Reviewerly/exHarmony huggingface dataset:
Efficient Parallel Algorithm for Mining High Utility Patterns Based on Spark

Utility pattern mining is an important data mining technology that can find patterns that are both statistically significant and in accordance with users' expectations and objectives, which emerged recently to address the limitation of frequent pattern mining. To the best of our knowledge, utility pattern mining algorithms proposed so far however are all sequential ones that are inefficient and not scalable when dealing with huge amounts of data. To address the scalability and efficiency challenge, this paper proposes a parallel utility pattern mining algorithm based on Spark, a parallel programming model that uses in-memory storage for data sharing. The contributions include an improved vertical data structure, a three-phase parallel mining framework, and an efficient algorithm. Extensive experiments on both artificial and real-world data show that the proposed parallel algorithm is scalable and efficient.
The role of education in human nature and future human design according to Edgar Morin

Understanding the structure of human nature is an important element in determining educational practices. Recent developments in the field of science, culture and technology today require us to reconsider the developments and changes in human nature. Therefore, while determining the qualifications and principles that should play a role in the education of the future, it is necessary to first evaluate how human that is both the subject and object of education in perceived in the 21st century. While all the disciplines are essentially examining human being from different perspectives and trying to understand its nature, Edgar Morin, a contemporary philosopher and sociologist, considers the issue from a different perspective and thinks that the reality of human nature can be reached only when the disciplines are considered as a whole. Morin, who thinks that uncertainties will be clarified with an integrated education, has suggestions for the education of the future.&#x0D; Keywords: Edgar Morin, philosophy of education, education of future, human nature.
PEMANFAATAN DATAMINING PADA PENGELOMPOKAN PROVINSI TERHADAP PENCEMARAN LINGKUNGAN HIDUP

This research aims to provide input for the government so that it can immediately tackle water pollution given the many adverse effects that lurk in various aspects of life. The method used in this study researchers used the method of K-means clustering datamining algorithm. The data used in this study are the number of villages according to the type of environmental pollution in 2018 which consists of 34 provinces in Indonesia obtained through the official website of the Directorate of Statistics Indonesia. The variable used is water pollution. The variable used is water pollution. Data is grouped into 2 clusters, namely provinces that have high levels of water pollution (C1) and provinces that have low levels of water pollution (C2). K-Means Clustering algorithm in this study produces 2 iterations, so the final result is: high water pollution (C1) in the provinces of North Sumatra, West Java, Central Java, East Java, for low level water pollution (C2) is in provinces of Aceh, West Sumatra, Riau, Jambi, South Sumatra, Bengkulu, Lampung, Kep.Bangka Belitung, Kep.Riau, DKI Jakarta, DI Yogyakarta, Banten, Bali, West Nusa Tenggara, East Nusa Tenggara, West Kalimantan, Central Kalimantan, South Kalimantan, East Kalimantan, North Kalimantan, North Sulawesi, Central Sulawesi, South Sulawesi, Southeast Sulawesi, Gorontalo, West Sulawesi, Maluku, North Maluku, West Papua, Papua.Keywords:Datamining, Clustering, K-means , Water pollution
Impact of Institutional Quality on Educational Attainment: The Case of Low-Income SSA Countries

Education produces many social, political and economic outcomes including improved cognitive competences, higher wages, better health and enhanced economic status. Nations ensure the development of their population by the use of educational intervention. Despite the documented empirical correlations of education attained, there have been scanty researches exploring the impact of institutional quality in low-income SSA countries. The problem facing SSA can be ascertained in the area of weak institutions which leads to poor level of educational attainment and low level of life expectancy which have become the focus of the development agenda in the world as a whole and developing countries in general. The objective of this study is to evaluate the relationship between institutional quality and educational attainment in low-income SSA countries from 2005 to 2013. The research used secondary data sourced from World Bank governance indicators, Transparency International and Heritage Foundation. The analysis was divided into panel data using the fixed effects method (FEM) and generalized method of moments (GMM). Both the panel data analysis and the generalized method of moments of institutional quality and educational attainment indicated that most of the countries investigated exhibits mixed performance in institutional quality. The study recommends policies to reduce corruption in all levels of economic activities. In addition, rule of law need to be strengthened and the educational sector should be refined to train manpower in all aspect of human activities in the region especially the low-income countries in SSA countries.
A Key-Ordered Decisional Learning Parity with Noise (DLPN) Scheme for Public Key Encryption Scheme in Cloud Computing

The variation of decisional learning parity with noise (DLPN) named as key-Ordered DLPN based security algorithm is presented in this work.The proposed scheme uses DLPN by extending it to an even-odd-order scheme, depend on the value of probability distribution of odd and even bits for encryption, where odd and even bits are the input integer values for key generation algorithm.This states that the probability distribution of odd and even bits are ordered based on the key generation, the process of odd and even bits resolving is the solution of DLPN attacker problems, thus, the proposed scheme provides more correctness and security proof.Through the learning parity with noise (LPN), DLPN and RSA algorithms, the proposed system is evaluated, to measure the encryption time, public key and ciphertext bits.
Human-Dimensionality and Values of Higher Education: Strategies for the Future of Complexity and Sustainable Development

The article is dedicated to the philosophical consideration of higher education and its development strategies under the situation of complexity and the need to enable a sustainable future. It is argued that the situation in question is characterized by the uselessness of any ready-made solutions and even pre-available knowledge and methodology. In the very field of professional activities, the competence of a specialist relies not so on vocational skills as on one’s critical thinking and creative abilities. It is concluded then that answering the calls of today’s global crisis requires higher education to face the transformation of its system of goals and values in order to enable the achievement of not just purely professional development of a graduate, but that of overall cultural background, the development of one’s personality. That still corresponds with the classical notion of the mission of university, but not with the linear methodology of the Modernity age aimed at standardization and unification that features mostly excessively mechanistic approach to the educational process, while accentuating applied professional competencies and neglecting the profound core, the ideal of the all-around developed human person. The author argues that such a task could be realized basing on the methodology peculiar to the post-non-classical type of scientific rationality that is oriented on human personality and his or her values. That feature could be called human-dimensionality: the appeal towards unique personalities of each student, as opposed to standardization, and with not only one’s mind and reason taken into account in higher education, but one’s will and emotions as well. The closeness between values of higher education and the ethos of science is demonstrated, with the growing numbers of students violating the norms of academic integrity serving as an example of a disastrous effect of the lack of general culture for professional activities. The role of philosophy and humanities in higher education is said to be rehabilitated and renovated.
Analysis of Printed Circuit Boards strains using finite element analysis and digital image correlation

This paper investigates the use of digital image correlation (DIC) and finite element analysis for strain measurement on Printed Board Circuits (PCBs). Circuit boards (PCBs) are designed to mechanically support and electrically connect an electronic component assembly. Due to screw assemblies, the surface level differences on which the PCB is placed, the process of assembling the electronic components induces a certain state of stress and deformation in the PCB. The main components affected are microprocessors due to the way they are glued to PCBs with BGA - Ball grid arrays (BGA). Digital Image Correlation (DIC) is a full-field contactless optical method for measuring displacements and strain in experimental testing, based on the correlation of images taken during test. The experimental setup is realized with Dantec Q-400 system used for image capture and Istra 4D software for image correlations and data analyses. The maximum level of the obtained strain is compared with the allowable limit. Finite element analysis (FEA) is a numerical method of analysis for stresses and strain in structures of any given geometry.
Modelling and Simulation of DC Motor Speed Control Using Fuzzy-PID Algorithm

&lt;p class="Abstract"&gt;This paper discusses the simulation of the Fuzzy-PID hybrid algorithm as a method for controlling the speed of a DC motor compared to the usual PID method. Comparisons were also made to the membership functions used in the fuzzy logic fuzzification process. Membership functions that are used are triangular, trapezoidal, and gaussian shaped function with each having 3, 5, and 7 as the number of membership to be compared. The performance of this control is compared by looking at the results of the step unit responses and the ability in tracking signals. The simulation results show that the Fuzzy-PID algorithm is superior to the ordinary PID algorithm but slower on computation time. The results of the comparison in the fuzzification process shows that the more number used in membership function, the faster the response reaches the set point, while the difference in shape has little effect on the response. The best results are achieved by fuzzy triangle shaped function with 7 membership number.&lt;/p&gt;
Reinforcement Learning with an Extended Classifier System in Zero-sum Markov Games

A reinforcement learning (RL) agent can learn how to win against an opponent agent in zero-sum Markov Games after episodes of training. However, it is still challenging for the RL agent to acquire the optimal policy if the opponent agent is also able to learn concurrently. In this paper, we propose a new RL algorithm based on the eXtended Classifier System (XCS) that maintains a population of competing rules for action selection and uses the genetic algorithm (GA) to evolve the rules for searching the optimal policy. The RL agent can learn from scratch by observing the behaviors of the opponent agent without making any assumptions about the policy of the RL agent or the opponent agent. In addition, we use eligibility trace to further speed up the learning process. We demonstrate the performance of the proposed algorithm by comparing it with several benchmark algorithms in an adversarial soccer game against the same deterministic policy learner.
Are the open-ended rules for negation categorical?

Vann McGee has recently argued that Belnap's criteria constrain the formal rules of classical natural deduction to uniquely determine the semantic values of the propositional logical connectives and quantifiers if the rules are taken to be open-ended, i.e., if they are truth-preserving within any mathematically possible extension of the original language. The main assumption of his argument is that for any class of models there is a mathematically possible language in which there is a sentence true in just those models. I show that this assumption does not hold for the class of models of classical propositional logic. In particular, I show that the existence of non-normal models for negation undermines McGee's argument.
Pengaruh Model Pembelajaran Kooperatif Tipe Index Card Match terhadap Hasil Belajar Matematika Siswa

Abstract:Learning will be more meaningful if students are given the opportunity to participate in various learning activities, students can actualize their abilities inside and outside the classroom. Choosing the right learning model can create an atmosphere fun and impact on student activities and learning outcomes. The Index Card Match type cooperative learning model is to find pairs of cards that are quite fun to use to exercises about the material that has been given. The purpose of this study is to determine whether there is influence of cooperative learning model index card match type on student learning outcomes. The research method uses pre-experimental designs with one-group pretest-posttest design models. Technical analysis using hypothesis testing, namely the t-test and correlation, the requirement to do the t-test is to do a normality test. The results of data analysis showed that there was the influence of the Index Card Match type of cooperative learning model on the mathematics learning outcomes of eighth grade students of Sumobito State Junior High School 2. SPSS calculation states that the value of r count = 0.709, which is located between 0.600 &lt;r≤0.800 which means that it is in the high criteria. Abstrak:Belajar lebih bermakna apabila siswa diberi kesempatan berpartisipasi dalam kegiatan belajar, mengaktualisasikan kemampuan mereka di dalam dan di luar kelas. Memilih model pembelajaran yang tepat dapat menciptakan suasana yang menyenangkan dan berdampak pada kegiatan siswa dan hasil belajar. Model pembelajaran kooperatif tipe Index Card Match menyenangkan digunakan untuk mengulang materi yang telah diberikan. Penelitian ini bertujuan untuk mengetahui pengaruh Index Card Match terhadap hasil belajar siswa. Metode penelitian menggunakan desain pra-eksperimental dengan model desain pretest-posttest satu kelompok. Uji hipotesis dilakukan dengan uji-t dan korelasi. Hasil analisis data diperoleh terdapat pengaruh tipe Index Card Match terhadap hasil belajar matematika siswa. Perhitungan SPSS menyatakan bahwa nilai r hitung = 0,709, yang terletak di antara 0,600 &lt;r≤0.800 yang berarti berada dalam kriteria tinggi.
Rotated Z^n-Lattices via Real Subfields of Q(\zeta_2r)

A method for constructing rotated Z^n-lattices, with n a power of 2, based on totally real subfields of the cyclotomic field Q(\zeta_{2^r}), where r\geq 4 is an integer, is presented. Lattices exhibiting full diversity in some dimensions n not previously addressed are obtained.
Efficient and secure real-time mobile robots cooperation using visual servoing

This paper deals with the challenging problem of navigation in formation of mobiles robots fleet. For that purpose, a secure approach is used based on visual servoing to control velocities (linear and angular) of the multiple robots. To construct our system, we develop the interaction matrix which combines the moments in the image with robots velocities and we estimate the depth between each robot and the targeted object. This is done without any communication between the robots which eliminate the problem of the influence of each robot errors on the whole. For a successful visual servoing, we propose a powerful mechanism to execute safely the robots navigation, exploiting a robot accident reporting system using raspberry Pi3. In addition, in case of problem, a robot accident detection reporting system testbed is used to send an accident notification, in the form of a specifical message. Experimental results are presented using nonholonomic mobiles robots with on-board real time cameras, to show the effectiveness of the proposed method.
A similarity measure method fusing deep feature for mammogram retrieval

BACKGROUND:Breast cancer is one of the most important malignant tumors among women causing a serious impact on women’s lives and mammography is one the most important methods for breast examination. When diagnosing the breast disease, radiologists sometimes may consult some previous diagnosis cases as a reference. But there are many previous cases and it is important to find which cases are the similar cases, which is a big project costing lots of time. Medical image retrieval can provide objective reference information for doctors to diagnose disease. The method of fusing deep features can improve the retrieval accuracy, which solves the “semantic gap” problem caused by only using content features and location features. METHODS:A similarity measure method combining deep feature for mammogram retrieval is proposed in this paper. First, the images are pre-processed to extract the low-level features, including content features and location features. Before extracting location features, registration with the standard image is performed. Then, the Convolutional Neural Network, the Stacked Auto-encoder Network, and the Deep Belief Network are built to extract the deep features, which are regarded as high-level features. Next, content similarity and deep similarity are calculated separately using the Euclidean distance between the query image and the dataset images. The location similarity is obtained by calculating the ratio of intersection to union of the mass regions. Finally, content similarity, location similarity, and deep similarity are fused to form the image fusion similarity. According to the similarity, the specified number of the most similar images can be returned. RESULTS:In the experiment, 740 MLO mammograms are used, which are from women in Northeast China. The content similarity, location similarity, and deep similarity are fused by different weight coefficients. When only considering low-level features, the results are better with fusing 60% content feature similarity and 40% lesion location feature similarity. On this basis, CNN deep similarity, DBN deep similarity, and SAE deep similarity are fused separately. The experiments show that when fusing 60% DBN deep feature similarity and 40% low-level feature similarity, the results have obvious advantages. At this time, the precision is 0.745, recall is 0.850, comprehensive evaluation index is 0.794. CONCLUSIONS:We propose a similarity measure method fusing deep feature, content feature, and location feature. The retrieval results show that the precision and recall of this method have obvious advantage, compared with the content-based image retrieval and location-based image retrieval.
Incorporating Textual Evidence in Visual Storytelling

Previous work on visual storytelling mainly focused on exploring image sequence as evidence for storytelling and neglected textual evidence for guiding story generation.Motivated by human storytelling process which recalls stories for familiar images, we exploit textual evidence from similar images to help generate coherent and meaningful stories.To pick the images which may provide textual experience, we propose a two-step ranking method based on image object recognition techniques.To utilize textual information, we design an extended Seq2Seq model with two-channel encoder and attention.Experiments on the VIST dataset show that our method outperforms state-of-the-art baseline models without heavy engineering.
ANALISIS PERFORMA KRIPTOGRAFI HYBRID ALGORITMA BLOWFISH DAN ALGORITMA RSA

Abstract:Computer data security relies on preventing data theft from irresponsible parties by using cryptography method. Some cryptography algorithms have good and poor performance in encrypting and decrypting data depending on the key types. Therefore the purpose of this research is to measure the performance of the hybrid algorithm, consisting a symmetric keyBlowfish algorithm and an asymmetric key RSA algorithm, in encrypting and decrypting multiple types of data such as documents, photos, audios, and videos. The result is the performance of the hybrid algorithm is almost on par with Blowfish and provides a more secure data encryption and decryption by taking advantage of RSA algorithm. The average encryption performance of hybrid algorithm is 0.85s on document, 1.06s on photo, 3.38s on audio, and 15.56s on video. While the average decryption performance of hybrid algorithm is 1.01s on document, 1.38s on photo, 4.3s on audio, and 27.56s on video. Keywords:Hybrid cryptography, Data security, Performance, Blowfish, RSA Abstrak:Keamanan data komputer berhubungan dengan pencegahan dari pencurian data oleh pihak yang tidak bertanggung jawab, salah satu cara pengamanan data komputer yaitu dengan teknik kriptografi. Beberapa metode kriptografi memiliki performa yang baik dan buruk tergantung dengan tipe kuncinya. Maka dari itu, tujuan dari penelitian ini adalah mengukur tingkat kecepatan kriptografi hybrid, terdiri dari algoritma simetris Blowfish dan algoritma asimetris RSA, dengan beberapa tipe data seperti dokumen, foto, audio dan video. Hasil dari penelitian ini adalah algoritma hybrid memiliki performa yang tidak jauh berbeda dari algoritma Blowfish dan membuat proses enkripsi dan dekripsi data lebih aman dengan keunggulan dari algoritma RSA. Rata-rata kecepatan enkripsi algoritma hybrid untuk dokumen 0,85 detik, gambar 1,06 detik, audio 3,38 detik, dan video 15,56 detik. Sedangkan rata-rata kecepatan dekripsi algoritma hybrid untuk dokumen 1,01 detik, gambar 1,38 detik, audio 4,3 detik, dan video 27,56 detik. Kata kunci:Kriptografihybrid, Keamanan data, Performa, Blowfish, RSA
Design and Implementation of Anti-theft System for ATM Machine using Internet of Things (IoT)

Automated Teller Machines (ATMs) security is the branch of knowledge which focuses on the solutions that delivers various points of protection versus physical and electronic snatch from ATMs and preserve their installations. From the anti fraud secure systems to silent designate systems, integrated ATM video monitoring cameras and ATM monitoring alternative, security authority are always ready to help the people to provide more ATM security and aims high for ATM loss prevention systems. The implementation of the system is achieved with the use of Machine-to-machine (M2M) technology. M2M communications is a topic that has newly attracted much curiosity. It yield real-time monitoring and control without the need for human involvement. The objective of M2M platform advises new system architecture for positioning and monitoring applications with wider scope and higher communication ability. The aim of the proposed work is to implement a low cost stand-alone system based on ESP8266 low cost Wi-Fi enabled chip and Cloud Computing. System offers a robust networking solution with huge span of application areas over internet. The various sensors like vibration, Temperature, accelerometer and sound are used in the system. The setup is proposed for ATM security, comprising of the modules namely, Controlling of shutter lock, web enabled control, sensors and siren control