Reviewerly/exHarmony huggingface dataset:
Comparison and Validation of Fast Organ Detection Methods on Ultrasound Images Using CNN

We are developing a system to treat kidney, liver and other organs, as well as stones and cancer in these organs using high-power focused ultrasound (HIFU) while tracking lesions that move by breathing and body movements. The system estimates organ movement by analyzing ultrasound images obtained from the probe and compensates for this movement with robotic control. In recent years, various medical image analysis methods using deep learning have been proposed and studied, but they have not been fully explored as methods to detect specific organs using robotic systems. In this paper, we compared and validated the performance of Faster R-CNN, which is commonly used for object detection, and the proposed methods, Regression Network (RegNet) and Segmentation In Regression Network (SegInRegNet), the proposed method based on the problems of Faster R-CNN, in a kidney detection task. And then, we show that 1) there are some problems with Faster R-CNN as a kidney detection method operating on a robotic system and that 2) proposed method performs better than Faster R-CNN in terms of detection speed and accuracy.
The Effect of Mobile User Typology on Mobile Learning Adoption in Higher Education

Mobile user typology is absent from popular models for mobile learning adoption though understanding such typology can help with design of learning. This paper explores the salient mobile user typology by applying latent class analysis to reported use of mobile phone features collected from students at six university campuses in four countries (Barbados, Guyana, Jamaica, Trinidad and Tobago). It also relates the user types to behavioural intention to adopt mobile learning within a structural equation modelling framework. The results indicate four mobile user types which are distributed differently over the campus-territory groups and to which age, sex, programme level and programme type of the students are significantly related. Furthermore, mobile user typology is related to behavioural intention to adopt mobile learning and this avails it as a candidate for inclusion in models used for mobile learning adoption. There is some extent of cross-national specificity of mobile user typology though some user categories seem to be more generalisable
Analysis of Design Paradigms based on Technology Features at Galeri Indonesia Kaya

Abstract This study aims to determine the design paradigm at the Galeri Indonesia Kaya (GIK). The paradigm shows how the orientation of a museum in utilizing digital media for delivering information. Knowing the design paradigm is useful for GIK to be more effective in developing ways of conveying messages and how to structure the narrative system. There are three experience design paradigms, namely user-centered experience design, participatory experience design, and agile experience design. GIK is chosen as the object of study because it is a museum that mostly uses digital media. The analysis is done descriptively using data collection methods based on direct observation. This study finds that GIK has a user-centered experience design (UCD) paradigm. This is indicated by the GIK features that fulfill the character of the paradigm. The conclusion in the narrative systems is GIK has an open system that makes visitors have to actively get information but GIK has not been able to make visitors reinterpret information or participate in providing a new information. Beside, with the technology features, GIK has the potency to shift to participatory experience design paradigm and become a democratic museum.
USE OF VIBRATION SENSOR AS DETECTION OF RAILWAY IN MECHANICAL SIGNALING SYSTEMS

Interlocking equipment used to secure a system. One of the systems on mechanical signalingthat is contained in trains. Mechanical signaling is used to form, lock, and control so that thesystem is safe from errors that occur in the system. In the world of railroad signalingmechanically it is very much needed so that the train route remains on the correct and safelane. The railroad to be traversed by the train is carried out mechanically. The developmentof electronic technology can have an impact on railroad signaling. So that the application ofelectronic technology can be done on railroad signaling in Indonesia. Rail contact,mechanical is signaling that is used to detect the presence of trains. Equipment rail contacts,to detect the presence of facilities on the railway line at the emplacement. The way railcontacts work uses an iron lever that is in direct contact with the rail wheels so that themovement of the lever causes the switch in the device to be active. Levers that are oftenstepped on by the train's wheels cause wear. A worn lever causes the level of precision toweaken, making it unsafe for trains to be on the right track. The application of electronictechnology, a microcontroller, can replace the worn lever. The SW-420 sensor as a vibrationdetector is integrated with a microcontroller to determine the presence of a train. This sensorcan be applied as a train detector by utilizing vibrations on the rails. From the results of trialsconducted, the system with sensors that are built can detect rail vibrations when the railroad 403stepped on the rail. So that train movement can be detected, and the microcontroller can showthe vibration value data in realtime.
SEPSIS DIAGNOSIS SYSTEM using MACHINE LEARNING

The timeliness of detection of a sepsis incidence in progress is a crucial factor in the outcome for the patient. Machine learning models built from data in electronic health records can be used as an effective tool for improving this timeliness, but so far, the potential for clinical implementations has been largely limited to studies in intensive care units[3]. This study will employ a richer data set that will expand the applicability of these models beyond intensive care units.
Basic Concepts of Algebra in Deep Learning

Algebra is extremely important for understanding Machine Learning, especially for Deep Learning. They provide you better feeling for a way algorithms really work under the duvet, which enables you to form better decisions. You would wish to be an expert during this field; you can't escape from mastering of its concept. During this topic we'll give the foremost important concept of algebra that are utilized in Deep Learning.
Design and Development of Activity Management at The mosque An-Nur Dinamika University

An-Nur Mosque is a University of Dinamika Mosque that was established in 2002. An-Nur Mosque, Dinamika University Institute of Business and Information with a capacity of pilgrims that can accommodate as many as 300 people. UKKI stands for Islamic Spiritual Activity Unit. UKKI is an organization which serves as the mosque of An-Nur. UKKI is a unit of activity that operates on the University of Dinamika campus in the area of special religion of Islam or of course. Based on interviews and observations with takmir, one of the problems that occurred was that there was no recording of the results of the meeting so that the discussion of the meeting was not monitored the results and the discussion was repeated, Lack of publication of information so that no new students registered to take part in the SII. Lack of information dissemination through publications from various media such as posters, banners, and oral.Based on permaslahan above, the An-Nur Mosque University of Dinamika Surabaya must have a system for the process of managing An-Nur Mosque activities related to information on the schedule of activities and financial processing of the Mosque. Then the right solution is how to design and build an application that can inform the activities of An-Nur Masjid Dinamika Surabaya University activities, conduct financial processing and report making so that the manager can monitor and know the financial condition of the mosque for the evaluation of further activities.
An Empirical Analysis of Preprocessing Tasks for Unstructured Data

Nowadays computing systems are able to learn, reason, hear and see. Enormous amount of new opportunities are created by artificial Intelligence. Artificial Intelligence has given two promising technologies. One such technology is NLP. Text Mining is also a promising area. These technologies enable and empower users to transform/map the key content in texts lying in documents into quantitative insight or to draw conclusion. Document Classification using supervised and unsupervised learning has a huge list of applications. Soft computing techniques like fuzzy logic helps to find a practical solution. This work proposes a methodology which is found to be significant while clustering unstructured data. The empirical analysis is included to demonstrate the improvement in document representation by using sparsification. Experiments are conducted on 5500 emails. Proposed methodology showed a significant improvement in representation of unstructured data.
The use of innovative technologies VR, AR, 3D in museum pedagogy

The most important task of a teacher is to teach children to learn, and to interest modern students in learning is not easy, but possible. Innovative and computer technologies can become assistants, which allow not only to form students' knowledge, skills and abilities, but also to solve a more important task that arises before learning - to develop the student's personality, to satisfy his cognitive interests.
A template-based approach to automatic program repair of Sonarqube static warnings

As the prevalence of software continues to increase, so does the number of bugs. Static analysis can uncover a multitude of bugs in a reasonable time frame compared to its dynamic equivalent but is ...
COVID-19. Higher Education and Educational Technology Actions Performed to Reduce the Negative Effects

This essay analyzes the impact of COVID-19 in higher education based on national policies implemented during the current outbreak. Additionally, it enlists and discusses the proposed strategies developed to support higher education in a post-pandemic scenario based on educational and political perspectives.
Anomaly detection and classification in traffic flow data from fluctuations in the flow-density relationship

We describe and validate a novel data-driven approach to the real time detection and classification of traffic anomalies based on the identification of atypical fluctuations in the relationship between density and flow. For aggregated data under stationary conditions, flow and density are related by the fundamental diagram. However, high resolution data obtained from modern sensor networks is generally non-stationary and disaggregated. Such data consequently show significant statistical fluctuations. These fluctuations are best described using a bivariate probability distribution in the density-flow plane. By applying kernel density estimation to high-volume data from the UK National Traffic Information Service (NTIS), we empirically construct these distributions for London's M25 motorway. Curves in the density-flow plane are then constructed, analogous to quantiles of univariate distributions. These curves quantitatively separate atypical fluctuations from typical traffic states. Although the algorithm identifies anomalies in general rather than specific events, we find that fluctuations outside the 95\% probability curve correlate strongly with the spikes in travel time associated with significant congestion events. Moreover, the size of an excursion from the typical region provides a simple, real-time measure of the severity of detected anomalies. We validate the algorithm by benchmarking its ability to identify labelled events in historical NTIS data against some commonly used methods from the literature. Detection rate, time-to-detect and false alarm rate are used as metrics and found to be generally comparable except in situations when the speed distribution is bi-modal. In such situations, the new algorithm achieves a much lower false alarm rate without suffering significant degradation on the other metrics. This method has the additional advantage of being self-calibrating.
A Decentralized Dynamic PKI based on Blockchain.

The central role of the certificate authority (CA) in traditional public key infrastructure (PKI) makes it fragile and prone to compromises and operational failures. Maintaining CAs and revocation lists is demanding especially in loosely-connected and large systems. Log-based PKIs have been proposed as a remedy but they do not solve the problem effectively. We provide a general model and a solution for decentralized and dynamic PKI based on a blockchain and web of trust model where the traditional CA and digital certificates are removed and instead, everything is registered on the blockchain. Registration, revocation, and update of public keys are based on a consensus mechanism between a certain number of entities that are already part of the system. Any node which is part of the system can be an auditor and initiate the revocation procedure once it finds out malicious activities. Revocation lists are no longer required as any node can efficiently verify the public keys through witnesses.
UIKit in SwiftUI

There will likely be times for various reasons you’ll want to use UIKit in your SwiftUI app. No problem.
Research on Big Data Platform of Power Grid Enterprise Accounting Business Based on Cloud Computing Analysis

With the rapid development of digital technologies such as big data and cloud computing, smart grids have also made considerable progress. A large number of sensors are embedded in the existing power grid system, and modern information technology is used to control and monitor them. These sensors collect a large amount of data, and the existing traditional financial management system cannot process and analyze the huge data in a timely and accurate manner. This paper proposes the use of big data to process and analyze the accounting data of the smart grid, so that the financial system of the grid company can better serve the grid company. Hope to help grid companies in financial management.
One-Time Delegation of Unlinkable Signing Rights and Its Application.

Delegation of signing rights can be useful to promote effective resource sharing and smooth cooperation among participants in distributed systems, and in many situations, we often need restricted delegation such as one-timeness and unlinkability rather than simple full delegation. Particularly, one-timesness cannot be achieved just by deploying cryptographic measures, and one needs to resort to some form of tamper-proofness or the assistance from external cloud servers for “key-disabling”. In this work, we extend the latter such that a delegatee can sign a message without the delegator’s involvement with the assumption that there exists at least one honest cloud server with secure erasure to achieve one-timeness. In this setting, if the delegator just shares their signing key between the delegatee and cloud servers, it may be problematic. It is because in the worst case, the delegator cannot know whether or not a signing key theft occurred because the signatures generated illegally are indistinguishable from the ones generated legally. To solve this, first we propose an efficient one-time delegation scheme of Okamoto-Schnorr signing. Further we combine the basic delegation scheme with anonymous credentials such that the delegator can detect the signing key theft even if one-time delegation is broken while also achieving unlinkability for both the delegator and cloud servers. Further we show its application to an e-cash scheme, which can prevent double-spending.
Web based Motorcycle Social Gathering Information System

Abstract Information System Arisan Motor Website base aims to facilitate people who want to do social gathering (known as arisan), especially motorcycle social gathering. Where on this social gathering website can display the winning result accurately, because randomization is done by system. Making this website method uses the SDLC (System Development Life Cycle) method which is carried out in several stages, system planning, analysis system, system design, and system implementation. In this application program also uses tools that are Flowcharts, Data Flow Diagrams, Entity Relationship Diagrams, and Relationships Between Table. The database used is MySQL, the link between the database and the display of the program using XAMPP, the language of the program and the application used to manage the display is PHP. Testing on the motorcycle social gathering website uses the Black Box Testing and User Acceptance Testing (UAT) methods. The motorcycle social gathering website can display a report for the owner in the form of the most chosen motorcycle, the number of people who have registered, the financial report, and the salary report of the member that can be seen by the owner of the motorcycle social gathering website
A Self-Organising Multi-Agent Knowledge Base

Service-oriented architectures are often deployed in highly dynamic domains like Fog Computing. In such environments, centralised registries would introduce a bottleneck. We present the design of a self-organised, multi-agent-based distributed knowledge base. It supports non-monotonic reasoning, storage of semantically annotated knowledge, ontology-like queries, and fault-tolerance of partial failures of the system. Experiments with a prototype show its viability.
Pengembangan perangkat pembelajaran online untuk guru SMP

In the midst of this Covid-19 pandemic, our education system must be ready to make the leap to transform online learning for all students and by all teachers. We are entering a new era to build creativity, hone students' skills, and improve self-quality with changes in our systems, views and patterns of interaction with technology. Indonesia also faces some real challenges that must be sought immediately: (1) technological inequality between schools in major cities and regions, (2) limited teacher competency in the utilization of learning applications, (3) resource limitations for the utilization of Educational technologies such as the internet and quotas, (4) teacher-student-parent relationships in online learning that are not yet integral. The problem found is: (1) Teachers at SMP Muhammadiyah 1 Gamping still have limitations in utilizing technology as a learning aid to teach in the school. In addition, (2) the problem found is the lack of teacher skills in varying or developing online learning tools. The solutions offered are: (1) the team helps develop online learning tools. and (2) The team helped solve problems in the use of online learning devices in the learning process of teaching in the classroom.
INCREASING STUDENT’S VOCABULARY OF THE FIRST GRADE AT SMA NEGERI 3 TOLITOLI THROUGH WORDS ASSOCIATION GAME

The objective of the research is to find out whether the application words association technique increasing students’ vocabulary words association game or not. It is a True-Experimental research. It is conducted at first grade of SMA Negeri 3 Tolitoli that was (X MIA1). The writer gave a pre-test to measure the students previous ability in vocabulary words association after given treatment which is the application of words association game technique. The writer used SPSS 16.0 program to analyze the data collection. the result of data analysis showed that technique give a significant effect to the students’ in words association game. The mean score of the post-test (80,61) was higher than the mean score of pre-test (63,65). Then, the testing hypothesis showed that the value of t count (t c ) was greater than t table (t t ) (6.099 ≥ 2,017). In conclusion, The application of words association game technique is effective to increasing students’ vocabulary. Keywords: Increasing, Vocabulary, Words Association Game, Experiment
Sistem Informasi Monitoring Kenderaan Pengangkut Sampah di Kabupaten Gorontalo

Environmental And Natural Resource Agency remains experiencing a problem related to waste hauling from Temporary Waste Disposal Site (TPS) To Final Disposal Site (TPA). In addition, people living nearby the site complain about certain things such as workers cross by the garbage dump with piling up waste, workers haul the waste at an irregular time as determined, and workers take the wrong route incidentally based on their own reason. Objective of this research was to create a web-based apps system which could monitor trash hauling from Temporary Waste Disposal Site (TPS) to Final Disposal Site (TPA) in area of Limboto Sub-district, Gorontalo District. It was designed by applying prototype system development method. Result of research showed that the created waste Collection Vehicle Monitoring Information System in Gorontalo District could optimize search process for garbage dump provided by gorontalo district government.
Determinants of Current Account Deficit: Empirical Evidence from Ethiopia

The main objective of this study is to empirically investigate the determinants of current account deficits in Ethiopia using annual time series data ranging from 1975 to 2016. To investigate the long run and short run relationship between current account deficit and its determinants, Autoregressive Distributed Lag (ARDL) model or bounds testing approach to co-integration and Error Correction Model (ECM) are applied respectively. The results of the Augmented Dickey Fuller (ADF) test indicate that the variables under consideration are a mixture of integrated of order zero and order one, that is, I(0) and I(1). Moreover, the result of bounds testing confirms the existence of stable long run relationship between current account balance and its determinants. The empirical result reveals that net foreign asset, real effective exchange rate, terms of trade and real GDP are found to have a negative impact on current account deficit, while government budget balance positively affected current account deficit in the long run. However, inflation is found to be insignificant both in the short run and in the long run. The ECM also shows that, real effective exchange rate, terms of trade and inflation have no significant effect on current account deficit in the short run. As a policy implication, it is recommended that employing appropriate policy mix along with devaluation, diversification and improving the quality of exports and implementation of efficient tax administration system are among the policy options that are supposed to alleviate the existing current account deficit. Keywords : ARDL, Bounds testing, Current account deficit, ECM, Ethiopia DOI: 10.7176/RJFA/11-17-06 Publication date: September 30 th 2020
Text Cohesion in CQA - Does It Impact Rating?

Community Question and Answer (CQA) platforms are expected to provide relevant content that is not readily available through search engines. With an increase in the number of users and growth of internet, CQA platforms have transitioned from generic to domain specific systems. Expert rating, machine learning and statistical methods are being used for assessing the quality of answers. However, the research on importance of consistency as a quality parameter in the form of text cohesion in CQAs is limited. We extracted 109,113 CQAs from StackExchange related to Information Security of the last 8 years to evaluate text cohesion in answers. An empirical study conducted with 246 participants (Information Security Experts, Software Engineers and Computational Linguists) on the extracted answers stated that lack of text cohesion impacts the rating of answers in CQA. Software Engineers are seekers and viewers of answers, they responded to a survey that lack of text cohesion leads to difficulty in reading and remembering. Information Security Experts providing answers to CQA stated that they need text cohesion for understandability.