminative training of deep neural networks, DR is defined as a distance over the features and included in the learning objective. With our experimental tests, we show that DR can help the backpropagation to cope with vanishing gradient problems and to provide faster convergence and smaller generalization errors.
Character Recognition Operations of a Connectionist Temporal Classification in Neural Network

Neural network plays a major role in recognizing the character from image text lines, usually consist of convolutional neural network (CNN), which performs to extract characters from the text lines of image and Recurrent Neural Network to propagate the sequence of information to neural network. Connectionist temporal classification can handle vanishing gradient problem to reduce loss value during training of the neural network and generate character score that means probability of each character represents like a matrix now to perform sufficient decoding algorithm for to represent text from it. The proposed algorithm word beam search decoding and token passing outperforms on huge amount of different datasets. Beam search decoding replace the word with most probably word to less probability word. Word Beam Search Decoding, which can handle problems like character sting between the different words and have better running time than other decoding methods, which generates the best path on the datasets.
Virtual congkak learning tool using augmented reality

Nowadays, we live in a life where technology has become a part of our lives. Technology has evolved in many ways where it helps us every day. People cannot see themselves without smartphones, computer and etc. Because of the evolution of technology era, many traditional cultures got lost and being forgotten. Some of it were important where it symbolize ourselves. For an instance, traditional games are the symbol of one’s culture. In Malaysia, we have our own traditional games to identify the identity of each cultures we have such as Malay, Chinese and Indians. From Malay’s culture, Congkak is one of a famous game played among the generation. But due to the technological sophistication, people are more attracted to play mobile games instead of traditional games especially to the younger generation. To overcome this problem, Virtual Congkak Learning Tool in Augmented Reality has been developed. This tool was created for the beginners of Congkak because the young generation may be not familiar with the rules of Congkak at all. So this tool will be helpful for them. And also, the idea of creating this learning tool in an augmented reality environment is to expose and attract these young generations to play traditional games, especially Congkak following the advanced technologies today. This application follows Rapid Application Development (RAD) methodology. Virtual Congkak was built using Unity 3D platform with supports of Vuforia for augmented reality. The result of this project was it meets all the objectives and the main functions worked and met the requirements.
Practical Bayesian Optimization over Sets

We propose a practical Bayesian optimization method over sets, to minimize a black-box function that can take a set as a single input. Because set inputs are permutation-invariant and variable-length, traditional Gaussian process-based Bayesian optimization strategies which assume vector inputs can fall short. To address this, we develop a Bayesian optimization method with \emph{set kernel} that is used to build surrogate functions. This kernel accumulates similarity over set elements to enforce permutation-invariance and permit sets of variable size, but this comes at a greater computational cost. To reduce this burden, we propose two key components: (i) a more efficient probabilistic approximation which is still positive-definite and is an unbiased estimator of the true set kernel with upper-bounded variance in terms of the number of subsamples, (ii) a constrained acquisition function optimization over sets, which uses symmetry of the feasible region that defines a set input. Finally, we present several numerical experiments which demonstrate that our method outperforms other methods in various applications.
Vad är ett frivilligt deltagande? - En utredning om våldtäktslagstiftningens frivillighetsrekvisit

The paper examines the new rape legislation with focus on voluntary participation. The purpose is to investigate what voluntary participation is and how the law is supposed to be understood. The legislation is critically reviewed, and the work questions the lack of an absolute requirement of performative consent. This is done on the basis of how sexual consent is to be defined – is it an act or an attitude? The thesis is based on the law and its preparatory works, and also examines court cases where voluntary participation has been crucial. How is voluntary participation interpreted by the courts and is this in accordance with the intention of the legislation?The result is that the requirement ‘voluntary participation’ has an undefined and unclear meaning. It is the courts’ task to assess the voluntary nature and further case law is needed to develop the legal area. At the present, voluntary participation may or may not be expressed in a variety of ways, including through passivity and inner consent. A consequence of this is that the limit for criminality becomes unclear and it is difficult to predict whether a certain action is legal or not. However, the court cases bring some clarity on how to interpret voluntary participation and passivity does not appear to indicate consent. This is further confirmed by NJA 2019 s. 668 where the Swedish Supreme Court states that the scope for interpreting passivity as consent is limited. Other general tendencies from the legal cases are that the previous relationship between the parties and what happened between them before the sexual relation matters.Finally, it can be noted that the new rape legislation seems to have fulfilled its purpose and that more cases than before can be considered rape. However, Issues such as lack of proof and lack of intent still remain. Furthermore, the chosen legislation can also be questioned since voluntary participation lacks a clear definition, which contributes to a lack of predictability and thereby a lack of legal certainty.
LibGuides: Schmidt Library: Staff and Services

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LibGuides: A Guide for Reader's Advisory and Collection Development: Collection Development

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Image Classification by Multilayer Feature Extraction Based on Nuclear Norm Minimization

This paper describes a novel multilayer image classification method based on a nuclear norm of dictionary atoms minimization; in each layer, the method designs dictionary atoms for training dataset by solving a nuclear norm regularized convex optimization problem. The problem promotes non-orthogonality of dictionary atoms and makes coefficient vectors non-negative; these contribute to the improvement of classification accuracies. Experiments result shows that our method is superior to the conventional KLT (Karhunen-Loeve Transform) based multilayer classification method in classification accuracy.
Design of an experimental platform for the automation of the goalkeeper of a foosball table

This paper describes the process of designing, deployment, and testing of an experimental platform whose goal is to automate the movement of the goalkeeper of a foosball table. The platform imposes several challenges that span different disciplines of Electronics Engineering, including computer vision techniques for detecting and tracking the position of the ball and players in the table, estimation algorithms for predicting the movement of the ball, and control algorithms for moving the rod that holds the player. Besides, the characteristics of the application impose stringent requirements in terms of precision and processing speed, which requires an adequate choice of the software and hardware for the communication, storing, and processing of data in real-time. The developed platform will serve in teaching and research activities in the context of modern cyber-physical systems, including the experimental characterization and validation of machine learning, control, estimation and computer vision algorithms, and the integration and evaluation of specialized computing platforms for accelerating computationally intensive processes. Moreover, because of the popularity of foosball tables, this experimental setup serves as an ideal platform for outreach activities related to STEM in non-academic audiences.
Responsibility, what's appropriate?

"Thus SIGCAS was born amidst controversy... And the work of the SIG, if done correctly, will undoubtedly invite controversy." 1 Whether intentional, Mark Zuckerberg's, Chief Executive Officer of Facebook, position on free expression and Internet platforms has undoubtedly invited controversy. As Mr. Zuckerberg is a recognized leading computing professional, I applaud him for taking a stand and "addressing concerns and raising awareness about the ethical and society impact of computers", which is the defined scope of SIGCAS' specialty [2]. As Editor-in-Chief, it is my honor to extend Mr. Zuckerberg an invitation to engage the SIGCAS community by contributing to Computers and Society , especially as our membership raises any concerns on his position. I understand Facebook is a commercial entity, but together "all people are stakeholders in computing" [1].
Underwater image dehazing and color correction algorithm based on scene depth estimation

The problem of restoring images degraded by an underwater environment is challenging, in part because light traveling underwater suffers from two combined degradations, known as scattering and absorption, which leads to inaccurate transmittance estimation. In this work, we propose that underwater image dehazing and color correction algorithm based on scene depth estimation. Through scene depth estimation, we get accurate transmittance to achieve better dehazing effect. The experimental results show that our approach obtains good-quality images, with a visibility enhancement comparable or better than other recent methods. As for color recovery, We recovere among different images, regardless of the different water conditions. In this work we not only achieves the effect of underwater image dehazing, but also guarantees accuracy and timeliness of recovery results.
Isolated Malay speech recognition using fuzzy logic

Artificial intelligence (AI) is one of the method that human use to communicate between human and computer. There are a lot of applications has been produces by AI approach such as medical diagnosis, proving mathematical theorems and autonomous vehicle. Many methods and approach has been used by researcher to develop speech recognition system such as neural network and Hidden Markov Model. This research aim is to develop a isolated Malay speech recognition using Fuzzy Logic method. This research is focused on six isolated words which is empat (four), lapan (eight), rekod (record), tidak (no), tujuh (seven), and tutup (close). This research is also focused on the development of fuzzy rules between each words. The evaluation process is measured based on the accuracy rate between the previous method using Hidden Markov Model. The result show that 75% speech recognition accuracy rate using fuzzy logic method.
Introduction to the course "Open science and research data management" (Pisa January-March 2020)

1. Scholarly communication and research evaluation: the Open Science Revolution2.Irresistible proxies? Peer review and (mainstream or alternative) bibliometric3. Copyright: taking authors' rights seriously4. General handout containing some additional explanations and clarifications.DOI: 10.5281/zenodo.3668872
You Learn A Lot Talking To Yourself Online in #IndieWeb Chat

The self directed nature of knowledge quilting relies heavily on agentive #apprenticeship. The network needs to provide resources even when experts are not around.We handle
Improving The Students Writing Narrative Text Through Problem Based Learning At Ten Grade SMK 2 Satrya Budi Perdagangan

This research was using classroom action research which the cycle did in three times consist of precycle, cycleone, and cycletwo. The subject of there search was X-RPL students of Smk 2 Satrya Budi Perdagangan in the academic year of 2019/2010. The data was gotten from students’ achievement that was obtained froms tudents’ score in the test, and data observation from students’and teacher’s activities during teaching learning process took place. There was also documentation that was used to look for the data concerning matter sorth evariable that are taken in the form of then or photo in teaching learning process. This research showed that apply problem based learning to improve writing in narrative text could help the students. Problem based learning could be a solution for the student stomake narrative text easier because problem based learning pose situation as stimulation which the students could develop ideas. There was an improvement on students score too. The mean of the tests score was 43,4 in precycle, it was becoming 56,2 in the first cycle, and it wasb ecoming 83,9 in the second cycle. Finally the result of this research had the improvement of students’ writing in narrative text and the improvement in the students’ positive response after being taught by problem based learning. Hope fully this research can be a reference for teacher of English to teach narrative text and for next researcher for conducting next research.
Preparing English for Nursing Students Course Based on Need Analysis

Mastering English is compulsory for every nurse, especially when they serve foreign patients. However, not every nurse has mastered English since not every institute has got English for Specific Purposes (ESP) course. This research aims to explore 30 nursing students’ in Kartini vocational high school learning need by doing study based on Need Analysis that is classified into Target Situation Analysis, Present Situation Analysis, and Learning Situation Analysis. Both quantitative and qualitative methods are used. This research is also supported by other researches which found out that communication is a skill that the nursing students and nurses are weak at. Speaking and Listening are the two most difficult skills for them. By not having ESP course, the nurses and the nursing students feel difficult while interacting with the foreigner since they do not understand about medical vocabularies or they are still weak in English. Consequently, this research may design the right ESP course for the nursing students and nurses. In addition, doing need analysis on nursing students who have got ESP course can be conducted in the future to see the difference of the results.
What Is Jakarta EE?

You have learned what Java EE is. You've seen what an application server is and how it relates to the term Java EE. Now it’s time to consider what Jakarta EE is.
LibGuides: Applied Behavior Analysis: Get Articles We Don't Have through Interlibrary Loan

Includes suggested databases, search techniques for finding single subject studies, and links to ABA journals. Step-by-step instructions for filling out an Interlibrary Loan request
The Privacy Preservation of Patients’ Health Records using Soft Computing in Python

The digitization of Electronic health records (EHRs) of a patient always offer a lot of advantages to the patients, keep track of his/her health record, which is much better than traditional system of keeping patients’ records manually by the hospital. Today, EHRs are widely adopted by the health sector across the world, EHRs always rich in sources to get information for stakeholders and research and development department for analysis and monitoring, however there is a risk related to patient’s data privacy due to improper published data. In this, the need of privacy is that the patients should have an option to access and authority to provide personal information publicly or not. One of the most common models used in privacy preservation was anonymization model which was popularly used to remove privacy breaches, however this model was only focused on identity disclosure. In this paper, we emprise on a balanced p+ sensitivity combined with t-closeness model for privacy preservation of Electronic health records. We presented that sensitivity combine with t-closeness provides better results than previous work in of different k-anonymity models. In this paper we used Machine Learning classification algorithms such as Support Vector Machine (SVM) and K-Nearest Neighbors (KNN) to justify our analysis using python language for their implementation.