Reviewerly/exHarmony huggingface dataset:
Learning Model Based on Information Technology in an Accounting Education Courses Based on Technology at Faculty of Economics in Universitas Negeri Semarang

It cannot be denied, nowadays technology is an inseparable part of learning in the classroom and also in the business world. Because of this there are many employers hoping that accounting and accounting education students get teaching about information technology in the field of accounting when they go to college. To fulfill this, in the College in the major of Accounting and Accounting Education curriculum, there are courses called accounting information systems (AIS), Computer Accounting and Introduction to Computer Accounting. This course, if traced back to its origin as mentioned above, is actually one of the very strategic courses. Why is it called very strategic value, because it is closely related to the development of information technology and the demands of the work world that are increasingly here becoming borderless? The teaching curriculum can be very different between each university depending on who and how the subject is coordinated. So that by using information technology learning instruments in the field of accounting developed by Wilis (2016), this study aims to examine a model of how to teach these courses in accounting education by incorporating the practice of using MS Excel in lecture meetings besides emphasizing the use of MS Visio.&#x0D; Keywords: information technology, computer-based learning, accounting education based on the information technology
Using FREAK descriptor to classify plasma influence in Mice sperm

Numerous classification mechanisms anticipate the class's instances to be carried out as the features' vectors, namely the points in a feature's space. It is oftentimes a chance to make an informative exemplification of an image's feature vector for classification problems in computer vision like utilizing global descriptors for the texture description or shape description. The proposed methodology is to classify the sperm image in mice that has been affected through plasma and this methodology consists of three stages. The points of interest could be elicited from sperm plasma images in the first stage by utilizing Adaptive and Generic Corner detector that depended on AGAST (Accelerated Segment Test). FREAK (descriptor of Fast Retina Key-points) was employed in the second stage for describing those points of interest and then computing the standard deviation for those points. KNN (K-Nearest Neighbors) was calculated in the third stage for plasma images classification depending on the STD (standard deviation) amount. The outcomes of the experimental work illustrated that; plasma produced by microwave holds minimum amount of STD than Plasma with high temperature.
A vision-based real-time obstacle avoidance’s rules utilising grid-edge-depth map

&lt;p&gt;This paper presents a new rules-based of a real-time decision system for an autonomous wheeled robot with the holonomic-drive system. The robot uses decisions to avoid collisions with obstacles. The decision rules based on Grid-Edge-Depth Map. The Grid-Edge-Depth map represents the obstacle’s position and distance in the environment. The generation process of the Grid-Edge-Depth map presented in previous research. The decisions of the first scenario with no destination point are forward, stop, 90&lt;sup&gt;o&lt;/sup&gt; right turn, and 90&lt;sup&gt;o&lt;/sup&gt; left turn. The decisions of the second, and third scenarios with a destination point are forward, stop, 90&lt;sup&gt;o&lt;/sup&gt; right turn, 90&lt;sup&gt;o&lt;/sup&gt; left turn, 45&lt;sup&gt;o&lt;/sup&gt; forward to the right, 45&lt;sup&gt;o&lt;/sup&gt; forward to the left, slide to the right, and slide to the left. The proposal tested in a 5x3 metre living environment. Finally, the experiment resulted in 93.3% of navigation’s success for all the scenarios.&lt;/p&gt;
CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D Networks

3D Convolution Neural Networks (CNNs) have been widely applied to 3D scene understanding, such as video analysis and volumetric image recognition. However, 3D networks can easily lead to over-parameterization which incurs expensive computation cost. In this paper, we propose Channel-wise Automatic KErnel Shrinking (CAKES), to enable efficient 3D learning by shrinking standard 3D convolutions into a set of economic operations (e.g., 1D, 2D convolutions). Unlike previous methods, CAKES performs channel-wise kernel shrinkage, which enjoys the following benefits: 1) enabling operations deployed in every layer to be heterogeneous, so that they can extract diverse and complementary information to benefit the learning process; and 2) allowing for an efficient and flexible replacement design, which can be generalized to both spatial-temporal and volumetric data. Further, we propose a new search space based on CAKES, so that the configuration can be determined automatically for simplifying 3D networks. CAKES shows superior performance to other methods with similar model size, and it also achieves comparable performance to state-of-the-art methods with much fewer parameters and computational costs on tasks including 3D medical imaging segmentation and video action recognition. Codes and models are available at https://github.com/yucornetto/CAKES
Optimization of Items Production using Fuzzy Logic Mamdani Methods

The availability of a production item is still difficult to monitor by the company, because the system used still relies on manual calculations from employees of the company. Assisting the company in predicting the availability of production goods effectively then used the fuzzy logic calculations. During this time the availability of production goods in Salman Collection is seen from customer's request. This makes the company not get the maximum profit because there is no planning the amount of production of goods, if the number of products manufactured by the company is less than the number of requests then the company will lose the opportunity to Gain maximum profit. Conversely, if the number of products produced is much more than the number of requests then the company will suffer losses. Application of goods production optimization using Fuzzy logic Mamdani method is an application intended to solve the problem of goods production in Salman Collection is uncertain. Implementing Fuzzy logic on solving the problem of production goods can help the company to optimize the production of goods. The construction of this application the company can determine the amount of production that corresponds to consumer demand and by applying Fuzzy logic Mamdani methods Most of the demand in Salman Collection is fulfilled and more optimal than With the old system or the amount in production by the company.
Private, Public and Foreign Investment Nexus in Pakistan: An Empirical Analysis of Crowding-In/Out Effects

This study empirically explores the relationship among private domestic, foreign direct and public investments for Pakistan economy using time series data from 1960 to 2015.Simultaneous equations and Vector Error Correction Model (VECM) frameworks are employed to examine the inter relationship among the three categories of investments.The study primarily works out crowding-in/out effect.Notably, the crowding-out effect is observed showing substitutability among the three types of investments.The study also finds that public, private domestic and foreign direct investments have strong positive impacts on economic growth.The findings suggest that better economic environment and favorable investment climate are pre-requisite to marginalize the crowding-out effect.
Discussion and debate as a method of professional training оf students of a pedagogical university

The article reveals the advantages and problems of using the methods of discussion and debate in teaching students of the pedagogical University on the example of prepared and conducted intellectual meetings between the students of Faculty of Geography and Faculty of Biology and Chemistry of Moscow Pedagogical State University; it also illustrates the emerging competencies and opportunities to the implementation of interdisciplinary connections and emphasizes the idea of personal self-realization of students.
An efficient ICKM approach for similarity measurement and distance estimation based on k-means

An iterative centroid initialization k-means (ICKM) based clustering has been proposed in this paper. In this approach first the dataset selection has been performed along with the option of choosing and selection as per the data use or the user can access partial data also based on the iterative centroid. Then the data preprocessing steps are followed for the data arrangement and analysis. There are four different distance algorithms have been considered with the k-means. These algorithms provide the complete variability for the distance estimation and production. The proposed method found to be useful along with different distance estimation and measures.
Forensic Dna Profiling In Ghana: Current Developments, Challenges And Future Directions

Ghana is one of nine African countries, the only one in West Africa that uses DNA profiling in criminal investigations. Forensic DNA analysis has proven effective in the identification of crime suspects while exonerating innocent suspects. It appears that DNA profiling has been effective in deterring offenders and reducing crime in Ghana. The Forensic DNA Laboratory (FDNAL) of the Ghana Police Service (GPS) is the only mandated DNA profiling institution that conducts crime-related DNA profiling in the country since its inception in 2011. However, development of this area of expertise has been stalled due to technical, financial and legal issues which include accreditation, the enactment of a DNA law and establishment of a DNA database. This paper seeks to depict the current status of forensic DNA technology in Ghana and provides suggestions towards making the FDNAL achieves the maximum best thereby fulfilling its mandate of serving the forensic DNA needs of the country specifically, and the sub-region as a whole.
An analysis on Learning Condition in Developing of Listening Comprehension Model by Using Social Media for English Students

Learning a foreign language by using social media is getting important because it has great potential to support student-centered learning, as it is flexible, interactive, and content–rich in nature. This research was aimed to develop an English listening comprehension model by using Social Media You tube. A Research and Development methodology ADDIE was used: analyzing students’ and teachers’ needs, designing a new learning materials, Developing material, Implementing it in a group, and evaluating the existing learning materials, validating the learning materials by experts, revising learning materials, trying out the learning materials, and revising learning materials. It was found that the existing learning materials were not appropriate for the students’ characteristics and were not organized in a systematic way. Students and lecturers indicated that they appreciated enjoyable English language learning materials such as songs, stories and games using You Tube. Based on these findings a new model for developing materials was developed for English Listening Comprehension Program at the Islamic University of Riau.
An intelligent video-monitoring system to detect responsive behaviours associated with Alzheimer’s disease and related disorders

BackgroundResponsive behaviours affect 90% of older adults with Alzheimer's disease and related disorders.They have significant consequences including decreased functional independence and quality of life for older adults living in long-term care facilities.An intelligent video-monitoring system (IVS) is being developed to detect responsive behaviours, document their causes and alert health-care professionals to ensure immediate intervention.Purpose To test the IVS's efficacy for responsive behaviour detection.Methods Two occupational therapy students completed a simulation study in an apartment-laboratory under the supervision of experts in gerontology (clinicians, researchers).Four responsive behaviours (aggressiveness, apathy, motor behaviours, vocal behaviours) were realistically replicated across six scenarios, and five were repeated under three different luminosity conditions (total: 16 scenarios).The IVS detects responsive behaviours based on unusual movements or screaming in a specific location.To assess its detection capacity, the scenarios were divided into actions to record true and false positives (TP, FP), and true and false negatives (TN, FN).Sensitivity and specificity were then calculated.The quality of sound, images, and alerts was also analysed.Findings Seventeen TP, two FP, 42 TN, and three FN were recorded, generating an overall sensitivity of 85% and specificity of 95%.Sensitivity and specificity of 100% were obtained for apathy and aggressiveness scenarios.Motor behaviour scenarios achieved a sensitivity of 75% and specificity of 84%, and verbal behaviour scenarios obtained a sensitivity of 50% and specificity of 100%.With this IVS, the quality of the images was satisfactory, but the sound recording was poor.Alerts were received on average 32.4 seconds after detection.Discussion The IVS is an innovative technology that can contribute to responsive behaviour management by immediately detecting such behaviours and helping identify their causes (by recording the previous 30 seconds).These results validate the IVS's potential for responsive behaviour detection before its use is explored in real contexts.
Improved Candidate Generation for Pedestrian Detection using Background Modeling in Connected Vehicles

Pedestrian detection is widely used in today's vehicle safety applications to avoid vehicle-pedestrian accidents.The current technology of pedestrian detection utilizes onboard sensors such as cameras, radars, and Lidars to detect pedestrians, then information is used in a safety feature like Automatic Emergency Braking (AEB).This paper proposes pedestrian detection system using vehicle connectivity, image processing and computer vision algorithms.In the proposed model, vehicles collect image frames using on-vehicle cameras, then frames are transferred to the Infrastructure database using Vehicle to Infrastructure communication (V2I).Image processing and machine learning algorithms are used to process the infrastructure images for pedestrian detection.Background modeling is used to extract the foreground regions in an image to identify regions of interest for candidate generation.This paper explains the algorithms of the infrastructure pedestrian detection system, which includes image registration, background modeling, image filtering, candidate generation, feature extraction, and classification.The paper explains the MATLAB implementation of the algorithm with a road-collected dataset and provides analysis for the detection results with respect to detection accuracy and runtime.The algorithm implementation results show an improvement in the detection performance and algorithm runtime.
Alternative and traditional indicators of the Brazilian Feminist Studies Journal

The connection of traditional and alternative indicators of academic impact has been recommended by scholars in the field of metric studies as they are considered complementary and offer a more complete picture of the evaluation of research results. From this perspective, the present descriptive exploratory study aimed to analyze the correlation coefficient between the traditional and alternative impact of Revista Estudos Feministas. The sample comprised the period from 2001 to 2018. Analysis data were obtained from the Dimensions database via API. 1,296 texts with 2,609 citations and 5,982 altmetric data were analyzed. The results showed that Mendeley obtained a positive evaluation in the correlation of Pearson's coefficient when compared with the quantity of published articles and with the citation and visibility indicators. The study found that altmetric data is 4.6 times larger than traditional data, although fluctuating it is important for indicating the tools and networks where readers and users share scientific content.
Automaattinen asiasanoitus Radio- ja televisio-ohjelmatietokanta Ritvassa

National Audiovisual Institute’s (KAVI) radio and television archive started a joint project with the Finnish broadcasting company (Yle) and the National Library of Finland to develop automated indexing using program subtitles as a source. Project relies on Annif tool originally developed by Osma Suominen. Annif is built upon a combination of existing natural language processing and machine learning tools. It is designed to be multilingual and it can support any subject vocabulary.&nbsp; Annif can use several different backends. During the spring and summer of 2019, 313 Yle programmes were jointly annotated by KAVI and Yle for Annif testing. Analysis was made using a cross-validation technique. It was noted that television programme may be produced so that the central theme is not mentioned at all.&nbsp; When a brief programme description was included, the results improved. Results and quality were promising and the project will continue.
Point Supervised Extended Scenario Nuclear Analysis Framework Based on LSTM-CFCN

Cells and cell like particles detection and segmentation are of significant interest to many biological and clinical studies. Traditionally, these tasks are usually performed by visual inspection, which is time consuming, labor intensity and prone to induce subjective bias between different people. These make automatic cell analysis protocols essential for large-scale and objective studies. In recent years, imaging technical has been significantly advanced following the great success by computer vision. In addition, these technologies enable the cross module microscopy analysis, and make the task of cell analysis extremely challenging. Over these decades, computer aided cell detection, counting and segmentation have evolved from earlier filter based methods to the state-of-art deep learning protocols. However, there are still few suitable frameworks that can process multiple source cell images at the same time. In this paper, we seek a different route and propose a novel efficient framework for robust cell analysis based on Long Short Term Memory Channeled Fully Convolution Neural Networks (LSTM-CFCN). The results demonstrates that our framework is able to perform most of cell detection, counting and segmentation tasks from different cell type, and it can also cover most kinds of microscopy images scenarios including dark field, bright field, pathological and electron images. We have perform substantial experiments on several benchmark datasets, the LSTM-CFCN achieves the highest or at least top-2 performance in terms of F1-score, compared with other state-of-the-art methods.
PEMBELAJARAN BERBASIS KOMPUTER MENGGUNAKAN MS. OFFICE 2019 PADA SISWA DI SMK DWITUNGGAL 1 TANJUNG MORAWA

The work world related to office administration, mastery of Microsoft Office is needed as an office administration work tool that must be mastered by vocational students. However, students of SMK Dwitunggal 1 Tanjung Morawa hasn’t been maximal in mastering Microsoft Office 2019, especially in making mail merge on Ms. Word. They are only limited to know the use of Microsoft Office 2019 in the basic stages. Community Service Activity aimed to provide training on introduction of Microsoft Office 2019 computer applications in making mail merge on Microsoft Word to students of SMK Dwitunggal 1 Tanjung Morawa majoring in Office Management. The method used in this service activities were the tutorial, the question and answer, and the practical method. This activity was done well and gained the expected results. The result of this activity was students’ improvement in the ability and skills of making mail merge for letters, certificates and labels using Microsoft Office 2019. It hoped that Students of SMK Dwitunggal 1 Office Management Department understands to create mail for letters, certificates and labels, and if they follow Competency Test for their mail merge material, they can pass and get a Competency Certificate that is given by the State.
Information Security Behaviors among Employees

Information Security is crucial to organization especially to financial and industrial when dealing with company information and data.Information Security is defined as protecting the information and information system from unauthorized access, use, disruption, modification, disclosure, or also the destruction which to provide the confidentiality, availability, and integrity of the information.Information Security role as protecting the information and systems that covers compliance which involves data protection and publication scheme, and Information Management for Corporate Records, Copyrights and Intellectual Property.In this fast-changing world today, mobile technologies in information age nowadays have the ability and advance functions of computers and connectivity.In everyone's daily life, technologies have become integral and ubiquitous without their realization and user is vulnerable to the cyber-attack.Criminal hackers are attracted to steal personal and organization information.Thus, corporate data must be prevented from being transferred to personal application whether it is on personal devices or computer networks.As for organization, information and data are crucial for their organization plan, business conducts and future successfulness.This article will discuss issues, awareness, types of behavior, compliance and policies regarding information security.
Improving Photovoltaic Panel (PV) Efficiency via Two Axis Sun Tracking System

In this paper two axis sun tracking method is used to absorb maximum power from the sun's rays on the solar panel via calculating the sun’s altitude and azimuth angles, which describe the solar position on the Iraqi capital Baghdad for the hours 6:00, 7:00, 8:00, 9:00, 12:00, 15:00 and 17:00 per day. The angles were calculated in an average approach within one month, so certain values were determined for each month. The daily energy achieved was calculated for the solar tracking method compared with the fixed tracking method. Designed, modeled and simulated a control circuit consisting of reference position truth table, PI Controller and two servomotors that tracked the sun position to adjust the PV panel perpendicular on the rays of the sun. The results obtained by a simulation software MATLAB/Simulink.
Designing BIPA’s Teaching Material: Inserting The Local Wisdom?

&lt;p class="AbstractText"&gt;This study aims to explain the teaching materials used and needed in BIPA &lt;em&gt;(Bahasa Indonesia bagi Penutur Asing)&lt;/em&gt; learning and to develop BIPA teaching materials based on local wisdom as pedagogical content knowledge at Tidar University. BIPA Learning at Tidar University is facilitated by the Integrated Service Unit for Language Centre. BIPA learning at University Tidar is still relatively new and still requires further research to find out the needs of foreign learners studying here. Teaching materials that have been used need to be developed by paying attention to local wisdom as pedagogical content knowledge, generally in Indonesia and specifically in Magelang, so that learners have a better understanding about the concept of Indonesian language by paying attention to the values or characters contained in the learning material. This research uses research and development methods (Research &amp;amp; Development). The subjects of this study were BIPA instructors and learners at Tidar University. The object of this research is the BIPA teaching materials document which will be developed using the local wisdom base as pedagogical content knowledge. Data collection techniques used in this study are questionnaire and interview techniques. The findings show that teaching material for the local wisdom as the pedagogical content knowledge is important to be inserted in BIPA teaching and learning process. &lt;/p&gt;