Reviewerly/exHarmony huggingface dataset:
Cultural Intelligence and Institutional Success: The Mediating Role of Relationship Quality

© 2019 Elsevier Inc. As managerial rationality is always bounded, managers utilise their cognitive abilities and social relations to manage their operational environmental uncertainties. We posit that relationship quality (RQ) mediates the association between cultural intelligence (CQ) and success in managing challenges arising out of differences in the institutional environments i.e. institutional success. Our CQ measure comprises cognitive, metacognitive, motivational and behavioural CQs. We included the interactive effects of two inter-related mental capabilities, namely cognitive and metacognitive CQs, and motivational and behavioural CQs while examining the mediating role of RQ between CQ and institutional success. Based on data from 186 Indian senior managers doing business with New Zealand, we find mixed support for our hypotheses. We find indirect-only mediation effects for interactive effects of cognitive and metacognitive CQs, and complementary mediation effects for motivational CQ. Contrary to expectations, we find negative direct-only non-mediation effects of behavioural CQ.
Comments for manuscript soil-2019-94

General comments Li et al., display an interesting study based on 137Cs activity and soil property measurements carried out in a karst depression in SW China to estimate soil erosion rates along a cultivated catchment's slope and related sediment accumulation rate in its bottom part.The authors only sampled 10 soil cores (nine along 3 hillslope positions and one within the depression).Estimates of soil erosion rates were derived from the soil 137Cs inventories for a limited number of sites using the method published by Zhang et al. (2009).They also carried out a PCA analysis to relate several soil properties (soil pH, total nitrogen -total phosphorus -total potassium
Emotional Immersion Through Interactive Media

Using gameplay, video games immerse players into a variety of different emotional experiences such as excitement, fear and disgust. Other emotional experiences such as sadness, anger and happiness are generally relegated to be expressed by video and audio in games such as cutscenes and voice clips. The goal of this project is to create a game that uses its interactivity to make players feel immersed in emotions not usually found in gameplay. This will be done through the use of VR motion controllers and headsets to make the player feel immersed and more emotionally connected to their actions in the game.
Multi Group Based Daily Living Activity Recognition (DLAR) using Advanced Machine Learning Algorithm

Human activity recognition (HAR) has realized more interest in several research communities given that understanding user activities and behavior help to deliver proactive and personalized services. Different types of noise in wearable sensors data frequently hamper the human activity recognition classification process. Categorically, in this proposed work designs the three-level hierarchical classification structure, i.e., instance based, group and sub-group based and subject based to detect the daily activity of human body motion among activity groups. In correlation with other famous classifiers, for such as Random Forest Tree, J48, Decision Table, Multilayer Perceptron, NaïveBayes, oneR and REPTree (Reduced Error Pruning Tree), etc., thorough experiments on the mHealth dataset (Shimmer2 mHealth Data) demonstrate that group based classification achieves the best classification results, reaching RFT 99.97%. We trained classier in order to estimate accuracy classification based on (gender, age, height, and weight). We applied validation methods to the process, 10-fold cross-validation. For all three classification structure, we achieve high accuracy values for all three classification task
On the benefits of multimodal annotations for vocabulary uptake from reading

© 2017 Informa UK Limited, trading as Taylor &amp; Francis Group. Several research articles published in the realm of Computer Assisted Language Learning (CALL) have reported evidence of the benefits of multimodal annotations, i.e. the provision of pictorial as well as verbal clarifications, for vocabulary uptake from reading. Almost invariably, these publications account for the observed benefits with reference to Paivio's Dual Coding Theory, suggesting it is the visual illustration of word meaning that enhances the quality of processing and hence makes new words more memorable. In this discussion article, we explore the possibility that it is not necessarily the multimodality per se that accounts for the reported benefits. Instead, we argue that the provision of multimodal annotations is one of several possible means of inviting more and/or longer attention to the annotations–with amounts of attention given to words being a significant predictor of their retention in memory. After reviewing the available research on the subject and questioning whether invoking Paivio's Dual Coding Theory is an optimal account for reported findings, we report an eye-tracking study the results of which are consistent with the alternative thesis that the advantage of multimodal glosses for word learning lies with the greater quantity of attention these glosses attract in comparison with single-mode glosses. We conclude with a call for further research on combinations and sequences of annotation types, regardless of multimodality, as ways of promoting vocabulary uptake from reading.
Development of Algorithm for Optimally Weighted Non-Iterative Bilateral Filter (OW-NI-BF) to Eliminate Gaussian Noise

Gaussian filter is linear that smooth independent of edges and details of the image. The standard bilateral filter is effective for low-density noise. However, the performance of filter degrades with an increase in noise level. We designed a non-iterative bilateral filter algorithm which is robust for large noise levels, but lacks low noise levels the performance. To get the best denoising performance out of these two, standard bilateral filter and proposed non-iterative bilateral filter is combined in weighted fashion using Stein's unbiased risk estimate. Thus, the proposed optimally weighted non-iterative bilateral filter (OW-NI-BF) algorithm is guaranteed to perform better than either of the component filter. It is non-linear, local and non-iterative that works on geometric closeness and gray level similarities irrespective of smoothing edge. In Gaussian noise scenarios, the performance of the proposed OW-NI-BF algorithm is compared with various methods. Quantitative and visual denoising results demonstrate significant improvement over the original filter. PSNR and IQI are used to measure the quality of the de-noised image.
Letter Frequency In Indonesian Language Using Proportion Estimation

Cryptanalysis is a process of finding weaknesses in cryptographic algorithms and using these weaknesses to decipher the ciphertext without knowing the secret key. One technique of cryptanalysis is frequency analysis, using the frequency of letters to translate ciphertext to plaintext. Frequency analysis is usually used to test the success of an encryption algorithm. Every language in the world has its own property in letter frequency. This made every language had a different aspect to make sure the algorithm working properly for securing plaintext. This makes it important to know the frequency analysis in Indonesian. The method that was used in this research paper is the proportion estimate to estimate the error from the result and the data we collected is from 10,000 articles that were scrapped from the internet. The result of this paper is the frequency of each letter in the Indonesian language.
SOCIAL DIMENSIONS ON POLITENESS STRATEGIES OF REFUSALS USED BY AMBONESE AND AMERICAN

The aims of this study were to identify the politeness strategies used by Ambonese and Americans in refusing requests, as well as the effects of social relationships. A descriptive qualitative approach was used in the study. The data of American conversations were collected from youtube.com and direct observation by recording conversations between interlocutors by 20 respondents of Ambonese in any situation. The data was analyzed and classified using six politeness systems by Yassi, and politeness strategies by Brown and Levinson. The results show that in interactions between strangers, Ambonese people tend to use a bald on record strategy, which is frequently combined with a negative politeness strategy, whereas Americans tend to use a negative politeness strategy, which includes expressing apology followed by a direct expression of refusal or using off-record strategy. In an intimate relationship, Ambonese people tend to use positive politeness strategies, whereas Americans tend to use off-record strategies and negative politeness strategies. In a hierarchal relationship, Ambonese tend to use negative politeness strategies by inferior to superior person, while Americans tend to use negative politeness strategies or off record strategies. Culturally, Ambonese people were influenced by local wisdom to maintain solidarity in responding and addressing, which is called Pela Gandong, whereas Americans were influenced by the freedom to express themselves.
Влияние интеллектуальных учебных заданий на актуализацию потребностей в физкультурных знаниях и физкультурном мышлении учащихся

The article deals with the problem of actualization of needs in physical culture knowledge and thinking of students of the second and third stages of general secondary education. Objective. To test experimentally the effectiveness of the use of intellectual educational tasks (used within the framework of pedagogical technology); aimed at forming needs in physical culture knowledge and thinking of students. Methods. A questionnaire forming a pedagogical experiment; methods of mathematical statistics. Results. The study involved 194 students of I–IV courses of DUO «Specialized Lyceum at the University of Civil Protection of the Ministry of Emergencies of the Republic of Belarus». The article presents some intellectual educational tasks that were used to form the needs in physical culture knowledge and thinking of students. It was revealed that during the period of the formation pedagogical experiment under the influence of intellectual educational tasks in the experimental group; the measure of actualization of needs in physical culture knowledge and thinking has increased statistically significantly; whereas in the control group no statistically significant positive changes have been observed. The results obtained during the period of the formation experiment; are indicative of the effectiveness of the use within the frames of pedagogical technology of intellectual educational tasks; aimed at forming the needs for physical culture knowledge and thinking of pupils of the second and third levels of general secondary education. The formation of needs for physical culture knowledge and thinking is contributed by the following conditions: inclusion of students in intellectual physical culture activities; providing them with various intellectual learning tasks; ensuring the interconnection of intellectual learning tasks with motor ones; the presence of high-quality demonstration of samples of physical culture knowledge and thinking; the use of the system of external motivation for educational activities.
A fuzzy Approach based for Document Datasets Clustering

CdO films have been produced on glass substrates by DC planar magnetron sputtering technique in Ar and O2 gases 1:4 and distance 6cm between cathode and anode and thickness 174 nm. It is observed from optical properties that the films possess transmittance 80% in visible and near infrared region of spectrum and direct band gap values in the rang 2.31-2.4 e V.
Influence of larning interest and vocabulary on the writing description of secondary school in Depok

The purpose of this research: (1) to know the influence of the interaction of learning interest and mastery of the standard vocabulary together to the ability to write the description of the students of SMPN in Depok. (2) to know the effect on the ability to write the description of SMPN students in Depok. (3) to know the influence of standard vocabulary mastery to the ability to write the description of SMPN students in Depok. The research method used is survey method with multiple correlation regression analysis. The sample of the research is the students of class VII: SMPN 1 Depok and SMPN 2 Depok as many as 80 students and take a simple random technique. Data collection was done by direct questionnaire to sample. Data analysis uses descriptive statistics, such as searching for mean (mean), median, mode, standard deviation, and inferential statistics, ie to find simple and double correlation coefficients followed by correlation coefficient significance test with t test. The findings of the researcher indicate that: (1) there is a significant influence of learning interest and mastery of the standard vocabulary simultaneously to the ability to write student description with the acquisition value Fo= 21,909 and Sig.= 0,000 &lt; 0.05; (2) there is a significant influence of learning interest on the ability to write student description with thitung (3,564) &gt; t table (1,99) and Sig. 0.001 &lt; 0.05; (3) there is a significant influence of vocabulary mastery of the learning achievement on the subject of writing description. This is evidenced by the value of thitung (5.909) &gt; t table (1.99) and Sig. 0,000 &lt; 0.05.
Agrobot in field of Machine Learning

Farming is still one of the largest sectors of India from a financial standpoint as well as employing almost two-thirds of our working population.Yetthe farming industry suffers from not being attuned with modern technological advancements. Hence farming industry has not reached its optimum potential and has a lot of areas for improvement.Our project tries to tackle some of these problems. The project’s main focus is on a crop recommendation system that was built using Machine Learning techniques. Along with this, we have worked to make a website as a UI for our recommendation system. Finally, we have also added a lot of agriculture-related infotainment as there is a lot of misinformation related to agriculture and also to pique the interest of the user in the field of modern agriculture. Through the whole process of implementing this project, our team learned about Machine Learning, Web Development, Content Creation, and most importantly the scientific method of Agriculture for the 21st century. Our design ideology revolved around making our system a holistic place for anyone who wants to get an introduction to modern farming. The germination of the project is from the need to modernize agriculture and thus the project intends to tackle issues from the grassroot
Alternative Voice Communication Device using Eye Blink Detection for People with Speech Disorders

Speech disorders is an inability to articulate sound due to medical ailments such as brain damage, stroke to paralysis and several other diseases. Research data suggests that about 15 million people in the world have partial or complete impairment of language expression due to brain damage, mostly from stroke. In this work a low-cost speech assistant device is proposed an alternate augmentative communication device for stroke or paralyzed patients. The eye blink sensor is used as the primary sensor for detection of eye blink. Based on the eye blink gestures the common words are displayed in the LCD and these words are also converted as voice output. This prototype will be an alternate communication aid for people with speech disorders.
Analysis and Design Of New Student Admission Systems On MTS AL MUHTADIIN

MTs Al-muhtadiin is the first private vocational school in the sub-district of Sukadiri, at the beginning of the opening of this school, it received quite a positive response with proven opening in 2017 around 62 students registered themselves as students at MTs Al-Muhtadiin. The new student registration system at MTs Al-Muhtadiin is already running effectively and efficiently. In analyzing the running system used the method of analysis and depiction of the system using UML (Unified Modeling Language) and in data collection used interview, observation and literature study methods. The results of the analysis of the system that runs in the admission of new students at MTs Al-Muhtadiin are still running manually with the help of Microsoft Excel in the process of making reports.
Security Problems in Iot Model and Privacy Preserving in Various Iot Devices

It is instead required for IoT units to equip along with the potential to withstand security and privacy threats when fulfilling the intended useful criteria and services. To obtain these targets, there are many brand-new problems for the IoT to apply personal privacy-preserving records manipulation. Initially, data professionals need to have to process privacy-sensitive data to remove the counted on details without particular privacy enclosure. Within this paper, our company temporarily showed the kinds of security concerns in IoT style, personal privacy-preserving in different IoT devices as well as additional challenges and also method for privacy-preserving time-series data publishing.
Human visual system inspired saliency guided edge preserving tone-mapping for high dynamic range imaging

With the growing popularity of High Dynamic Range Imaging (HDRI), the necessity for advanced tone-mapping techniques has greatly increased. In this thesis, I propose a novel saliency guided edge-preserving tone-mapping method that uses saliency region information of an HDR image as input to a guided filter for base and detail image layer separation. Both high resolution and low resolution saliency maps were used for the performance evaluation of the proposed method. After detail layer enhancement and base layer compression with constant weights, a new edge preserved tone-mapped image was composed by adding the layers back together with saturation and exposure adjustments. The filter operation is faster due to the use of the guided filter, which has O(N) time operation with N number of pixels. Both objective and subjective quality assessment results demonstrated that the proposed method has higher edge and naturalness preserving capability, which is homologous to the Human Visual System (HVS), as compared to other state-of-the-art tone-mapping approaches.
Influence of Causal Factors towards Internal Educational Quality Assurance of a University Course Tier

This study investigated the various factors affecting the operational efficiency of the internal educational quality assurance at Rajamangala University of Technology.It particularly assessed the strategic management, transformational leadership, motivation, and operational efficiency of the internal quality assurance.It also tested the consistency of the causal model of factors affecting operational efficiency of internal educational quality assurance and the influence of strategic management, transformational leadership, and motivation on the internal educational quality assurance.Data collected from the 236 lecturers of the different courses from the nine (9) campuses of the university were analyzed using the path analysis.The results revealed that the respondents have high regards on the strategic management, transformational leadership, and motivation.The hypothesis testing showed that the causal model of factors was consistent with the empirical data.The strategic management and motivation directly affected operational efficiency of the internal educational quality assurance with statistical significance level of 0.05 and 0.01, respectively.Meanwhile, transformational leadership affected the operational efficiency of internal educational quality assurance at statistically insignificant level.The results of the study would be useful for the enhancement of the internal quality assurance practices of universities in Thailand.
Diversification and Stability of African Banks

The present study empirically examines whether banks operating within Africa concentrate or diversify their incomes and loan portfolios and how these decisions affect their stability. The present study uses Generalized Methods of Moments (GMM) as the econometric tool in carrying out the analysis. The study shows that banks in Africa are relatively stable and well diversified. However, income diversification strategies do not enhance banks’ stability. Loan portfolio concentration guarantees a reduction in bank credit risk and boosts stability. Overall, loan portfolio concentration is therefore more important for stability than income diversification among banks in Africa.
A Semantic based Terms Relation Research for Classification in Web Information Mining

The rapid growth of web information and its services in different areas such as e-commerce, healthcare, digital marketing, online booking, etc. is a challenge in providing accurate information in the domain services related to the user's query. The current web information of services classifies the retrieval of the relevant service and assists the classification by supporting the knowledge and classifications of the specific service information. Because of these limitations and the complexity of automatic update mechanisms to see this service information, a large number of non-related service information for a requested query, and getting the required web information of services is a cumbersome problem. This paper proposes Semantic based Terms Relation Approach (STRA) for classifying information for effective classification of WIS on the web. The approach utilize Concept Terms Similarity (CTS) method for the most relevant terms in a service domain and construct a Related Terms Hierarchal Model (RTHM), which will be used for classification. A modified Naive Bayes classifier is used to perform the classification of the web information of services using RTHM, to categorize and present accurately. The experiment evaluation of the proposed approach shows an improvement in the classification of information and achieve a highly related matching results against different number of users queries.
PPDM for Medical Data using Visual Cryptography

Privacy preserving data mining is a growing field with advancements reported frequently. In this paper, for maintaining privacy of medical data of patients, a novel visual crypto technique of peeling with modular scheme is proposed. In this work, using the concept of group theory, PPDM for medical data is done using Verilog.
Association on Supervised Term Weighting Method for Classification on Data Twitter

Term weighting is a preprocessing phase that has an important role in the text classification by giving the appropriate weight for each term in all documents. In previous research, many supervised term weighting methods have been introduced, but most of the supervised term weighting only considers the distribution of terms in the two classes so that it is not optimal for the multi-class classification. This paper introduces a new supervised weighting with association concept to optimize term weighting distributions in multi-class cases by considering terms that exist in each class and paying attention to the number of terms in the document belonging to the class, also considering the relationship pattern between one or more items with association concept in a dataset to measure the strength of terms in a class by using confidence values. The dataset used are the data twitter taken from the PR FM twitter account. The proposed supervised term weighting method implemented with SVM classifier can outperform unsupervised weighting schemes such as TF-IDF with the average accuracy 81.704%.