Reviewerly/exHarmony huggingface dataset:
Detecting Relevant Feature Interactions for Recommender Systems via Graph Neural Networks.

Feature interactions are essential for achieving high accuracy in recommendersystems (RS), so they have been taken into consideration in many existing RS,where all feature interactions are modeled. Nevertheless, not all featureinteractions have positive effects for RS: modeling the irrelevant featureinteractions may introduce noises and degrade the accuracy. To overcome thisproblem, in this work, we propose a graph neural network-based model, L0-SIGN,to detect the relevance of feature interactions and utilize only the relevantones for RS, with features as nodes and feature interactions as edges.Generally, our model consists of two components: an L0 regularization basededge prediction model to explicitly detect relevant feature interactions; and agraph classification model, SIGN, to effectively model and aggregate thedetected ones for recommendations. These two components positively influenceeach other to ensure that the most relevant feature interactions will bedetected and modeled. In addition, we further prove that the effectiveness ofour model is theoretically sound. We first show that our model is a variationalapproximation of information bottleneck principle, i.e., the detected featureinteractions are guaranteed to be most relevant. We then show that our modelfollows the definition of statistical interactions, proving that the modelingof detected feature interactions in L0-SIGN is effective. Experimental resultsshow that (i) L0-SIGN outperforms existing baselines in terms of accuracy, and(ii) the detected feature interactions are beneficial for performance gain andinterpretability.
Application of Virtual Reality Combined with Eye Tracking Technology for Design Flows

In this paper, a combination of virtual reality (VR) and eye tracking technology applied in design process is presented. The efficacy evaluation of the proposed application is further discussed. The paper combines the ARCS and IMMS models. Furthermore, traditional design process is researched and optimized, which not only helps to enhance the design efficacy, but is also suitable for improving the efficiency of the whole industry. This interdisciplinary research provides theoretical and technical bases for the application and evaluation of immersive design in different disciplines, showing high academic and practical significance.
Fitness-evaluated Adaptive Switching Simulated Kalman Filter Algorithm with Randomness

&#x0D; &#x0D; &#x0D; &#x0D; The original Simulated Kalman Filter (SKF) is an optimizer that employs synchronous update mechanism. The agents in SKF update their solutions after all fitness calculations, prediction process, and measurement process are completed. An alternative to synchronous update is asynchronous update. In asynchronous update, only one agent does fitness calculation, prediction, measurement, and estimation processes at one time. A recent study shows that the asynchronous SKF outperforms synchronous SKF. In this study, synchronous and asynchronous mechanisms are combined in SKF. At first, the SKF starts with either synchronous or asynchronous update. By evaluating the fitness, if no improved solution is found, the SKF changes its update mechanism. The decision to switch from synchronous to asynchronous or vice versa is made randomly. Using the CEC2014 benchmark test suite, experimental results indicate that the proposed adaptive switching SKF randomness outperforms the original SKF algorithm.&#x0D; &#x0D; &#x0D; &#x0D;
Analisis Faktor-Faktor yang Mempengaruhi Auditor dalam Memberikan Opini Audit atas Laporan Keuangan Pemerintah Daerah (LKPD) Provinsi Sumatera Barat

ABSTRAC&#x0D; This research was conducted to determine the effect of independence, audit expertise, the scope of the audit, audit audit, and interim examination of the consideration of giving audit opinion. In this study, researchers examined the consideration of providing audit opinion at the Office of the Republic of Indonesia Supreme Audit Agency (BPK) of West Sumatra Province by using independent variables, namely independence, audit expertise, audit scope, audit judgment, and interim examination. The population in this study are all auditors who work at the Representative Office of the Supreme Audit Board (BPK) of Republic of Indonesia in West Sumatra Province. The primary data collection method used was a questionnaire method distributed to respondents, the sampling technique was purposive sampling with a sample size of 22 respondents. The results of testing the hypothesis in this study indicate that the variables of independence, audit expertise, audit judgment and interim examination have a positive and significant effect on giving audit opinion, while audit scope variable has no effect but has a negative direction. Simultaneously the variables of independence, audit expertise, audit judgment and interim examination have a positive and significant effect on giving audit opinion.&#x0D; ABSTRAK&#x0D; Penelitian ini dilakukan untuk mengetahui pengaruh independensi, keahlian audit, lingkup audit, audit judgemet, dan pemeriksaan interim terhadap pertimbangan pemberian opini audit. Dalam penelitian ini, peneliti mengkaji pertimbangan pemberian opini audit pada Kantor Badan Pemeriksa Keuangan (BPK) RI Perwakilan Provinsi Sumatera Barat dengan menggunakan variabel independen, yaitu independensi, keahlian audit, lingkup audit, audit judgement, dan pemeriksaan interim. Populasi dalam penelitian ini adalah seluruh auditor yang bekerja pada Kantor Perwakilan Badan Pemeriksa Keuangan (BPK) RI Perwakilan Provinsi Sumatera Barat. Metode pengambilan data primer yang digunakan adalah metode kuesioner yang dibagikan kepada responden, teknik pengambilan sampel yaitu dengan purposive sampling dengan jumlah sampel sebanyak 22 responden. Teknik analisis data yang digunakan dalam penelitian ini adalah teknik analisis regresi linier berganda. Hasil dari pengujian hipotesis dalam penelitian ini menunjukkan bahwa variabel independensi, keahlian audit, audit judgement dan pemeriksaan interim berpengaruh positif dan signifikan terhadap pemberian opini audit, sedangkan variabel lingkup audit tidak berpengaruh namun beraarah negatif. Secara simultan variabel independensi, keahlian audit, audit judgement dan pemeriksaan interim berpengaruh positif dan signifikan terhadap pemberian opini audit.&#x0D;
Assessment for Secondary School Students’ Experiences in Using Tablet in Classroom

The Egyptian government integrated tablets in Egyptian secondary schools. Thus, the researcher aimed to explore the effectiveness of using tablet in Egyptian secondary schools from the students’ perspective. He aimed to explore that in order to assess students’ experiences in this regard. He selected a random sample consisting from 745 female and male secondary school students in Egypt. Those students were selected from three schools. Questionnaire forms were distributed to those students by hand. All the distributed forms were retrieved. However, 9 forms were excluded due to missing data. Thus, 736 questionnaire forms are valid for analysis. It was found that tablet serves as an effective learning method in Egyptian secondary schools. It was found that using tablet in classroom improves students’ creative thinking skills and makes teachers more creative. It was found that using tablet in classroom enriches students’ vocabulary, improves their language skills and increases their academic achievement in classroom. It was found that such use can meet the learning needs of various types of learners. The researcher recommends conducting studies about the challenges facing teachers in using tablets in classroom.
Cybercrimes awareness, cyber laws and its practice in public sector Tanzania

Government of Tanzania provides services such as education, healthiness, security, transportation, water, electricity, wellbeing and accommodation, on a huge scale.These are public services, which are offered by public servants as an implementation of government goals on behalf.Anything that has to be accomplished so as to improve our country and to provide services to the people, is determined by the work of public servants.
Detection of Sulphide Deposit Using Uranium/Potassium Ratio Map

Potassium (K) response is associated with minerals that can be easily weathered, whereas uranium (U) is usually related to residual clay, oxides and accessory minerals. With a view to interpret for the detection of sulphide deposit based on similar responses exhibited by the various rock units, radiometric data set was interpreted. The study area is located within Latitude +8000’00’’to +8030’00’’ and Longitude +5030’00’’E to +6000’00’’E. The data was collected in most parts of the Nigeria by Fugro Airborne Services Ltd. Johannesburg in collaboration with the Nigerian Geological Survey agency using a light aircraft that was flown in NW-SE direction with a nominal terrain clearance of 80 m and at a speed of 70-80 m/s, with a flight line spacing of 500 m apart. The acquired data was subjected to elemental concentration enhancement using Geosoft Oasis Montaj Software. From the interpreted data, the red coloured portions indicate high uranium and low potassium formations (H-U/K), while the blue coloured portions indicate low uranium and high potassium formations (L-U/K). The regions L-U/K have recorded low U/K ratios, meaning that L-U/K have very low uranium count rates as compared to the count rates of potassium in these regions; this signifies potassium abundance. This also suggests igneous activities that usually culminate to the emplacement of the meta-volcanic lithologies. H-U/K and M-U/K (Moderate U/K formations) are seen to have patches of high U/K ratios within the central portions. This high U/K ratio was therefore, as a result of sulphide deposition.
NATURAL LANGUAGE PROCESSING FOR DATA MINING IN COMPUTER SCIENCE EDUCATION

F. López-Ostenero, L. Plaza, J. Martinez-Romo, L. AraujoUniversidad Nacional de Educacion a Distancia (UNED) (SPAIN)
ANALYSIS OF THE ABILITY OF READING CLASS 1 BASIC SCHOOL STUDENTS IN STATE BASIC SCHOOL 009 KEPAU JAYA SIAK HULU KAMPAR DISTRICT

The background of this research is the problem of reading ability of grade 1 elementary school students in 009 Kepau Jaya Public Elementary School, Siak Hulu Subdistrict, Kampar Regency, as seen by students who have difficulty recognizing letters, even though the teacher often repeats the letters in front of the class, saying words, and matching pictures with writing when the teacher uses the task of matching images with children's writing tends to be less able to do it. This study aims to analyze the reading ability of grade 1 elementary school students at 009 Kepau Jaya Public Elementary School. The population and sample in this study were all first-grade students of 009 Public Elementary School Siak Hulu, Siak Hulu Subdistrict, amounting to 30 students. The method used in this research is quantitative descriptive to analyze the reading ability of grade 1 elementary school students at 009 Kepau Jaya Public Elementary School, Siak Hulu District, Kampar District. The data collection technique used was the observation of grade 1 students and analyzed to find out the results of descriptive statistics that illustrated the level of ability to educate elementary school students in grade 1. Based on the results of the study it was found that the ability to read first-grade students of 009 Kepau Jaya Public Elementary School in Siak Hulu District was a low category. This can be seen in the category of scores obtained by students where 18 or 60% of students are in the low initial reading ability, while the remaining 12 or 40% of students are in moderate reading ability. This is influenced by physiological factors, intellectual factors, environmental factors, and psychological factors.
IC &amp; OI The impact of intellectual capital on organizational innovation

Intellectual capital can generate value for organizations and improve organizational innovation. This study aims to investigate the effects of intellectual capital on corporate innovation. Mixed research methodology approach has been used by combining both qualitative and quantitative analysis to explore and empirical examine the research model. The targeted population of interest is the licensed pharmaceutical manufactures, 90 organizations in the Egyptian pharmaceutical industry throughout its three main sectors (11 public, 70 local private and 9 MNCs). Statistical analyses are employed based on the questionnaires gathered from 39 pharmaceutical manufactures’ companies (44% response rate). In addition, sixty-three “63” in depth interviews have been conducted with both top and middle managers. The research findings indicate that all dimensions of intellectual capital (human, structural, and relational capital) have positive significant effects on organizational innovation of pharmaceutical manufactures’ companies. The study clarifies that the most dominant dimension is structural capital, which provides the largest and strongest support to pharmaceutical manufactures’ companies. The deep realization of the importance intellectual capital and its impact on innovation helps leaders to adopt accurate system to run organizational innovation in a better way, which lead to sustainable competitive advantage for organizations.
Maskara: Compilation of a Masking Countermeasure With Optimized Polynomial Interpolation

Side-channel attacks are amongst the major threats for embedded systems and IoT devices. Masking is one of the most used countermeasure against such attacks, but its application remains a difficult process. We propose a target-independent approach for applying a first-order Boolean masking countermeasure during compilation, on the static single assignment (SSA) form. Contrary to the state-of-the art automated approaches that require to simplify the control flow of the input program, our approach supports regular control-flow program structures. Moreover, our compiler is the first to automatically mask table lookups using a polynomial interpolation approach. We also present new optimizations to speedup the evaluation of polynomials: we reduce the number of terms of the polynomial, and we accelerate finite-field multiplication. We show that our approach is faster than the standard masked table approach with mask refresh after each access, with speedups up to ×2.4 in our experiments. Finally, using a formal verification approach, we show that the compiled machine code is secure, i.e., that all intermediate computations are statistically independent of the secrets.
The Principle and Progress of Dynamically Reconfigurable Computing Technologies

With the emergence of new applications and the increasing cost of new semiconductor manufacturing technology, high energy-efficiency and flexibility are both critical for processors. Dynamically reconfigurable computing architecture, which has the both characteristics, is one of the most promising architectures for future processors. It has shown notable advantages in many important application fields, compared to conventional architectures. However, the fundamental reasons for the characteristics have never been deeply discussed in previous papers. This paper analyzes the reasons from the perspective of design methodology. The technologies of dynamically reconfigurable computing are continually evolving, and some cheering results of application have been achieved. This paper summarizes the latest progress in key technologies and provides an introduction of the application achievements.
Empirical verifications of web-learning environment to enhance learning effectiveness and motivation in mechanical drawing

In mechanical drawing class, it is a problem that a lecturer has students get a wide range of knowledge and skills in a class whose time and place are limited in a semester. The situation surrounding the classes has led to insufficient understanding of students. Accordingly, it has been desired to reveal an effective learning method in mechanical drawing class. In this study, a web-learning environment was created on the basis of motivation-oriented teaching method using ARCS model and Gagne’s 9 events of instruction. Then, the web-learning environment was introduced into mechanical drawing class, and the effectiveness was investigated with the comparison of results from paper-based and web-based tests. After that, learning motivation was also assessed using ARCS evaluation sheet. From the results, there existed the advantage of using web-learning environment. In addition, it was remarkable that attention-related factors greatly contributed the enhancement of learning motivation.
Second-Order Masked Lookup Table Compression Scheme

Masking by lookup table randomisation is a well-known technique used to achieve side-channel attack resistance for software implementations, particularly, against DPA attacks. The randomised table technique for first- and second-order security requires about m•2n bits of RAM to store an (n,m)-bit masked S-box lookup table. Table compression helps in reducing the amount of memory required, and this is useful for highly resource-constrained IoT devices. Recently, Vadnala (CT-RSA 2017) proposed a randomised table compression scheme for first- and second-order security in the probing leakage model. This scheme reduces the RAM memory required by about a factor of 2l, where l is a compression parameter. Vivek (Indocrypt 2017) demonstrated an attack against the second-order scheme of Vadnala. Hence achieving table compression at second and higher orders is an open problem.In this work, we propose a second-order secure randomised table compression scheme which works for any (n,m)-bit S-box. Our proposal is a variant of Vadnala’s scheme that is not only secure but also significantly improves the time-memory trade-off. Specifically, we improve the online execution time by a factor of 2n−l. Our proposed scheme is proved 2-SNI secure in the probing leakage model. We have implemented our method for AES-128 on a 32-bit ARM Cortex processor. We are able to reduce the memory required to store a randomised S-box table for second-order AES-128 implementation to 59 bytes.
Deblurring approach for motion camera combining FFT with α-confidence goal optimization

Sharp images ensure success in the object detection and recognition from state-of-art deep learning methods. When there is a fast relative motion between the camera and the object being imaged during exposure, it will necessarily result in blurred images. To deblur the images acquired under the camera motion for high-quality images, a deblurring approach with relatively simple calculation is proposed. An accurate estimation method of point spread function is firstly developed by performing the Fourier transform twice. Artifacts caused by image direct deconvolution are then reduced by predicting the image boundary region, and the deconvolution model is optimized by an α-confidence statistics algorithm based on the greyscale consistency of the image adjacent columns. The proposed deblurring approach is finally carried out on both the synthetic-blurred images and the real-scene images. The experiment results demonstrate that the proposed image deblurring approach outperforms the existing methods for the images that are seriously blurred in direction motion.
Correction to: Multicenter comparison of three intraoperative hemoglobin trend monitoring methods

In the original publication of the article, the ABGHb graph of Fig. 2 was incorrectly rendered during conversion from black and white to color. The figure shows hemoglobin results from the 3 compared monitoring methods to results obtained by laboratory hematology analyzer. Importantly this illustration of secondary outcome was not used for statistical comparisons but is intended to show relative accuracy of the 3 monitoring methods. The corrected Fig. 2 is given in this erratum.
Bi-Directional Filter for the Removal of Lines and Cracks in Images

In this paper, a method for the removal of noisy lines and cracks corrupted by different noise types is explored, using a cascade of filtering cycles based on the principle of symmetry among neighboring pixels. Each filtering cycle includes a filter in two perpendicular directions, one horizontal and the other vertical. Any pixel, to be deemed original, should have a number of symmetric pixels within its neighboring pixels greater than the number specified by the condition set for each direction in all the filters. Since the conditions of each filter increase gradually from one cycle to the next, it becomes more difficult for a noisy pixel to satisfy the filter conditions in each filtering cycle, while an original pixel can easily satisfy the conditions in all the filtering cycles. The reason is that a noisy pixel has a random value and therefore faces difficulty in finding a sufficient number of symmetric pixels in each direction, while an original one has a value correlated with the values of its neighboring pixels. Extensive simulation experiments prove that the proposed method efficiently detects and restores different noisy lines and cracks of different shape and thickness. Also, it retains the image details and outperforms other well-known algorithms, both objectively and subjectively. More specifically, the proposed algorithm achieves restoration performance better than the other known methods by ≥0.81dB in all simulation experiments.
Cross-view pedestrian clustering via graph convolution network for unsupervised person re-identification

At present, supervised person re-identification method achieves high identification performance. However, there are a lot of cross cameras with unlabeled data in the actual application scenarios. The high cost of marking data will greatly reduce the effect of the supervised learning model transferring to other scene domains. Therefore, unsupervised learning of person re-identification becomes more attractive in the real world. In addition, due to changes in camera angle, illumination and posture, the extracted person image representation is generally different in the non-cross camera view, but the existing algorithm ignores the difference among cross camera images under camera parameters and environments. In order to overcome the above problems, we propose unsupervised person re-identification metric learning method. The model learns a shared space to reduce the discrepancy under different cameras. The graph convolution network is further employed to cluster the cross-view image features extracted from the shared space. Our model improves the scalability of pedestrian re-identification in practical application scenarios. Extensive experiments on four large-scale person re-identification public datasets have been conducted to demonstrate the effectiveness of the proposed model.
MODERN ASPECTS OF THE USE OF FOGGY TECHNOLOGIES IN THE EDUCATIONAL PROCESS OF HIGHER EDUCATIONAL INSTITUTIONS

The article considers the issues of improving the managerial and educational activities of higher education institutions through the use of cloudy and foggy innovative technologies. The author of the article on the basis of the analysis of scientific, pedagogical and specialized literature proves the relevance of research in this direction. This scientific legacy presents Google services that are appropriate to use in the educational process to increase its effectiveness and efficiency, as well as the feasibility of organizing and implementing an educational and scientific laboratory of innovative technologies.