Reviewerly/exHarmony huggingface dataset:
Impact of Business Intelligence Capabilities on the Competitive Performance of Islamic Banks in Jordan

This study aimed to measure the impact of business intelligence capabilities on the competitive performance of Islamic banks in Jordan. The study population involved 240 senior- and middle-level managers of Islamic Banks in Jordan. The 202 managers responded to the distributed questionnaire from which 202 questionnaires were received, among which 14 were unsuitable for statistical analysis. Structural equation modeling (SEM) was used to test the hypothesized relationships. The importance of this study comes from the structure of the study variables that this study deals with the business intelligence variable as one of the renewable and evolving variables, as it allows organizations in general, and banks in particular, to manage a large amount of data, and turn it into the information of interest to the organization by following up on technological development. The study found a statistically significant effect of business intelligence capabilities represented by capabilities of business intelligence, structure, and culture of business intelligence on competitive performance. Based on the study results, the researchers recommend that managers and decision-makers more clearly interpret top management decisions to ensure the progress of the business.
A Comprehensive Review on Data Security and Threats for Data Management in Cloud Computing

The cloud is a network of virtual computers that are linked together and may exhibit and offer computational capabilities continuously depending on certain Service Level Agreements (SLAs) that have been agreed between the parties to a contract between the clients and the internet provider. Cloud computing has several benefits, including endless computational resources, cheap cost, security controls, hypervisor protection, instantaneous elasticity, high throughput, and fault-tolerant solutions with increased performance. Since cloud computing is a comparatively recent computing model, there exists a lot of uncertainty about how well confidentiality of all levels, including host, network, data levels, and implementation, can be achieved. As a result, there still are important obstacles to cloud computing adoption. These constraints include security issues concerning privacy, compliance, and legal issues. When databases and software applications are moved from the cloud to large data centers, data management becomes a major challenge. Numerous security issues may develop while using cloud computing, including issues with privacy and control, virtualization and accessibility issues, confidentiality, management of credentials and identities, authentication of responding devices, and authenticity. In this paper, an effort is made to offer a comprehensive review of data security and threats in cloud computing.
The Influence of Service Quality and Library Facilities on User Satisfaction at the Laa Roiba National Institute of Islamic Religion

This study discusses the quality of service and library facilities on user satisfaction at the National Islamic Institute of Religion Library Laa Roiba Bogor based on the opinions of library users. The method used is quantitative, the population in this study is library visitors, namely students of the National Islamic Institute of Islam Laa Roiba as many as 355 people. This population is obtained from the number of library visitors. The type of sample selection in this study uses simple random sampling, where the sampling of members of the population is carried out randomly without regard to the existing strata in the population. In determining the number of samples using the Slovin formula. With the Slovin formula, it is known that the sample is 78 people. Based on the results of the study, according to library users, the quality of service and library facilities at the Laa Roiba National Islamic Institute Library got a good score. This is evidenced by the results of regression analysis that the correlation coefficient of service quality competence and library facilities is positive.
Quantum computing gets down to business

Martijn Boerkamp reports how investments into quantum computing have ballooned in the past year, bringing huge expectations for the sector.
Feature cross fusion - Attention mechanism for intelligent semantic segmentation of surface features around railway

The surface features around railway can provide necessary environment information for railway survey and design, construction management, operation and maintenance, which provide information support for railway design and route selection, land demolition and land acquisition, and foreign object intrusion restrictions. However, the traditional artificial method has problems such as large manpower occupation, long time consumption and high detection missed rate. Aiming at the above problems, we proposed the feature cross fusion-attention mechanism for intelligent semantic segmentation of surface features around railway. On the basis of the hyperseg, the features of adjacent layers are fused by cross-convolution, which improves the information sharing between features of different scales. The attention module is constructed between the same layers of upsampling and downsampling. The local features in the multi-scale fusion feature map are weighted by the attention module and fused with the upsampling features to enrich the detailed local features in the upsampling feature maps and improve the accuracy of target segmentation. The experimental results show that the segmentation accuracy of the color steel houses and buildings of proposed method can reach 0.9235 and 0.7921, and the mIOU can reach 0. S761 and 0.6852.
Mapping Research Trend of Jurnal Bina Praja: A Bibliometric Review Between 2012 and 2021

This study aims to identify the trend of articles published in Jurnal Bina Praja through co-authorship and co-occurrence analysis by describing the citation trend, most cited articles, top productive author, most collaborated author, most frequently keyword appeared, the latest, and the densest keyword of the journal. This study used several applications for collecting and analyzing the data, namely Publish or Perish for searching the literature, Mendeley for completing the metadata, and VOSviewer for building the visualization and analysis. This study showed that 273 articles were published online in Jurnal Bina Praja from 2012 volume 4 number 1 to 2021 volume 13 number 2. Based on this mapping, there has been a significant increase in citations from 2017 to 2020. The year 2020 was the highest number of sources, namely 266 citations, compared to the previous year, with only 162 citations. The most cited article was the one written by Saksono in 2012 entitled "Creative Economy: New Talents for Regional Competitiveness Triggers." The most productive author is Hamudy, with several publications of 9 documents. In terms of collaboration between authors, as seen from co-authorship based on total link strengths, there are 9 clusters. The most collaborated author with seven total link strengths, namely Afriyani, Fitri, Manoby, and Pranasari. According to the network visualization, the most frequent keyword in Jurnal Bina Praja is local government, with 18 occurrences. COVID-19 was the latest keyword in the Jurnal Bina Praja in 2021. Local government is the densest keyword in this journal, followed by decentralization, poverty, development, and innovation.
<i>Alcyone</i> come modello nella poesia di Goliarda Sapienza Prime osservazioni per uno studio in corso

Ancestrale is Goliarda Sapienza’s first and only poetic work written between the 1950s and 1960s. In the book she develops an interesting approach to vocabulary, building a part of her own poetics. Although critics have long dealt with Sapienza’s poetry, there is no study of her sources. This essay proposes some initial observations on the possibility that d’Annunzio’s Alcyone may have served as a model for Sapienza, through an analysis and a comparison of their poetic lexicon and of its frequencies.
INNOVATION AND OBSTACLES IN WEST AFRICAN FIRMS: AN EVIDENCE FROM THE GHANAIAN CONTEXT

Innovation is a concept that has kept the attention of researchers worldwide. Innovation leads to product and process improvement, assists the organization to survive, grow faster, efficiently, and be more profitable than non-innovative organisations. However, the innovation level among Ghanaian firms is not yet reaching its full potential. In addition, innovative behaviour among Ghanaian enterprises is still at the infancy stage. To boost the innovation rate, it is imperative to solve the challenges and issues faced by Ghanaian firms. Innovation has become the building block of development in both developed and developing countries it is commonly agreed that innovation is the critical path towards growth and prosperity for countries as well as for individual firms. It is the key to technology adoption, creation and explains the vast difference in productivity across and within countries. However, in Africa, the case seems to have faced a challenging time due to obstacles like finance accessibility, electricity, trade regulations, land access, tax, corruption, informal sector malpractices, tax administration, political instability, transportation, and others. It is against some of these obstacles that we decided to embark on this study to help us critically investigate the effect of the barriers to firms’ growth and its effect on the degree of innovation among Ghanaian firms. To help recommend possible solutions to these obstacles. Hence, this will help facilitate firms’ growth and their degree of innovation.&#x0D; Keywords: Innovation, Obstacles, Firms, Ghana.
PELATIHAN PENGOLAHAN DATA MENGGUNAKAN APLIKASI SPSS UNTUK MENINGKATKAN KOMPETENSI MAHASISWA DALAM MENGANALISIS DATA

The obligation for every student at the end of his study period is research. Students are required to write research to obtain a bachelor's degree. The problem in the field is that most of them do not have experience in conducting research and do not know the right program that can be used to facilitate the process of processing data. Moreover, in operating the data processing program, most students are not capable. Therefore, training is needed for students that aims to provide knowledge and competence to process data using the application of a data processing program, namely Statistical Product and Service Solutions (SPSS) version 21. Training activities use lecture, practice, and discussion methods. This training was successful because there was an increase in students' ability to understand and master SPSS.
A FUSION MODEL WITH YOLOV3 AND SHUFFLENETV2 NETWORKS FOR TRAFFIC SIGN RECOGNITION

The rapid and accurate recognition of traffic signs helps to improve the performance of advanced driver assistance systems and provides important safety guarantees for unmanned driving.Aiming at the existing object detection algorithms with the low accuracy of traffic sign recognition, weak generalization ability, and difficult detection for small targets, which cannot be well applied to practical applications, a lightweight deep network model for fast and accurate recognition of traffic signs is established by introducing the lightweight deep learning network ShuffleNetV2 and improving the regression-based object detection network model YOLOv3.Five data augmentation techniques were used to amplify the public dataset and the network parameters were trained using the transfer learning strategy, indicating that the new network was less computationally intensive and could achieve an accuracy of 96%.
Pengaruh Pembelajaran Berbasis Masalah dan Media Pembelajaran Berbasis Online Terhadap Hasil Belajar Siswa Pada Mata Pelajaran Pemasaran Online Kelas XI di SMK Negeri 2 TONDANO

This study aims to determine the effect of problem-based learning and online-based learning media on student learning outcomes in online marketing subjects in class XI at SMK Negeri 2 TONDANO. The research method used in this research is the experimental method. Based on the research it is known that student learning outcomes using the Problem Based Learning Model in class XI Marketing 1 SMK N 2 Tondano have increased. There are differences in student results through test results using Problem Based Learning Model (Problem Based Learning). So there is an increase in student learning outcomes by using the Problem Based Learning Model (Problem Based Learning). Based on the research, it is known that student learning outcomes using online-based learning media in class X1 marketing at SMk N 2 Tondano have increased after the application of the use of online-based learning media. There are differences in student results through test results using online-based learning media. So there is an increase in student learning outcomes using online-based learning media
Change and Innovation of Survey Research in the Internet

Survey research must be accompanied by economic and social development and continuous innovation. As one of the greatest inventions of the 20th century, Internet technology brings huge challenges to survey research work, profoundly affecting the change and development of survey research work. In order to better understand the real needs of the peo 7ple, the Internet era of survey research must be combined with the new characteristics of the Internet era, the practice of innovative survey research work path.
The Decision Tree Aided Neuro-Fuzzy Inference Characterization of the Stochastic Hydrology of the Tana Alluvial Aquifer

The Tana Alluvial Aquifer is the name given to the little-understood aquifer which is active in the areas bordering the River Tana Flow course as the river weaves its way through the sedimentary plains of Balambala, Garissa, Fafi and Ijara and, finally, into the Tana Delta areas, with the common denominator being the proximity to the Lower Tana catchment, especially the riparian corridor of the River itself, and beyond. The aquifer may extend to between five to fifteen kilometers away from the river channels course way, and at times, it may be felt even 20 kilometers away. The geology of the locality is heterogeneous and comprise sediments whose soil mechanics may not be easily deciphered, since some areas close to the river have very fresh water while others are saline (Bura East in Fafi Sub County easily comes to mind here). There are areas far from the river but bearing fresh water (Mulanjo comes to mind). In some areas, sites close to the river discharge low yield figures, whereas those located farther afield discharge favorably. The water quality and discharge are therefore stochastic variables, subject to chance occurrence. In view of this inconsistency, and on the account of data scarcity, the neuro-fuzzy inference algorithm was developed to map the Universe of Discourse of the Tana Alluvial Aquifer, aka the T.A.A., as it relates to the longitudes, latitudes, depths, and discharges of the aquifers in the study area. The mapping was with respect to aquifer discharge, the variable used to characterize an aquifer, in terms of Transmissivity and Hydraulic Conductivity, thereby defining aquifer recharge propensity. Membership functions were developed using the trapezoidal membership family, and fuzzy rules were appropriately evolved from the fuzzified aquifer data, before finally employing the Sugeno inference engines (in Python) to make predictions of discharge, at each of the T.A.A. aquifer subsets mapped for fresh, saline, hard and brackish water species. The accuracy in the outputs achieved in the areas mapped vindicated the power of the neuro-fuzzy inference systems, as the accuracy oscillated between 92 and 99 percent, when the discharge values predicted were compared with the actual known discharge values of the wells mapped. The water quality class characterization was then undertaken using the decision tree (DT) algorithm in python which gave rise to a 100 percent prediction accuracy. The same DT algorithm could not successfully predict the discrete values of aquifer discharge or EC values, with as much accuracy (but performed excellently with salinity class data), and that was why fuzzy logic was employed. The study vindicated the use of the DT and Fuzzy Logic Algorithms as simple, yet powerful analytical tools, in characterizing the Stochastic Hydrology of the Tana Alluvial Aquifer.
Information System for Industrial Mapping at the Industrial Department in Samarinda City

The progress and development of increasing data demand human progress to become someone more advanced. So that everything related to data and information will be more structured and transparent if it is carried out and processed using information technology, including in government agencies. The Department of Industry of Samarinda City always collects data. the existence of industry in the city of Samarinda every year experiences data development and changes. The obstacle is that every industrial data collection was done manually and the officers finding the location of the industry had to contact the village office while not all industries were recorded in the village data. This study uses data collection methods, namely interview and observation methods. The result of this research is an industrial mapping information system at the Industrial Office of Samarinda City based on Android that can be used to help officers find out the distribution of industrial location points in Samarinda City and make it easier for users to find out industrial location routes.
Using GAN Augment CNN performance in Acute Leukemia Classification

Generative Adversarial Networks (GAN) is a type of artificial neural network and deep learning used to synthesize images. In recent years, many studies have applied GAN in the field of medical imaging. This study uses Convolutional Neural Networks (CNN) to predict the classification of acute leukemia and compares the accuracy of CNN model classification prediction before and after the use of GAN data proliferation. After using the original data to generate images with 8 different parameter combinations, twodimensional images using CD3 and CD7 were used to obtain a classification accuracy of 77.4% without GAN data proliferation. Following GAN data proliferation to add images for which the original data were insufficient, CNN classification prediction accuracy increased to 84.7%. This indicates that using GAN to fill gaps for medical diagnostic data can effectively provide the large volume of data required for CNN model training.
Learn2Sum

Due to the enormous volume of data on the web, it is hard for the user to retrieve effective and useful information within the right time. Thus, it has become a need to generate a brief summary from a large amount of textual data according to the user profile. In this context, text summarization is used to identify important information within text documents. It aims to generate shorter versions of the source text, by including only the relevant and salient information. In recent years, the research on summarization techniques based on topic modeling techniques has become a hot topic among researchers thanks to their ability to classify, understand a large text corpora and extract important topics on the text. However, existing studies do not provide the support of personalization when generating summaries because they need to know not only which documents are most helpful to the users, but also which topics and keywords are more or less related to the user' interests. Thus, existing studies lack of the support of adaptive user modeling for user applications in the emerging areas of automatic summarization, topic modeling and visualization. In this context, we propose a new approach of automated text summarization based on topic modeling techniques and taking into account the user's profile which helps to semantically extract relevant topics of textual documents, summarizing information according to the user' topics interests and finally visualize them through a hyper-graph Experiments have been conducted to measure the effectiveness of our solution compared to existing summarizing approaches based on text content. The results show the superiority of our approach.
Containers

We just spent some time going over virtual machines, where a machine stack is virtualized within an image file. This allows you to run multiple virtual machines on a single physical server, with the hypervisor managing the interaction between the guest operating system and the actual hardware, providing a layer of abstraction between the OS and the hardware. However, since each of these VMs must bring their own licensed OS, they are large images, and there tends to be a lot of “wasted space” because, for example, three Windows VMs would be storing three copies of the OS in memory, plus the instance of the OS from the system on which the VMs are running. Containers, on the other hand, are a different approach to system virtualization and permit abstraction above the OS layer instead. This difference in approach results in smaller images that can be loaded much faster than VMs.
STRATEGIC COURSES IMPLEMENTED BY THE PHILIPPINE NATIONAL POLICE ON ILLEGAL DRUGS IN THE PROVINCE OF CAPIZ

The study was conducted to determine the strategic courses implemented by the Philippine National Police on illegal drugs in the Province of Capiz. Specifically, it sought to determine the socio-demographic profile of the respondents, the degree of implementation and problems encountered in the implementation, if there is a significant difference in the degree of implementation considering respondents' category and location and if variables such as respondents' category and location are significantly related to the problems encountered on the implementation of the strategic courses on illegal drugs in the Province of Capiz. Descriptive-correlational type of research was used in the study utilizing survey questionnaire to gather the needed data. The gathered data were analyzed using statistical tools such as frequency count, percentage, mean, t-test, F-test and Chi-Square.&#x0D; The majority of the respondents were males, married, college graduates, PNP Personnel, and coming from the 1st District with a mean age of 44 years old.&#x0D; Strategic courses of the Philippine National Police on illegal drugs as to demand reduction strategies, supply reduction strategies and reduction of the adverse consequences of drug use strategies were implemented.&#x0D; The respondents had encountered moderately serious problems in the implementation of strategic courses on illegal drugs in the Province of Capiz.&#x0D; There was a significant difference in the implementation of strategic courses of the Philippine National Police on illegal drugs as to demand reduction strategies, supply reduction strategies, and reduction of adverse consequences of abuse use strategies considering respondents' category.&#x0D; A significant difference was found between the degree of implementation of supply reduction strategies and respondents' location but no significant difference to demand reduction strategies and reduction of adverse consequences of drug use strategies considering respondents' location.&#x0D; There was no significant relationship between respondents' category and location and the problems encountered in the implementation of strategic courses on illegal drugs.