Reviewerly/exHarmony huggingface dataset:
RFID-based Real-time Localization System Enhancement for Retained Surgical Instrument in the Body: A Preliminary Case Study

Retained surgical items are classified as preventable medical errors that cost the United Statesapproximately $17 to $29 billion each year and is the most frequently reported sentinel event in 2011 asreported by the Joint Commission. This research proposes a new approach to decrease such preventablemedical errors by developing a Radio Frequency Identification-based Real Time Locating System (RTLS)for surgical operations (RfSurg). Patient safety concern, e.g. the excessive exposure of x-ray to the patientafter the surgery, is a major motivation behind the need of RTLS in this research. The use of RTLStechniques in this research may eliminate the need of the x-ray procedures and improve the time neededto find surgical equipment retained in the body. The results obtained from this non-clinical research haveproven that the RFID-based RTLS is able to preliminarily answer the research question of: “If the surgicalequipment is detected in the patient’s body, can it be located in a timely fashion during surgery?” Thisnon-clinical study can be extended to further efforts for prototyping RfSurg with regard to its currentlimitations, e.g. elaborating some explanatory factors that could explain their relationship to thelocalization error.
Automatic content-based image retrieval using hierarchical clustering algorithms

The overall objective of this thesis is to present a methodology for guiding adaptations of an RBF-based relevance feedback network, embedded in automatic content-based image retrieval (CBIR) systems, through the principle of unsupervised hierarchical clustering. The main focus of this thesis is two-fold: introducing a new member of Self-Organizing Tree Map (SOTM) family, the Directed self-organizing tree map (DSOTM) that not only provides a partial supervision on cluster generation by forcing divisions away from the query class, but also presents an objective verdict on resemblance of the input pattern as its tree structure grows; and using a base-10 Genetic Algorithm (GA) approach to accurately determine the contribution of individual feature vectors for a successful retrieval in a so-called "feature weight detection process." The DSOTM is quite attractive in CBIR since it aims to reduce both user workload and subjectivity. Repetitive user interaction steps are replaced by a DSOTM module, which adaptively guides relevance feedback, to bridge the gap between low-level image descriptors and high-level semantics. To further reduce this gap and achieve an enhanced performance for the automatic CBIR system under study, a GA-based approach was proposed in conjunction with the DSOTM. The resulting framework is referred to as GA-based CBIR (GA-CBIR) and aims to import human subjectivity by automatically adjusting the search process to what the system evolves "to believe" is significant content within the query. In this engine, traditional GA operators work closely with the DSOTM to better attune the apparent discriminative characteristics observed in an image by a human user.
Automatic Navigation of Mobile Robot Based on Wheel’s Encoder and Predefined Map

Recently, the automatic movement of mobile robots has played a very important role in the advancement of technology. Automated mobile robot path determination is one of the most important challenges in the science of technology. This paper proposed a path planning method for wheeled mobile robots based on a real time calculation of a predefined distance on a certain map to enable the mobile robot to navigate at indoor areas according to the calculated distances and angles on the paths. The proposed system uses two wheels’ car as a prototype with two optical encoders to determine the number of wheel’s rotations, in order to calculate the needed distances and angles between two points on the navigation path. The system was controlled by a microcomputer Raspberry Pi, programmed using python programming language. The experimental results show an accurate distances and angles measurement for the navigation under a suitable condition.
Plant Parts and Their Functions Visualized Through E-Storybook Learning Media: Is It Feasible?

Online learning due to the Covid-19 pandemic raises problems for students due to the lack of learning media that supports the learning process. This research aims to know the design of the media and know the feasibility of E-Storybook learning media on plant parts material and its function in the science content of Grade IV Elementary School. The ADDIE development model is the model used in this study. This research stage consists of analysis stage (Analyze), design stage (Design), development stage (Development), implementation stage (Implementation), and evaluation stage(Evaluation). The subject of this study is the learning medium E-Storybook. Data collection techniques using questionnaire methods. The data collected in quantitative descriptive analysis and qualitative descriptive data analysis. Product validation is done by 3 experts, namely learning content experts, learning design experts and learning media experts. The results showed that the average validity score of content experts is 92% with excellent qualifications, the average validity score of learning design experts is 93% with excellent qualifications, the average score of learning media experts is 95% with excellent qualifications and the average result of 3 respondents is 92.7% with excellent qualifications. Thus the learning media of E-Storybook has been declared eligible for use in online learning.
PENINGKATAN KETERAMPILAN MENULIS TEKS BERITA DENGAN MENGGUNAKAN MODEL EXAMPLES NON EXAMPLES

This research report is motivated by 1) The process of learning Indonesian, especially aspects of writing skills in Class VIII A, SMP Negeri 1 Sekaran is still not satisfactory enough. The average score on the aspect of writing is still below the standard set at the beginning of the semester. 2) This requires the teacher to do remidial, however, sometimes the implementation of remedial is only a formality. Remedial is not done properly. Remedial is only done as a process of raising a child's value from a condition under minimal completeness to a condition of achieving minimal completeness. Research reports on learning to write news texts using the cooperative learning model Examples Non Examples through group assignments and individual assignments, researchers have done for up to two cycles. In each cycle there are four phases, namely (1) planning BP, (2) carrying out BP, (3) carrying out observations, and (4) making reflections. The four phases are planned and implemented to improve students' ability to write news texts through group assignments, and individual assignments using the Examples Non Examples model. The phases in the first cycle are designed as a result of reflection on daily learning activities. While the phases in the second cycle are designed from the results of the reflection of the first cycle, in this way it is expected that in the second cycle all students improve their ability to write news text with the Examples Non Examples model. From the results of the analysis of each cycle, it can be seen student learning outcomes have increased. In the pre-mastery stage students only scored 61% or enough categories, then in the first cycle the completeness value obtained by 72% was still sufficient category, at this stage increased by 11%. Then in cycle II the value of students' mastery learning increased even better than the first cycle, which is 89% and is included in the excellent category. In other words an increase of 27%, the 85% complete limit has been exceeded.
AghaKouchak, Artemyev, Fischer, Macdonald, and van Sebille Receive 2019 James B. Macelwane Medals

Amir AghaKouchak, Anton Artemyev, Emily V. Fischer, Francis A. Macdonald, and Erik van Sebille were awarded the 2019 James B. Macelwane Medal at AGU’s Fall Meeting 2020 Honors Ceremony on 11 December 2019 in San Francisco, Calif. The medal is for “significant contributions to the geophysical sciences by an outstanding early career scientist.”
Technology of Problem Education in the Training of Vocational Education Teacher

More and more stringent requirements are imposed on the training of a vocational education teacher. Therefore, there is a need to search for technologies that would meet the requirements of the state and society. One of these technologies is the problem learning technology. The purpose of the article is to consider the main aspects of educational technology implementation in the preparation of a vocational education teacher to form his professional competence. The article demonstrates the essence of problem-solving technology in education, reveals the levels of solving the problem task and describes the steps for students to solve the problem situation. The case method, the project method, the dialogue method, and the research methods are identified as the methods used in technology of problem-based learning implementation.
PEMAHAMAN MEMBACA NASKAH BERITA DENGAN MENGGUNAKAN METODE KOOPERATIF STAAD PADA MATA PELAJARAN BAHASA INDONESIA

ABSTRACTThe choice of the problem of classroom action research is based on the fact that students' ability to read news texts is still very low. Whereas with the mastery of Indonesian language lessons in general students do not have difficulty learning other subjects. This research was conducted in July to November 2015, because in those months the students had completed the first semester of the general exam and were still at the beginning of the second semester so that the students' conditions could be observed from the beginning.Cooperative Method STAD is a learning method wherein the learning process teaches the teacher to invite students to work together in groups to complete assignments in the classroom and allow students to find information on information that can be traditionally told or disguised.From this writing it can be concluded that with the motivation in learning STAD cooperative learning methods the students' ability to read news scripts increases and learning outcomes will be optimal. The more precise the motivation given, the more successful the lesson will be. With high motivation, the intensity of student learning efforts will also be high. So motivation will always determine the intensity of student learning. This will improve student understanding.Keywords: Reading News Scripts, Cooperative STAD
Additional Properties of Natural Numbers

In this chapter, we will introduce exponentiation and root of order n of natural numbers. We will then derive general properties of exponentiation and nth root. We will also introduce standard notations that are used with these operations.
Analysis of user Awareness for Saudi State Mobile Applications

In this article, we analyze the perception of Saudi state application users about password selection from real-world data. A total of 1,082 participants provided information about their behavior on state applications. The study extracts useful information related to the users’ weak practices. The findings include useful information representing thousands of minds and individual behaviors in using state applications. As a contribution to the area, it is found that the state applications were developed properly regarding security practices. However, users still represent the weakest party, and they are not aware of the proper practices they should follow. Thus, extensive effort is required to be spent on user education. On the other hand, the diversity of state applications may represent an extra effort to users in the way that they have separate passwords for each application, which makes a unified login portal for all the state applications the appropriate solution.
Software-hardware analysis of signal feature classification algorithms

Over the last few decades, signal feature analysis has been significantly used in a wide variety of fields. While several techniques have been proposed in the area of signal feature extraction and classification, all of these techniques are achieved by using modern computers, which rely on softwares, such as MATLAB. However, in real-time applications or portable devices, software implementation is not enough by itself, and a hardware-software co-design or fully hardware implementation needs to be considered. The selection of the right signal feature analysis tool for an application depends not only on the software performance, but also on the hardware efficiency of a method. However, there is not enough studies in existence to provide comparison of these signal feature extraction methods from the hardware implentation aspect. Therefore, the objective of this thesis is to investigate both the hardware and algorithmic perspectives of three commonly used signal feature extraction techniques: Autoregressive (AR), pole modeling, and Mel-frequency Cepstral coefficients (MFCCs). To fulfill this objective, first, the hardware analysis of AR, pole modeling, and MFCC feature extraction methods is performed by calculating the computational complexity of the mathematical equations of each method. Second the FPGA area usage of each feature extraction methods is estimated. Third, algorithmic evaluation of these three methods is performed for audio scene analysis. Once the results are obtained from the above stages, the overall performance of each feature extraction method is compared in terms of both the hardware analysis and algorithmic performances. Finally, based on the performed comparison, pole modeling feature extraction approach is proposed as the suitable method for the audio scene analysis application. The suitable method (pole modeling feature extraction) + linear discriminant analysis (LDA) classifier are implemented in Altera DE2 Board using Altera Nios II soft-core processor. The audio classification accuracy obtained using this implementation is achieved to be equal to the MATLAB implementation. The classification time for one audio sample is determined to be 0.1s, which is fast enough to be considered as a real-time system for audio scene analysis application.
An efficient trapezoidal compression algorithm using wavelet transformation for medical image

Image compression processes moderate the number of bits essential to signify an image, which can improve the performance of systems during storage and transmission without compromising image quality. They are classified into lossy compression and lossless compression. In this work, a new algorithm called trapezoidal algorithm has been proposed for image compression. The encoding part of proposed algorithm is like trapezoid shape so it is named as trapezoidal algorithm. Two transformation techniques DWT, IWT with three wavelets such as Haar, Sym4 and Coif1 have been combined for image compression to confer good characteristics of these methods. In this each pixel coordinates are encoded using the logic from SPECK algorithm. In SPECK, the set S is encoded when the pixel level is reached whereas in proposed algorithm (trapezoidal) the set S is encoded when the size of set S is reached 4x4. The approximation of image is named as set S. set S can be formed into three subset termed as s1, s2, s3. S is grouped into many subsets each set can be defined based on a pattern of proposed algorithm. Magnetic Resonance Imaging (MRI) of brain and Computer Tomography (CT) of lung images are used for analyzing compression. The proposed algorithm gives high PSNR compared to existing algorithms EZW, SPIHT and SPECK. The performance metrics such as Peak signal-to-noise ratio (PSNR), Structural Similarity Index (SSIM), Mean square error (MSE), Bits Per Pixel (BPP), Compression Ratio (CR) and Compression Time (CT) are measured for lung and brain images. The dataset has been collected from various scan centers.
Chapter 16: Scalable Clustering Algorithms

Given a data set with n records in a d-dimensional space, the cost of applying a clustering algorithm to partition the data set into k clusters is a function of n, k, and d. In the situation that n is large but k is small and the situation that both n and k are large, scalable clustering algorithms are needed. In this chapter, we will review and present some algorithms these situations.
Fighting phishing

Computer Fraud & SecurityVol. 2019, No. 7 RegularsFighting phishingRoger A GrimesRoger A GrimesKnowBe4Search for more papers by this authorRoger A GrimesPublished Online:6 Nov 2021https://doi.org/10.1016/S1361-3723(19)30076-4AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareShare onFacebookTwitterLinked InEmail View article FiguresReferencesRelatedDetails 1 January 2019Volume 2019Issue 7ISSN (print): 1361-3723ISSN (online): 1873-7056 Metrics History Published online 6 November 2021 Published in print 1 January 2019 Information© MA Business Ltd.PDF download
ІНФОРМАЦІЙНЕ МОДЕЛЮВАННЯ В ПРОЦЕСАХ ІНФОРМАЦІЙНОГО ЗАБЕЗПЕЧЕННЯ ОРГАНІЗАЦІЇ

&lt;p&gt;&lt;strong&gt;&lt;em&gt;The purpose&lt;/em&gt;&lt;/strong&gt;&lt;em&gt; of the research is to build an information model of information resources of the institution for the vehicle drivers training, to analyze the effectiveness of the information resources use in the context of information support for driver training. &lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Research methodology.&lt;/em&gt;&lt;/strong&gt;&lt;em&gt; To build an information model of information resources of the institution for the vehicle drivers training the following methods were used: analysis, description, generalization, classification, information modeling. &lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Results.&lt;/em&gt;&lt;/strong&gt;&lt;em&gt; The information resources used in the activities of the institution for the vehicle drivers training were analyzed. The information resources of the institution were divided into traditional and electronic, internal and external. Among the main information resources that form the information flows of the institution are the organizational and administrative documentation of the institution, the information automated system «Driving School» workstation, the institution’s website, page and groups on social networks, external electronic information resources of government bodies on legislative and regulatory information, website of the information automated system’s developer regarding technical support of the «Driving School» workstation. The construction of a figurative-symbolic information model in the form of a scheme containing a combination of graphic and textual elements was carried out. &lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Novelty.&lt;/em&gt;&lt;/strong&gt;&lt;em&gt; Building an information model of information resources of the institution for the drivers training helped to identify features and some gaps in the information support of the institution, the appropriate level of which serves to ensure transparency and openness of its activities in accordance with current laws, regulations and technologies.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Practical significance.&lt;/em&gt;&lt;/strong&gt;&lt;em&gt; The main types of information resources that have a decisive influence on the activities of the institution for the vehicle drivers training were identified. Analysis of the state of use of these information resources can be used in the process of conducting a regular information audit of the institution. &lt;/em&gt;&lt;/p&gt;&lt;strong&gt;&lt;em&gt;Key words:&lt;/em&gt;&lt;/strong&gt;&lt;em&gt; information model, information resource, information modeling, automated information system, electronic document management. &lt;/em&gt;
GUI Control with Head Gesture

Face detection based mouse movement is one of the important works for the physically challenged people. The movement of head can notify the computer specific task. By understanding, the disabled people computer can pass message to other person and that can help disabled to notify others the urgent need of them. In this project, an application has been built which will help the people who do not have any control of their hands but they can only move their head. In this work, OpenCV based Haar-like feature extraction has been used to detect face. By using face detection algorithm, faces as well as non-faces are classified as faces. So, to reduce the false positive results, face detection algorithm has been enhanced. After face detection, mouse movement has been controlled with the coordinate of face movement.
A Semantic Recognition Method of Radiotelephony Communication for Apron Controller based on Deep Learning

With the rapid development of China's civil aviation industry, the security and efficiency of airport operation is necessary to improve.Apron control transfer has become a trend at the China airport with 10 million throughputs.However, there is lack of specific research on semantic recognition of apron controller's ground air calls.This paper firstly establishes the framework of apron control semantic recognition.Then it analyzes the structure and content characteristics of apron control ground air call.The feature template of key instructions is extracted based on data from Urumqi airport.Finally a deep learning method is used to achieve semantic recognition of apron controller under special circumstances.The simulation results verify the effectiveness of the model.
CAREER SELF-DETERMINATION OF UNDERGRADUATE STUDENTS

The article focuses on the problem of career self-determination of the individual, his readiness for rapid changes in career strategy in the conditions of super-dynamic transformations in the labor market. In theoretical terms, the phenomenon of career self-determination of an individual is considered in relation to the established category of «professional self-determination» in Russian science, the concepts «career», «career strategy», «career competence». The importance of the period of professional education as the basic stage of a career for the formation of the image of a future career and personal prerequisites for career self-determination is indicated. The results of the empirical study of some aspects of career self–determination of undergraduate students – future teacher-psychologists and psychologists are presented. In a local study, students recorded an average level of career self-determination with predominance of internal motivation for future professional activity. Contrary to the opinion about the dominance of utilitarian motivation for work among young people, the perspective reflection of psychology students shows a small amount of «high income» and «vertical career type» (official promotion), they are rather aimed at a «horizontal career» – promotion to professionalism. The analysis of data obtained from the samples of the 1st and 4th years of training did not reveal statistically significant differences, but the indicators of 4-year students at the average level of the sample are higher in certain parameters (certainty of professional choice, satisfaction with professional choice, desire to build a career in the chosen professional field, the presence of personal meanings in future professional activities, stability of career orientations). However, data from a sample of 4-year students indicate a lack of internal consistency of personal and professional perspectives and difficulties in making career decisions.
Chatbots

Chatbots provide a way to build a conversation application between a human and an application using a defined data source. Chatbots are often used in web-based customer service areas to answer common questions as they can simulate human communication and interact intelligently through a dialog with a human. This kind of interaction works best where the questions are likely targeted to a specific topic, for example, restaurant reservations or standard ordering-related questions. When chatbots work well, people interacting with them may not even realize they are not talking to a person.