Reviewerly/exHarmony huggingface dataset:
Measuring randomness in IoT products

Choosing and using a random number generator is no simple task. Most random number generators fail statistical tests, revealing patterns in their output. Good generators can lead to disasters if not properly seeded. IoT products may not afford safe random number generators if these products are built on low resource hardware because safety tends to require more resources than not. Testing the chosen random number generator under the conditions of the product is important to know its limitations. We present an easy-to-use tool we have developed to bring the industry's products the state-of-the-art in random number generator testing.
Recommendation Algorithm based on Blending Learning

Recommendation systems in today's world are extremely important for any business and users. Matrix Factorization is extensively researched and widely used for recommendation purposes. But it uses the dot product which does not satisfy the inequality property. Therefore, different techniques are proposed to solve the problem such as Metric Factorization. Although the results of Metric Factorization improved, but there is always welcome for new research work. Therefore we use a multi-model ensemble technique called blending. This Technique consists of two steps. First we train several base models and get the predicted rating of movies, then use a linear regression to combine these results as a second-layer model to get a final rating of movies. The metrics RMSE and MAE are used for evaluation for different models. Our experimental results indicate that new blending approach is superior to other used techniques.
Towards Detecting and Managing Information Anxiety in the ICT Industry

Information Anxiety is defined as "stress caused by the inability to access, understand, or make use of information necessary for employees to do their job".Even though it is in itself an intangible phenomenon, it is widely acknowledged and has been linked to impaired decision-making ability, information withdrawal, information avoidance, burnout and other health issues.The ICT industry is acknowledged to be a fully fledged knowledge industry.That is to say that its workers are mainly tasked with creating, understanding, applying and distributing knowledge as part of their day-to-day job.The industry is also characterised by disruptive innovations, continuously changing technologies and customers who constantly change their mind about what they want systems to do.In this paper, we present the results of a study which tracked 18 participants for a period of one month in order to investigate the presence of information anxiety in the Maltese ICT industry.Our results indicate that information anxiety is present in nontrivial levels amongst our cohort of participants, with information overload being the predominant cause.Also, participants working in a quality assurance (QA) function are more exposed to the phenomenon as well as being exposed to a wider variety of sources of anxiety than developers.Experience is also shown to be a factor with participants being less prone to symptoms of information overload as they gain more experience in the field.
Skew constacyclic codes over the local Frobenius non-chain rings of order 16

We introduce skew constacyclic codes over the local Frobenius non-chain rings of order 16 by defining non-trivial automorphisms on these rings. We study the Gray images of these codes, obtaining a number of binary and quaternary codes with good parameters as images of skew cyclic codes over some of these rings.
HUD Layout Adaptive Method for Fighter Based on Flight Mission

In order to solve the problem of inadequate display of important information in the mission process, which leads to low cognitive of pilots, an HUD layout adaptive method based on flight tasks is proposed in this paper. Specific methods include the following steps: dividing HUD interface according to function; classifying the pilot’s field of view; collecting the pilot’s eye movement data in the task phase and calculating sub-region’s interest value; gridding HUD interface; calculating fitness function; adjusting the layout according to rules, selecting the interface with the largest value as the final HUD output interface. This method can effectively improve pilots’ attention allocation and provide important reference for HUD interface layout.
Probability-based Collision Detection and Resolution of Planned Trajectories for Unmanned Aircraft System Traffic Management

We address the problem of traffic management of an unmanned aircraft system. In an effort to improve the performance with safety, we propose a probability-based collision resolution algorithm. The proposed algorithm analyzes the planned trajectories to calculate their collision probabilities, and modifies individual drone starting times to reduce the probability of collision, while attempting to preserve high performance. Our simulation results demonstrate that the proposed algorithm improves the performance of the drone traffic management by guaranteeing high safety with minimal modification of the starting times.
Cancer Classification using improved Extreme Learning Machine

In recent years there has been explosion in the amount and complexity of micro-array datasets obtained from various biological experiments and many community research. These datasets when utilized efficiently can help in building of complex disease prognosis systems. Efficient and accurate classification model is needed for analysis and interpretation of these datasets. Extreme Learning Machine (ELM) has been catering the attention for training single-layer feed forward network (SLFN) by providing higher performance in terms of fast learning speed and better accuracy. The efficiency of these models are heavily dependent on the selection of network parameters which involves hidden weights and biases. Therefore, many evolutionary algorithms have been used to enhance the performance of ELM. However, these evolutionary approaches are limited to explore the global search space, i.e. diversification. In order to obtain high quality solution, along with diversification searching the local neighbourhood i.e, intensification is required. In the proposed work, a novel method is developed where Jaya optimization algorithm and Simulated Annealing (SA) is together implemented to produce a profitable synergy. Further, adaptive technique is introduced to enhance the search process. Comparison and experiments on five micro-array datasets reveals the robustness of the proposed ELM models. The experimental results demonstrate that the proposed hybridized ELM are better than the original ELM algorithm and other existing state-of-art in terms of accuracy and efficiency.
Researches on the Eye-Movement Mode of Chinese College Students in Reading English Websites

In order to improve the immersion and interest of Chinese college students in English web pages reading, an eye-movement pattern inquiry experiment, which included 30 college student subjects, has been carried out in this research. A civilian eye tracker, Tobii Eye Tracker 4C, is chosen as the interactive device, the gaze time and regression are chosen as eye-movement indicators, and a set of classification models are built based on the differences of eye movements between familiar word reading and unfamiliar word reading. According to the classification models, a browser extension named Chinen Translation is developed, which can translate automatically and timely. In the usability test of Chinen, the prediction ability of the unknown words in the full text of the 30 subjects in the classification model is 96.69% for average, the highest is 99.35%, and the lowest is 93.55%.
Rancang Bangun Aplikasi Pembelajaran 3D Klasifikasi Makhluk Hidup Kingdom Monera dan Protista Berbasis Desktop untuk Siswa Sekolah Menengah Pertama (SMP)

Monera and Protista kingdom are part the part of the classification of living creatures lesson that is biology subject at seventh (VII) grade of Junior High School.Conventional tools or instruments of the learning that are utilized can be some images or animal that preserved (for animalia kingdom).Monera and protista kingdom are micro-creatures which only can be observed with microscopes.However, based on pre-research results, about 54,3% of teachers stated that seventh grade students of Junior High School have not been equipped with the knowledge to use microscopes.So that, some alternative ways are required as learning media which can show micro-creature objects.To facilitate the undertanding of the subject, the
Nonexistence of certain binary and ternary linear complementary dual codes

Linear complementary dual (LCD) codes are linear codes that intersect with their dual trivially. We give a characterization of LCD codes over $\mathbb{F}_q$ having large minimum weights for $q \in \{2,3\}$. Using the characterization, we determine the largest minimum weights among LCD $[n,k]$ codes over $\mathbb{F}_q$ for $(q,k) \in \{(2,4), (3,2),(3,3)\}$. Moreover, we give a complete classification of optimal LCD $[n,k]$ codes over $\mathbb{F}_q$ for $(q,k) \in \{(2,3), (2,4), (3,2),(3,3)\}$.
Development of Media Convertible Book Based on Scientific Approach to Improve the Understanding of Environmental Care Concepts and Characters

The&#x0D; aims of the research are (1) to develop a convertible book based on a&#x0D; scientific approach to improving the conceptual understanding and&#x0D; care-for-environmental character, (2) to reveal the effectiveness of the&#x0D; developed convertible book to improve the conceptual understanding and&#x0D; care-for-environmental character of grade IV students of elementary schools in&#x0D; Moga subdistrict., Pemalang Regency, Indonesian Country. The&#x0D; research uses Research and Development (R&amp;amp;D) model with reference to&#x0D; product development by Borg &amp;amp; Gall. The subject of research are students of&#x0D; elementary schools in Moga subdistrict. The validity of the developed&#x0D; convertible book was analyzed by converting to five quantitative criteria. The&#x0D; effectiveness of the convertible book in improving the conceptual understanding&#x0D; and care-for environmental character was analyzed by N-gain score, t-test, and&#x0D; MANOVA at the significance level of 0.05. The result of the research showed&#x0D; that the develop convertible book fulfilled the feasibility criteria according&#x0D; to the validation by material expert and media expert, teachers' responses and&#x0D; students' response which was in a good of very feasible category. The&#x0D; convertible book was effective to improve the students' conceptual&#x0D; understanding and care-for-environmental character. The result of the t-test at&#x0D; sig. 0.05 showed the effect of the use of the media and test MANOVA there is&#x0D; significant effect between class experiment and class control at 0.00.
Upaya Meningkatkan Hasil Belajar Melalui Penerapan Model Pembelajaran Kooperatif Tipe TGT (Teams Games Tournament) di SMP Negeri 1 Sakra Barat

This study aims to determine whether through the application of the TGT cooperative learning model can improve the learning outcomes of the Human Reproductive System, and also to determine the response of students to the application of cooperative learning learning models. The type of research conducted is PTK with a qualitative approach. Research data in the form of learning outcomes obtained in the study as much as 2 cycles. Data on student learning outcomes are collected from the pre-test and post-test scores given by researchers in each cycle. The results of the study showed that the application of the TGT cooperative learning model could improve the learning outcomes of students in class IX.A SMPN 1 Sakra. This can be seen in the percentage increase in learning outcomes in cycle II is greater than cycle I. The average post-test score of cycle I is 64, while the average post-test score of cycle II is 70. Percentage of increase in mastery learning in cycle I students amounting to 56% while the percentage increase in learning completeness of students in cycle II was 85%.
Penentuan Materi Layanan Bimbingan TIK Menggunakan Algoritma C4.5

Changes in curriculum from KTSP (Education Unit Level Curriculum) to 2013 Curriculum result in changes in Information and Computer Technology (ICT) subjects to ICT Guidance (BTIK). These subjects are not scheduled in general, so students need to be guided by questionnaires. To find out the right guidance needs data mining is needed. So this research is done in determining the accuracy of the guidance needs in accelerating the process of questionnaire data. The method used is C4.5 Algorithm. The results of the study have an accuracy of 90%, so it can be recommended in determining guidance material for students.
BGP Anomaly Prediction Using Ensemble Learning

This paper investigates anomalies such as worms, power outages, and routing table leak (RTL) events occurring in Border Gateway Protocol (BGP) that can cause connectivity and data loss issues.Ensemble learning is a machine learning model employing multiple classifiers in order to reliably identify network anomalies.We use bagging, boosting, and random forests ensemble models trained on network anomaly datasets for classification improvement.Models were compared with respect to the following performance metrics: F-measure, Matthews correlation coefficient (MCC), Receiver operating characteristic (ROC) curve, precision-recall (PR) curves and model execution time.We observed improvement in performance measures when ensemble classifiers realized in Python were used in comparison to our previously reported results on single classifiers.Further improvement in most performance measures was observed by using sampling techniques (oversampling and undersampling) on anomalous datasets.This approach increases model execution time which is not favorable for real-time anomaly detection models.
KAJIAN PSIKOLOGI SASTRA NOVEL BIDADARI BERMATA BENING KARYA HABIBURRAHMAN EL SHIRAZY DAN NILAI PENDIDIKAN KARAKTER TOKOH DALAM PERSPEKTIF PEMBELAJARAN BAHASA INDONESIA

&lt;p&gt;&lt;em&gt;The purpose of this research is to describe and explain: (1) intrinsic element of novel Bidadari Bermata Bening; (2) psychological burden of the main character; (3) character education values; (4) the position of novel Bidadari Eye Bening by Habiburrahman El-Shirazy in Indonesian Language Learning perspective. This research was conducted by qualitative descriptive method and using psychology approach of literature. The results of this study indicate that: (1) each element of the novel has relevance with other elements so as to make the story coherent. (2) psychological analysis for the psychological burden of the main character using Sigmund Freud's theory of analysis which includes the three elements of personality namely id, ego, and superego. (3) the values of character education contained in the novel include religious, honest, tolerance, discipline, hard work, creative, independent, curiosity, respectful achievement, friendly / communicative, peace loving, social caring, and responsibility. (4) novel Bidadari Bermata Bening by Habiburrahman El Shirazy can be used as Learning material of Bahasa Indonesia.&lt;/em&gt;&lt;/p&gt;
Implementation of national cryptocurrency using ethereum development platform

While Ethereum run in public networks which make the blockchain size large and transaction run time longer than time for private or national network, that led to continuous worries over the expanding size of Ethereum Blockchain, which certainly reduce Cryptocurrency's effectiveness. The estimations were on increase and believed it would cross the node limit of 1 TB terribly shortly. If new consumer a full node enters to that blockchain and cryptocurrency world, a node is a computer software cum database of the blockchain, which a full node client must download on their personal computers to become a full node in the blockchain. in this way, the client can be verifying transaction on the network with the help of other nodes on the system. We proposed to implement national cryptocurrency which developed using Ethereum as a development platform that could serve national or regional people that has limited or slow internet connections like Iraq, in addition payments in countries with unstable fiat currencies, although cryptocurrencies are suffering from unstable exchange rates against fiat currencies, the use of national cryptocurrency instead of the native fiat cash could even be a far better alternative for individuals in certain countries like Iraq, Iran and Syria, with high rate of inflation. The reminder of this paper is arranging as following: an introduction, the advantages and drawbacks of cryptocurrencies, Background on Blockchain and Ethereum, implementation, results and conclusion.
3D Color CLUT Compression by Multi-scale Anisotropic Diffusion

3D CLUTs (Color Look Up Tables) are popular digital models used in image and video processing for color grading, simulation of analog films, and more generally for the application of various color transformations. The large size of these models leads to data storage issues when trying to distribute them on a large scale. Here, a highly effective lossy compression technique for 3D CLUTs is proposed. It is based on a multi-scale anisotropic diffusion scheme. Our method exhibits an average compression rate of more than $$99\%$$ , while ensuring visually indistinguishable differences with the application of the original CLUTs.
DIKSI DALAM PUISI KELAS VIII SMP NEGERI 3 SINGOSARI

2) imaji di dalam diksi yang paling menonjol adalah imaji taktil.Imaji visual banyak ditemukan dalam penelitian ini.Imaji auditif tidak begitu tampak dalam penelitian ini.(3) persepsi manusia sebagai dasar pemilihan diksi yang paling banyak adalah persepsi manusia.This study aims to describe (1) diction based on meaning, (2) diction based on images, and (3) perceptions in poetry by students of grade VIII SMPN 3 Singosari.This study uses a qualitative approach with a kind of text or document study research.The data this study is a poem by the class VIII G of Singosari Malang 3 Junior High School.The results showed (1) the diction based on the most prominent meaning was denotative diction.There are also connotative, but not dominant, dictionaries.(2) the image in the most prominent diction is a tactile image.Visual images are found in this study.Auditive images are not so visible in this study.(3) human perception as the basis for selecting the most diction is human perception.
Well Logs Inversion Into Lithology Classes: Comparing Bayesian Inversion and Machine Learning

Summary Lithology classification is a crucial challenge in geological research. Lithologies at thelocations without cores need to be predicted by using indirectly geophysics measurementssuch as well logs and seismic data. In this study, we use the spatial dependency of sedimentsand well logs data for inversion into lithologies by a kernel-based hidden Markov model(HMM) and a gated recurrent unit (GRU) model. We estimate model parameters from twotraining wells and predict lithologies from well log observations for a blind test well. Thepredictions are also compared to results from a deep neural network (DNN) model, whichassumes spatial independence. Results indicate that the lithology predictions supplied by theHMM and GRU models are more reliable than the ones from DNN in term of classificationaccuracy and make more senses in geological interpretation. Moreover, the HMM providesquantifications of the classification uncertainty.
OPEN SCIENCE, KNOWLEDGE SHARING AND REPRODUCIBILITY AS DRIVERS FOR THE ADOPTION OF FOSS4G IN ENVIRONMENTAL RESEARCH

Abstract. Support for open science is a highly relevant user requirement for the environmental data portal EnviDat. EnviDat, the institutional data portal and publication data repository of the Swiss Federal Research Institute WSL, actively implements the FAIR (Findability, Accessibility, Interoperability and Reusability) principles and provides a range of services in the area of research data management. Open science, with its requirements for improved knowledge sharing and reproducibility, is driving the adoption of free and open source software for geospatial (FOSS4G) in academic research. Open source software can play a key role in the proper documentation of data sets, processes and methodologies, because it supports the transparency of methods and the precise documentation of all steps needed to achieve the published results. EnviDat actively supports these activities to enhance its support for open science. With EnviDat, WSL contributes to the ongoing cultural evolution in research towards open science and opportunities for distant collaboration.
Trust in Cyber Security Recommendations

Over the last two decades, the Internet has established itself as part of everyday life. With the recent invention of Social Media, the advent of the Internet of Things as well as trends like "bring your own device" (BYOD), the needs for connectivity rise exponentially and so does the need for proper cyber security. However, human factors research of cyber security in private contexts comprises only a small fraction of the research in the field. In this study, we investigated adoption behaviours and trust in cyber security in private contexts by measuring - among other trust measures - disposition to trust and providing five cyber security scenarios. In each, a person/agent recommends the use of a cyber security tool. Trust is then measured regarding the recommending agent. We compare personal, expert, institutional, and magazine recommendations along with manufacturer information in an exploratory study of sixty participants. We found that personal, expert and institutional recommendations were trusted significantly more than manufacturer information and magazine reports. The highest trust scores were produced by the expert and the personal recommendation scenarios. We argue that technical and professional communicators should aim for cyber security knowledge permeation through personal relations, educating people with high technology self-efficacy beliefs who then disperse the acquired knowledge.
DESIGN AND IMPLEMENTATION OF A SOFTWARE COMPONENT FOR GEOSPATIAL DATA VISUALIZATION IN EXCEL

This paper proposes an architecture for a software component that allow us to display data from an xlsx document in a geospatial context.In order to spatial data manipulation and visualization, it was used specialized libraries as Geopandas and Matplotlib in a user defined Python script.The software component is plugged to Excel application as an Add-in, in this case it can be used in any document is necessary.To emphasize the utility of this component in the end of this paper is presented a case study for displaying the share of urban population for each Romanian county on a map.
Update on geophysical survey progress from Geoscience Australia and the Geological Surveys of Western Australia, South Australia, Northern Territory, Queensland, New South Wales, Victoria and Tasmania (information current on 10 July 2019).

Further information about these surveys is available from Mike Barlow Mike.Barlow@ga.gov.au; (02) 6249 9275 or Laura Gow Laura.Gow@ga.gov.au 02) 6249 9605.Survey nameClientProject managementContrac...
A New Learning Algorithm: SinAdaMax

Artificial Neural Networks are clearly influencing the field of machine learning since the age of the ‘Deep Learning’, roughly starting after the first 10 years of the 21st century. The neural network training success highly depends on the optimizers which modify the network weights, and these learning algorithms affect the success of the training of the networks significantly. In this work, different optimizers are employed in different problems like sentiment analysis and image classification for comparing and figuring out the successful ones. To show the success of the new optimizer SinAdaMax we proposed previously, recurrent and convolutional neural networks on different datasets are used with other well-known learning algorithms in this research.