Reviewerly/exHarmony huggingface dataset:
Non-Markovian dynamics of a dephasing model in a squeezed thermal bath

The non-Markovian dynamics of a qubit dephasing in a squeezed thermal environment with general Ohmic spectral density are investigated, and the analytical solution is presented for the models with sub-Ohmic, Ohmic, and super-Ohmic spectral densities in the zero-temperature limit. We study the non-Markovianity of the open qubit system, and find that it is very large in a certain regime of the squeezed parameters and almost vanishes outside this regime, given the parameters of the environmental spectrum. Furthermore, the non-Markovianity can be enhanced to surpass that of the unsqueezed case by adjusting the squeezing parameters. More interestingly, we find that given the other parameters, the non-Markovianity of a small coupling constant between the qubit and its environment may be larger than in the case of a large coupling constant; this is dependent on the competition between the coupling constant and the Ohmicity parameter of the environment. We also discuss the influence of squeezing operator on the quantum speed limit (QSL) time for the considered model, and find that the QSL time can be reduced via the adjustment of the squeezing operator.
Research on Classification of Scientific and Technological Documents Based on Naive Bayes

Text classification is an important step for text mining in the direction of data mining. Today, text categorization techniques are widely used in various fields, such as user behavior analysis in shopping recommendation systems, and spam filtering, but text categories based on scientific literature are seldom studied. This article uses biological material information. The scientific literature of the aspect is text, and the naive Bayesian method is used to classify the literature into different topic types. It is evaluated through the model test standard in data mining to verify the validity of the method. Finally, the research trend of biological materials A simple analysis was performed.
Pengembangan Android Apps Berbasis Discovery Learning Untuk Meningkatkan Pemahaman Konsep Matematis Siswa Kelas VII

Lack of innovative learning media that is interesting, practical and easy to use in learning such as listening to lesson modules or seeing powerpoint shows used by teachers, thus causing learning to be ineffective, unattractive, and slow to understand, this results in a lack of understanding of mathematical concepts. Because of this, researchers are trying to develop an interesting and interactive learning media. This type of research is development research that aims to produce learning media on Android-based discovery learning apps that are feasible to use and to improve understanding of mathematical concepts of seventh-grade students. The method used is the ADDIE method. Which consists of 5 stages, namely Analysis, Design, Development, Implementation, and Evaluation. Data analysis was carried out by normality, homogeneity, n-gain test, and right-sided t test. The results of this study can be concluded that (1) the results of the percentage of media expert validation amounted to 80.26%, material experts 86.36% and student response responses of 87.16% with the criteria of each very good. (2) the results of the n-gain test obtained that there is an increase in understanding of mathematical concepts of students who use learning media on Android-based discovery learning applications. (3) data from the field shows that student learning outcomes that obtain learning media android apps based on discovery learning are better than students who use conventional learning
Sistem Pendukung Keputusan Pemilihan Mobil Bekas dengan Metode AHP dan SAW pada Nava Sukses Motor

Someone buying a used vehicle in determining his choice, of course, is based on several criteria that are used as a benchmark in choosing used car vehicles, including engines, body, interior, frame number & engine, letters & taxes, and prices. These criteria are a consideration for buying a used car, various considerations are made by a buyer to get a good and good used car. Difficulties in choosing a used car, a reference is needed as a rationale for choosing a used car. Decision support systems offer a solution for referrals in choosing a used car. Decision support systems offered using Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) in solving problems. Problems can be solved using a ranking system based on global weighting. Buyers of used car vehicles can choose used cars based on references or recommendations from expert decision support systems. Based on the results of the calculation of the assessment criteria proposed to the system, the determination of used cars is obtained through calculating the priority weight values for the selection of used cars to be purchased. With the Decision Support System to choose used cars using the Analytical Hierarchy Process (AHP) method and Simple Additive Weighting (SAW) in determining used cars the accuracy rate is 73% compared to using the Simple Additive Weighting (SAW) method which has a level of accuracy only 60%.
Illumination invariant face recognition using dual-tree complex wavelet transform in logarithm domain

Abstract In this article, we develop a new algorithm for illumination invariant face recognition. We first transform the face images to the logarithm domain, which makes the dark regions brighter. We then use dual-tree complex wavelet transform to generate face images that are approximately invariant to illumination changes and use collaborative representation-based classifier to classify the unknown faces to one known class. We set the approximation sub-band and the highest two DTCWT coefficient sub-bands to zero values before the inverse DTCWT transform is performed. Experimental results demonstrate that our proposed method improves upon a few existing methods under both the noise-free and noisy environments for the Extended Yale Face Database B and the CMU-PIE face database.
Proposed A Permutation and Substitution Methods of Serpent Block Cipher

Block cipher technique is one of cryptography techniques to encrypt data block by block. The Serpent is one of AES candidates. It encrypts a 128-bit block by using 32 rounds of a similar calculation utilizing permutations and substitutions. Since the permutations and substitutions of it are static. Then this paper proposes dynamic methods for permutation, substitution and key generation based on chaotic maps to get more security. The proposed methods are analyzed and the results showed that they were able to exceed the weakness resulting from the use of static permutations and substitutions boxes in the original algorithm and also can reduce number of rounds and time usage compared with a classical Serpent block cipher algorithm
Chapter 11. Stable variation in multidimensional competition

The Fundamental Theorem of Language Change (Yang 2000) implies the impossibility of stable variation in the Variational Learning framework, but only in the special case where two, and not more, grammatical variants compete. Introducing the notion of an advantage matrix, I generalize Variational Learn-ing to situations where the learner receives input generated by more than two grammars, and show that diachronically stable variation is an intrinsic feature of several types of such multiple-grammar systems. This invites experimentalists to take the possibility of stable variation seriously and identifies one possible place where to look for it: situations of complex language contact.
A holographic waveguide based eye tracking device

We demonstrated the feasibility of using a holographic waveguide imager for eye tracking. A holographic waveguide placed in front of the eye was used to capture images of the anterior segment of the eye and to guide the images to a camera distant from the eye. The pupil centre (PC) and corneal reflection (CR) of the eye was used to compute eye position. A custom-built model eye was used to validate the prototype eye tracker. A linear relationship between the angular eye position and the PC/CR vector was found over 60 horizontal degrees and 40 vertical degrees. The tracking accuracy and precision were 0.72 degree and 0.50 degree over these tracking ranges. These results confirmed that holographic waveguide could be a viable platform for developing compact, wearable, see-through eye trackers that can continuously monitor eye movements during real life tasks and thus can facilitate diagnosis of oculomotor disorders.
CONSTRUCTION OF EVEN-DIMENSIONAL LATTICES OF FULL DIVERSITY

In this work even-dimensional ideal lattices of full diversity are obtained via the twisted homomorphism of the ring of integers of a totally real subfield of Q(ζ p ), where p is an odd prime.
A new local path planning approach based on improved dual covariant Hamiltonian optimization for motion planning method

We propose a new local path planning approach based on optimization methods with probabilistic completeness in this article. This approach adds a linear constraint to the original covariant Hamiltonian optimization for motion planning problem with a new cost function. By deducing the dual form, the path planning problem is described as a box-constrained quadratic programming problem. The nonmonotone gradient projection algorithm is introduced to solve the dual problem, which makes the algorithm adaptable to non-convex cost functions. In order to prevent early convergence at local minima that can occur when applying optimization methods, this article introduces Hamiltonian Monte Carlo to the modification, which constantly forces the initial path to jump out of the local extremum, thus improving the robustness and success rate of the path planning approach. Compared with other methods through simulations, this approach is proven to provide balanced planning efficiency and path quality. The feasibility in a real environment is experimentally validated by applying the approach to a wheeled mobile robot.
Effect of Inflation on Economic Growth of Ethiopia

The interaction between growth and inflation is one of the macroeconomic problems.Determining the effect of inflation on the economic growth of one country must be considered as a prior issue to build up a healthy economy.The main objective of this paper is to test that, whether inflation is an indicator or obstacle for economic growth of Ethiopia.Pair wise Granger causality test has been made to verify the objective of the paper and the pairwise Granger causality test result suggesting the existence of strong and significant correlation between variables pairwise.The test reveals a uni-directional causation between, real GDP and export (EX) and between real GDP and inflation and real GDP and investment.The causation runs from real GDP to inflation, real GDP to export and real GDP and investment respectively.In addition, taking the main objective which hypothesizes to proof whether inflation cause economic growth or the reverse holds true, the granger causality test pertains a uni-directional causation which runs from economic growth to inflation.Accordingly one can conclude that economic growth can cause for inflation but inflation doesn't cause economic growth during the study period in Ethiopia .Based up on the finding it is evident that balancing economic growth target in line with a monetary policy target may have a vital role to boost economic growth and control the level of inflation.
Experience and lessons learned from the Army RCO Blind Signal Classification Competition

The Army Rapid Capabilities Office (RCO) sponsored a Blind Signal Classification Competition seeking algorithms to automatically identify the modulation schemes of RF signal from complex-valued IQ (in-phase quadrature) samples. Traditional spectrum sensing technology uses energy detection to detect the existence of RF signals but the RCO competition further aimed to detect the modulation scheme of signals without prior information. Machine Learning (ML) technologies have been widely used for blind signal classification problem. Traditional ML methods usually have two stages where the first stage is to manually extract the features of the IQ symbols by subject matter experts and the second stage is to feed the features to an ML algorithm (e.g., a support vector machine) to develop the classifier. The state-of-art technology is to apply deep learning technologies such as Convolutional Neural Network (CNN) or Recurrent Neural Network (RNN) directly to the complex-value IQ symbols to train a multi-class classifier. Our team, dubbed Deep Dreamers, participated in the RCO competition and placed 3rd out of 42 active teams across industry, academia, and government. In this work we share our experience and lessons learned from the competition. Deep learning methods such as CNN, Residual Neural Network (ResNet), and Long Short-Term Memory (LSTM) are the fundamental neural network layers we used to develop a multi-class classifier. None of our individual models were able to achieve a competitively high ranking in the competition. The key to our success was to use ensemble learning to average the outputs of multiple diverse classifiers. In order for ensemble methods to be more accurate than any of its base models; the base learners have to be as accurate as possible. We found that while ResNet was more accurate than the LSTM; the LSTM was less sensitive to deviations in the test set.
Identity-as-a-Service: An Adaptive Security Infrastructure and Privacy-Preserving User Identity for the Cloud Environment

In recent years, enterprise applications have begun to migrate from a local hosting to a cloud provider and may have established a business-to-business relationship with each other manually. Adaptation of existing applications requires substantial implementation changes in individual architectural components. On the other hand, users may store their Personal Identifiable Information (PII) in the cloud environment so that cloud services may access and use it on demand. Even if cloud services specify their privacy policies, we cannot guarantee that they follow their policies and will not (accidentally) transfer PII to another party. In this paper, we present Identity-as-a-Service (IDaaS) as a trusted Identity and Access Management with two requirements: Firstly, IDaaS adapts trust between cloud services on demand. We move the trust relationship and identity propagation out of the application implementation and model them as a security topology. When the business comes up with a new e-commerce scenario, IDaaS uses the security topology to adapt a platform-specific security infrastructure for the given business scenario at runtime. Secondly, we protect the confidentiality of PII in federated security domains. We propose our Purpose-based Encryption to protect the disclosure of PII from intermediary entities in a business transaction and from untrusted hosts. Our solution is compliant with the General Data Protection Regulation and involves the least user interaction to prevent identity theft via the human link. The implementation can be easily adapted to existing Identity Management systems, and the performance is fast.
Modification in Hill Cipher for Cryptographic Application

In order to keep the information secure from various contenders is an important factor for data security.For any organization, it is an incredibly important feature to timely transmit secured data.Optimized techniques for key management and protected encryption algorithms are always helpful for reducing the overhead of the system and maintain the integrity, authentication and confidentiality of data.Cryptographic applications play an important role in our daily lives through sending emails, exchanging bank account transaction information, through mobile communication and through ATM card transaction.To secure our information from unauthorized users, Hill Cipher is one of the most well-known symmetric cryptosystems.For Hill Cipher, here we are proposed an algorithm for encryption and decryption which is based upon the transposition, substitution and left-right shift.
KLASIFIKASI SENTIMENT ANALYSIS PADA KOMENTAR PESERTA DIKLAT MENGGUNAKAN METODE K-NEAREST NEIGHBOR

The process of analyzing and classifying comment data done by reading and sorting one by one negative comments and classifying them one by one using Ms. Excel not effective if the data to be processed in large quantities. Therefore, this study aims to apply sentiment analysis on comment data using K-Nearest Neighbor (KNN) method. The comment data used is the comments of the participants of the training on Udiklat Jakarta filled by each participant who followed the training. Furthermore, the comment data is processed by pre-processing, weighting the word using Term Frequency-Invers Document Frequency, calculating the similarity level between the training data and test data with cosine similarity. The process of applying sentiment analysis is done to determine whether the comment is positive or negative. Furthermore, these comments will be classified into four categories, namely: instructors, materials, facilities and infrastructure. The results of this study resulted in a system that can classify comment data automatically with an accuracy of 94.23%
The Development of Phonological System Made by the Children

Language is one of the most important and difficult for young children in communication. Most children learn to talk in the years before school entry. The objective of this study is the writer tries to investigate and identify the phonological system made by children 3 years to 5 years old. The writer use descriptive qualitative analysis in order to figure out and identify the form of phonological and semantic system made by children at the age 3-5 years old. The writer use observation and interview in collecting the data. The research finding in this study were there are omission that can be seen in phonological system on children at the age 3-4 years, the consonant sound of /k/, /t/, /r/, and /s/ and there also replacement sound occurs in pronunciation made by the age 3-4 years such sound letter /c/ with /s/ and letter sound consonant /r/ with /l/. At the age of 5 years, the sound of consonant has been seen more clearly in the pronunciation of words. They have been able to recognize the sound of consonant /k/, /t/, /r/, and /s/. in conclusion, The phonological system made by children 3 years to 5 years old it can be seen from the difficulties of the latter sound; /t/, /d/, /r/, /l/, and the replace of position latter /s/ with /c/ and also the latter /r/ with /l/.
Enabling people to lower barriers with a codesign prototyping approach: sex education for upper-elementary students at home

(2019). Enabling people to lower barriers with a codesign prototyping approach: sex education for upper-elementary students at home. The Design Journal: Vol. 22, Running with Scissors: 13th International Conference of the European Academy of Design, Dundee, 10-12th April, 2019, edited by Louise Valentine, Joanna Bletcher and Leon Cruickshank, pp. 539-551.
Serendipity in the Field. Facilitating serendipity in design-driven field studies on ship bridges

(2019). Serendipity in the Field. Facilitating serendipity in design-driven field studies on ship bridges. The Design Journal: Vol. 22, Running with Scissors: 13th International Conference of the European Academy of Design, Dundee, 10-12th April, 2019, edited by Louise Valentine, Joanna Bletcher and Leon Cruickshank, pp. 1899-1912.
An Introduction to Quantum Computers and Their Effect on Banking Institutions

Quantum computers leverage the incredible and dynamic properties behind quantum physics. In doing so, these computers are able to solve mathematical equations that, as of now, cannot be solved using today’s conventional computers. Realizing the potential that quantum computers represent, banking institutions are beginning to both analyze and apply these computers’ use potential, particularly in increasing the efficiency and speed of complex transactions. Simultaneously, banking institutions must also carefully examine quantum computers’ ability to bolster cybersecurity defenses. In the age of quantum computers, existing defenses will prove inadequate, even to lattice-based cryptography. At the dawn of the quantum age, banking institutions are in a unique position to leverage not only quantum computers’ vast computing power in completing complex transactions, but also to use such computers to counter the threat of quantum cybersecurity threats.
POSITIVE ATTITUDE BUILDOUT AT SECOND GRADERS THROUGH OUTDOOR EDUCATION ACTIVITIES

Outdoor education has come to the point where, besides being a modern teachinglearningmethod, it can easily develop certain competencies if it is done according tostrategical rules. Modern education is based on the development of competencies andthe curriculum motivates the use of activities that can build these in children of anyage. One of the most important parts of a competency is the attitude of pupils towardsoneself, others and learning. This study, presents the theoretical base of attitudes asparts of competencies and how pupils can achieve them through formal education. Italso presents a research amongst a group of second graders from Arad County basedon outdoor learning activities and the multiple ways in which these can developattitudes in the research group. We are going to present the instruments and theresults, which preliminarily show that involving kids in outdoor learning activities cansuccessfully develop positive attitudes towards self, society, the micro group andtowards learning.
Cyber-offenders versus traditional offenders: an empirical comparison

Weulen Kranenbarg, M
Analysis and Design Computerized Semester Exams by Randomization Order of The Questions with Linear Congruential Generator Methods (Study Case : Agathos Vocational High School)

In this modern era, education begin to use more advanced technology in order to ease their activities such as semester exams. By taking advantage of computer technology in education will make semester exams become simpler during the process of the exam and scoring, as in shuffling the order of the question and scoring become faster and more accurate. Currently, Agathos Vocational High School still use manual exam system, and the process cost is high. They have to print out the test and answer paper, undisciplined students can cheating during exam, mistakes during marking the test, and unorganized archives when filing the student’s results. After finding out the current system in Agathos Vocational High School, To solving their current problems is develop a system that will organize the information electronically in filling the student’s grades and making a random order of questions, using Linear Congruential Generator (LCG) method. This computerized system will help the teachers to making the questions with inputting process, and will be done in three days, marking the answers and filling the grade are automatically done by system, then print it out to be Student’s Report. With using LCG method, can motivating the students to study as the order of the question is randomized by Student’s ID Number, the students will not be able to continue filling their answers after the time is up and this will reducing the possibility of cheating. The time needed to prepare exam questions was reduced from 8 days to 1 day. The system test results is 64% can be accepted by the user.