Reviewerly/exHarmony huggingface dataset:
An integrated approach for mining closed and generator high utility itemsets

High Utility Itemset Mining (HUIM) is playing an important role in extracting meaningful knowledge that is profitable itemsets rather than their occurrence frequency. HUIM result thrives into a huge number of utility itemsets that makes it difficult in decision policy. The alternative procedure is condensed representation of HUI’s that contains utility itemsets without any redundancy. Closed High Utility Itemsets (CHUI) and High Utility Generators (HUG) are lossless utility itemsets useful in recommendation systems. In this paper, we address how to extract Closed and Generator HUI’s from the given dataset. For faster accessing, it is proposed hash based technique that store itemsets with the frequency, utility value, closed flag, and generator flag. Experimental results shows that it outperforms other approaches in time and space.
Tolerance Zone-Based Grouping Method for Online Multiple Overtracing Freehand Sketches

Multiple overtracing strokes are common drawing behaviors in freehand sketching; that is, additional strokes are often drawn repeatedly over the existing ones to add more details. This paper proposes a method based on stroke-tolerance zones to group multiple overtraced strokes which are drawn to express a 2D primitive, aiming to convert online freehand sketches into 2D line drawings, which is a base for further 3D reconstruction. Firstly, after the user inputs a new stroke, a tolerance zone around the stroke is constructed by reference to its polygonal approximation points obtained from the stroke preprocessing. Then, the input strokes are divided into stroke groups, each representing a primitive through the stroke grouping process based on the overtraced ratio of two strokes. At last, each stroke group is fitted into one or more 2D geometric primitives including line segments, polylines, ellipses, and arcs. The proposed method groups two strokes together based on their screen-space proximity directly instead of classifying and fitting them firstly, so that it can group strokes of arbitrary shapes. A sketch-recognition prototype system has been implemented to test the effectiveness of the proposed method. The results showed that the proposed method could support online multiple overtracing freehand sketching with no limitation on drawing sequence, but it only deals with strokes with relatively high overtraced ratio.
External Debt, Investment and Economic Performance in Sub-Saharan Africa

Background and Objective: External debt has been identified as a key source of finance for many countries in sub-Saharan Africa (SSA) due to inadequate funds from other sources.Many countries relied on external debt to finance their investment with the expectation of spurring economic growth.Therefore, this study investigates the effect of external debt and investment on economic performance.Materials and Methods: The study utilized a panel of 26 sub-Saharan Africa (SSA) countries between 1999 and 2014 using system General Method of Moments (GMM).Results: The estimated results showed that the growth effect of external debt is negative while positive for investment.Also, the result of the interaction between external debt and investment is negative.The growth effect of inflation is negative while that of trade openness is positive.In addition, the growth effects of the interactions are positive and statistically significant for inflation and external debt, trade openness and external debt and crisis and external debt.More so, the non-linear effect of external debt is positive.Conclusion: This study, therefore, concludes that inflation, financial crisis and the interaction between external debt and financial crisis negatively influenced growth while the impact of trade openness is equivocal.The impact of the interaction between external debt and inflation on economic growth is positive.It is recommended that countries should monitor their debt level when raising funds for investment to prevent debt crisis in the future.In addition, the efficient use of the resources from external debt is very important for the countries in SSA to prevent crowding out effect.Given the unstable nature of global economy, there is need for countries to create economic resilience for the external debt to foster investment and economic performance in the sub-Saharan African countries.The SSA countries is encouraged to work towards these recommendations to promote investment expansion and better economic performance.
Implementasi Metode Caesar Cipher dalam Penerapan Sistem E-Voting Berbasis Web pada Pemilihan Abang None Jakarta

In this increasingly modern era, technology has become a must in improving performance in every organization and various other activities. One example of the application of technology that will be explained in this research is the design of a web-based e-voting system in the election of Abang None Jakarta by inserting an E-KTP numbers to be able to cast a vote in the election. Previously, the selection of Abang None Jakarta still uses SMS voting system that is considered to be less effective because the use of credits is considered more wasteful than the use of internet quota. In developing this web-based e-voting system, the researcher uses the SDLC (System Development Life Cycle) method and the Caesar Cipher algorithm method for voter data security. Besides that, the Gateaway SMS system is used to prevent any voter who uses someone else's E-KTP before casting a vote in an election. The e-voting system is made using the PHP and Xampp programming languages as its database. The e-voting system is expected to be used in making a transparent decision, speeding up the voting counting process, saving costs and preventing fraud when implementing e-voting in the election of Abang None Jakarta. The results of research is proven successful in terms of both the use of the web to conduct the election and the use of security in encryption and decryption of user data.
Information Fusion in Offspring Generation: A Case Study in Gene Expression Programming

Gene expression programming (GEP), which is a variant of genetic programming (GP) with a fixed-length linear model, has been applied in many domains. Typically, GEP uses genetic operators to generate offspring. In recent years, the estimation of distribution algorithm (EDA) has also been proven to be efficient for offspring generation. Genetic operators such as crossover and mutation generate offspring from an implicit model by using the individual information. By contrast, EDA operators generate offspring from an explicit model by using the population distribution information. Since both the individual and population distribution information are useful in offspring generation, it is natural to hybrid EDA and genetic operators to improve the search efficiency. To this end, we propose a hybrid offspring generation strategy for GEP by using a univariate categorical distribution based EDA operator and its original genetic operators. To evaluate the performance of the new hybrid algorithm, we apply the algorithm to ten regression tasks using various parameters and strategies. The experimental results demonstrate that the new algorithm is a promising approach for solving regression problems efficiently. The GEP with hybrid operators outperforms the original GEP that uses genetic operators on eight out of ten benchmark datasets.
Improved Impossible Polytopic Attacks on Round-reduced DES

Abstract In Eurocrypt 2016, Tyge Tiessen introduced the d -difference which considering the differences between multiple plaintexts, and proposed the impossible polytopic attack on block cipher which effectively reducing the data complexity. In this paper, we improve the impossible polytopic attacks of round-reduced DES by some ideas like truncated differentials. Given the input 3-difference of each S-box in the third round, the number of the output 3-difference is actually smaller than the theoretical upper bound, which helps us reduce the memory complexity of the attack on 5-round DES from 2 12 bytes to 2 6.9 bytes and increase the success rate of the attack. Using the idea of truncated differentials, the time complexity of the attack on 6-round DES is reduced from 2 32.2 encryptions to 2 25.8 encryptions by selecting the output 3-differences of 6 S-boxes for key recovery. We also improve the attack on 7-round DES by using more plaintexts based on our improved attack on 6-round DES.
Kernel Principal Component Analysis Allowing Sparse Representation and Sample Selection

Kernel principal component analysis (KPCA) is a kernelized version of principal component analysis (PCA). A kernel principal component is a superposition of kernel functions. Due to the number of kernel functions equals the number of samples, each component is not a sparse representation. Our purpose is to sparsify coefficients expressing in linear combination of kernel functions, two types of sparse kernel principal component are proposed in this paper. The method for solving sparse problem comprises two steps: (a) we start with the Pythagorean theorem and derive an explicit regression expression of KPCA and (b) two types of regularization $l_1$-norm or $l_{2,1}$-norm are added into the regression expression in order to obtain two different sparsity form, respectively. As the proposed objective function is different from elastic net-based sparse PCA (SPCA), the SPCA method cannot be directly applied to the proposed cost function. We show that the sparse representations are obtained in its iterative optimization by conducting an alternating direction method of multipliers. Experiments on toy examples and real data confirm the performance and effectiveness of the proposed method.
AsyncQVI: Asynchronous-Parallel Q-Value Iteration for Discounted Markov Decision Processes with Near-Optimal Sample Complexity

In this paper, we propose AsyncQVI, an asynchronous-parallel Q-value iteration for discounted Markov decision processes whose transition and reward can only be sampled through a generative model. Given such a problem with $|\mathcal{S}|$ states, $|\mathcal{A}|$ actions, and a discounted factor $\gamma\in(0,1)$, AsyncQVI uses memory of size $\mathcal{O}(|\mathcal{S}|)$ and returns an $\varepsilon$-optimal policy with probability at least $1-\delta$ using $$\tilde{\mathcal{O}}\big(\frac{|\mathcal{S}||\mathcal{A}|}{(1-\gamma)^5\varepsilon^2}\log(\frac{1}{\delta})\big)$$ samples. AsyncQVI is also the first asynchronous-parallel algorithm for discounted Markov decision processes that has a sample complexity, which nearly matches the theoretical lower bound. The relatively low memory footprint and parallel ability make AsyncQVI suitable for large-scale applications. In numerical tests, we compare AsyncQVI with four sample-based value iteration methods. The results show that our algorithm is highly efficient and achieves linear parallel speedup.
The analysis service implementation by the apotheker in private apotek in padang city online based in 2019

Apotheker or pharmacist is one of the health providers who give conseling services. Preliminary studies conducted on 33 private Apotek in Padang, pharmacists who come every day only 3 from 33 Apotek. Conseling is no perfect.It is need inovation to give conselling. . Type of reserch mix quantitatiff and qualitatif . Research was carried out in 33 private apotek in Padang City. The technique of determining informants used purposive sampling and data collection using in-depth interviews and observations.The results showed that pharmacy services had not been implemented properly. Apotheker who came once a week as many as 14 out of 33 pharmacies, 2 times a week 10 out of 33 pharmacies, 1 time a months 6 of 33 pharmacies. The percentage of conseling the attendance of pharmacists is mostly 18,2 % who only attend once a month , and only 42 % attend 4 times a month. Only 9% attend every day to provide pharmacy counseling services perfectly. The results of this study indicate that the pharmacist's task has not been carried out in accordance with its function as a counselor. It is expected that by using online media the pharmacist is can still serve patients in providing counselling.
Study on Effectiveness of Classroom Interaction

The classroom interaction is an efficient way to improve the efficiency of classroom learning.Besides the increase in the amount of classroom interaction, the quality of it also requires the attention, which will decide the effectiveness of classroom interaction.The improvement and insurance of classroom interaction are studied from the perspective of form, approach and the role of teacher and students.
Performance of complete blood count (CBC) upon use of different anticoagulants in rats

Complete blood count (CBC) is used as an index of health status of human and different animals as well as to diagnose a variety of diseases. Therefore, there is a growing need of using the most suitable anticoagulant to obtain the most appropriate hemogram. The present study was designed to assess the effect of different anticoagulants viz. Heparin, Sodium Citrate and EDTA on complete blood count (CBC) in rat with a view to choosing the best suitable candidate among the common anticoagulants. A total of 30 samples out of which 10 were for each type anticoagulant were collected from 10 apparently healthy rats of Long Evans strain. From each rat 6 ml of blood was drawn and subsequently divided into three different test tubes with three different anticoagulants. The samples were analyzed for their complete blood count (TEC, TLC, Hb, Hct, DLC, absolute leukocyte count, Red Cell Indices, RDW-SD, RDWCV, Platelet, MPV, PCT and PDW) using Sysmex XT-1800i Auto hematological analyzer. Results showed a significant (p&lt;0.05) decrease in TLC, absolute neutrophil, and platelet count, and a significant (p&lt;0.05) higher level of relative lymphocyte count in Sodium Citrate treated sample than with Heparin and EDTA. No significant changes were observed for RBC or erythrocyte indices among the three different groups. It can be concluded that samples treated with Sodium Citrate results in significant change in blood parameters. Therefore, it is better to use Heparin and EDTA than Sodium Citrate for complete blood count (CBC).&#x0D; Asian J. Med. Biol. Res. March 2020, 6(1): 16-21
Design and Implementation of Intelligent Wheelchair System Based on EEG Control

In order to improve the self-care ability of disabled people, this paper designs and implements an intelligent wheelchair system based on EEG control.The human EEG signal collected by the sensor is sent to the core control board through Bluetooth device.And the wavelet packet transform is used for noise reduction and feature extraction.Then the multi-class SVM technology is used to recognize the EEG signal and realize the intelligent control of the wheelchair in various motion states.In the experiment, the average Kappa coefficient reach 0.622, which is better than BP neural network.Moreover, the system has short response time and high recognition rate, which further showing the effectiveness and reliability of the proposed method.
GREETING AND LEAVE TAKING AMONG NATIVE SASAK IN LOMBOK

Greetings and leave-takings are conversational routine used to maintain person’s relationship in society. However, each culture may have different ways of expressing them. In English, the common greetings and leave-takings pattern used are time-free and time-bound greeting expressed by good afternoon, good evening, good night, nice to meet you and so forth. These are not found in Sasak, so they may cause problem for native Sasak speaker to understand another culture greetings and leave takings; conversely for non-native Sasak speaker who intends to learn them as well. The aim of this study is to find out the forms of greeting and leave taking that appear in Sasak. This study uses ethnography design. To collect the data, observation sheet is utilized. Then, using Haliday’s theory of time-free and time-bound greeting, the data is analyzed by comparing and contrasting greeting and leave-taking patterns used in English and Sasak. The result of the study indicates that Sasak types of greeting and leave taking consist of time-free and time-bound greeting. However, these forms are not exactly the same with common English greeting and leave-taking, they tend to be more phatic utterance (speech act which function to show solidarity and empathy). Therefore, the English curriculum linked with greeting and leave-taking material needs to be associated with Sasak greeting and leave-taking forms in order to create students’ better understanding.
Double Cross &amp; Deep Network for News Recommendation

News recommendation algorithms are widely used in many Internet products that people use.With the increase of commercial value, the research on various recommendation algorithms has become more and more interesting.This paper proposes the Double Cross & Deep Network (DCDN) algorithm, which is used in news recommendation.On the basis of the DCN network, the features of "relevant articles" involved in the field of news recommendation are separately extracted, and high-level intersections are made with user information and seed information, respectively.The parameters of the two Cross Network and Deep Network of the DCDN network are independent, and users can change the parameters according to the predicted demand.When the number of layers of the Cross Network is increased, the relevance of the recommendation can be increased, while the equivalent number of layers of the Deep Network can increase the diversity of recommendations.Experiments show that compared with DCN networks, DCDN networks have better parameter performance and faster model operation.
XRD Analysis in Gundar River Estuary and Beach Sediments of Mookaiyur Area, Ramanathapuram District, South India

Quantitative analysis was carried out to determine the major and minor constituent minerals present in sediment samples collected at the coastal region between in Mandapam and Vembar, Gulf of Mannar coast, South India by XRD technique.The grain-size distributions of sediments are studied in the study of grain size in relation to mechanism of sediments deposition.The composition of the coastal sediment is dominated by medium to fine sand.The distribution pattern and textural parameters of sediments vary regionally in the Ramanathapuram coastal sediment distribution.Based on the texture of sediments it can be said that the beach consists of medium to fine sand was domains.Sedimentological studies reveal that depositional patterns in the beach are mostly controlled by fluvial and marine processes.The deposition of medium to fine sands in the extreme in our study area attributed to the discharge Vembar and Gundar Rivers.Further, the representative sediment samples were analyzed by XRD technique to yield more information about the minerals.X-ray diffraction methods were non-destructive and can be used in the identification of mineralogical composition.These results confirmed that the applied techniques are relatively quicker and more reliable in mineral analysis.The X-Ray diffraction sediments sample analysis proved that the minerals of calcite, quartz, orthoclase, microcline, biotite, hypersthene, hornblende, albite, anorthite sepiolite, illite, chlorite, halloysite Montmorillonite, halite and heavy mineral garnet,
PENENTUAN FAKTOR-FAKTOR YANG MEMPENGARUHI INTENSITAS CURAH HUJAN DENGAN ANALISIS DISKRIMINAN GANDA DAN REGRESI LOGISTIK MULTINOMIAL (Studi Kasus: Data Curah Hujan Kota Semarang dari Stasiun Meteorologi Maritim Tanjung Emas Periode Oktober 2018 – Maret 2019)

Meteorologist develop rainfall forecasting methods to obtain better and more accurate rainfall information. One of them is the research of grid data and the method of grouping rainfall. According to BMKG, rainfall is classified into light, medium, and heavy rain. This study aims to determine the factors that influencing rainfall grouping using multiple discriminant analysis with a stepwise selection method. This study uses the daily climate data of Semarang City for period of October 2018 to March 2019. Based on its partial F value, the wind speed variable is eliminated so the significant variable on rainfall grouping are air temperature, air humidity, and wind direction. This analysis produces discriminant scores obtained from linear combinations between discriminant weights and observation values of significant independent variable. The classification procedure is based on the discriminant score each observations compared to cutting score resulted in classification accuracy of 62.89%. Multinomial logistic regression analysis is used to determine the effect of independent variables on rainfall intensity using the odds ratio. This analysis produces an estimate of the conditional probability of each group using significant independent variables are air temperature, air humidity, wind speed, and wind direction. The classification procedure is based on the largest conditional probability value between rainfall groups resulted in classification accuracy of 69.80%. Keywords: multiple discriminant analysis, multinomial logistic regresion, classification accuracy, rainfall
The Cluster Crossover Operation for The Symmetric Travelling Salesman Problem

This paper proposed the new algorithm intended to solve a specific real-world problem, the symmetric travelling salesman problem. The proposed algorithm is based on the concept of the galaxy based search algorithm (GbSA) and embedded the new ideas called the clockwise search process and the cluster crossover operation. In the first step, the nearest neighbor algorithm introduces to generate the initial population. Then, the tabu list local search is employed to search for the new solution in surrounding areas of the initial population in the second step. The clockwise search process and the cluster crossover operation are employed to create more diversity of the new solution. Then, the final step, the hill climbing local search is utilized to increase the local search capabilities. The experiments with the standard benchmark test sets show that the proposed algorithm can be found the best average percentage deviation from the lower bound.
Research on the SLAM of Mobile Robot Based on Particle Filter Method

This paper mainly studies mobile robots under ROS (Robot Operating System), combined with lidar and odometer information collection, to solve the indoor robot SLAM (Simul-taneous Localization and Mapping) and path planning technology problems. For this problem, this paper solves this problem based on ROS and mobile robot. In order to improve the computational efficiency and positioning accuracy of the robot in SLAM, SALM algorithm based on particle filter is adopted in this paper to complete the positioning and map creation functions of the robot in the unknown environment. At the same time, the path planning algorithm provided by ROS navigation function package is used to complete the navigation of the robot in the global map of the known environment, and the obstacle avoidance function of local map. The experimental results show that this technology can construct high-precision two-dimensional grid map and realize high-precision positioning and optimal path planning of the robot.