Reviewerly/exHarmony huggingface dataset:
Rethinking Trajectory Evaluation for SLAM: a Probabilistic, Continuous-Time Approach

Despite the existence of different error metrics for trajectory evaluation in SLAM, their theoretical justifications and connections are rarely studied, and few methods handle temporal association properly. In this work, we propose to formulate the trajectory evaluation problem in a probabilistic, continuous-time framework. By modeling the groundtruth as random variables, the concepts of absolute and relative error are generalized to be likelihood. Moreover, the groundtruth is represented as a piecewise Gaussian Process in continuous-time. Within this framework, we are able to establish theoretical connections between relative and absolute error metrics and handle temporal association in a principled manner.
A Survey on Fishy URL Detection Using URL Features and CNN

Phishing is a network type attack where the attacker creates the fake of an existing webpage to fool an online user into elicits personal Information. The prime objective of this review is to do literature survey on social engineering attack: Phishing attack and techniques to detect attack. NLP offers a natural solution for this problem as it is capable of analyzing the textual content to perform intelligent recognition and performing semantic analysis of text to detect malicious intent. In this type of cyber-attack, the attacker sends malicious links or attachments through phishing e-mails that can perform various functions, including capturing the login credentials or account information of the victim. This paper aims to provide a comprehensive and comparative study of various existing free service systems and research-based systems used for phishing website detection. The systems in this survey range from different detection techniques and tools used by many researchers.
A Fine-Grained Access Control Survey For The Secure Big Data Access

In this big data era, from different sources a large data can be quickly generated. Access controlling in big data which contains a large amounts data becomes a difficult and challenging task. As per the needs of end users, it is required to build some mechanisms of access control to share the confidential information of end user to a specific authorized user. The main issue in cloud is security for access control. Cloud systems are protected by access control from the security issues. At present Cloud concentrates on various latest researches and implementations, which assures the secured and reliable file transfers. The access controls based on role, attribute, identification and hierarchical based access controls are in existing solutions. These are not enough to trust the cloud computing servers. The further future aim is to secure the files in storage by implementing a trusted model. The main aim of this presented paper is to give a fine-grained access control survey for the secure big data access with others. Access rights are provided by access control, in order to subject exact for object entity set. A set of rights are provided for a certain authorized person is done by Fine grained access control..
Short versus long video-based lectures as a tool for faculty development during COVID-19 pandemic

With emerge of the COVID-19 pandemic, video-based lectures (VBLs) was widely used as an effective online faculty development tool. VBLs varies from short videos (5-minute) to the long one (1-2 hours). So, the current study aims to evaluate the effectiveness of long VBLs versus short VBLs. A total of 21 short (9) and long (12) VBLs were produced, in 2020, by the authors. The metadata for all of VBLs was downloaded from YouTube [VBLs overview data, audiences’ engagement data, and audience retention (AR) report]. The viewership data included the number of views (4800), watch time by hours (173.6), males to females’ ratio (79/21), the number of the subscribers (157), the video length (2.9±1.2 minutes), number of viewers (241.1±157.8), and the watch time (5.1±3.3 hours). The audience retention is presented as average view duration (1.1±0.4 hours) and average percentage view (42.8±7.9%). Lastly, audience engagement is represented by the number of subscribers (6.4±7.4), likes (9.7±8.0), and dislikes (0.3±0.7). The comparison of the mean audience retention and engagement between short and long VBLs showed that short VBLs had significantly higher number of subscribers and likes as well as the average percentage views in comparison to long VBLs. We could conclude that short VBLs are more effective and efficient as a regard audience retention and engagement. Moreover, the more use of advanced technology for video development makes it more engaging.
Location Prediction in Real Homes of Older Adults based on K-Means in Low-Resolution Depth Videos

In this paper we propose a novel method for location recognition and prediction in smart homes based on semi-supervised learning. We use data collected from low-resolution depth video cameras installed in four apartments with older adults over 70 years of age, and collected during a period of one to seven weeks. The location of the person in the depth images is detected by a person detection algorithm adapted from YOLO (You Only Look Once). The locations extracted from the videos are then clustered using K-means clustering. Sequence prediction algorithms are used to predict the next cluster (location) based on the previous clusters (locations). The accuracy of predicting the next location is up to 91%, a significant improvement compared to the case where binary sensors are placed in the apartment based on human intuition. The paper presents an analysis on the effect of the memory length (i.e. the number of previous clusters used to predict the next one), and on the amount of recorded data required to converge.
Immunophenotyping in Acute leukemias: First tertiary care centre experience from Punjab

Acute leukemia is a heterogenous group of disorders, require multidiscplinary approach for diagnosis and prognostication. Immmunophenotyping has emerged as important tool in diagnosis of hematolymphoid malignancies. Since, Punjab is emerging as cancer capital of India, with leukemia cases on the rise. The diagnostic modalities like flow cytometry need to be popularized and more medical fraternity is required to be familiar with this technique. Therefore we hereby present study from the state of Punjab focussing on leukemia patterns diagnosed by flow cytometry.Keywords: Leukemia, Diagnosis, Flow Cytometry, Punjab
PENINGKATAN KEAKTIFAN BELAJARDAN KETERAMPILAN MENULISTEMA WE LOVE WHAT WE DO MELALUI MODEL WHO AM I QUIZ PADA SISWA KELAS VIIH SMP NEGERI 1 TALANG SEMESTER GENAP TAHUN PELAJARAN 2019/2020

The Who Am I Quiz Learning Model is a learning model designed in such a way as to increase student learning activity and have implications for increasing writing skills. The purpose of this study was to improve student learning activeness and writing skills of class students. To strengthen and facilitate this study the authors used several accurate references. This study used two stages, namely cycle I and cycle II. Each cycle consists of planning, acting, observing, and reflecting. From the results of the study, the percentage value of student learning activeness in the first cycle was 56.25% in the active category and very active and increased in the second cycle, namely 93.63% in the active and very active category. While the average value of writing skills in cycle I was 66% and increased in cycle II to 76.3. Meanwhile, the percentage of completeness in the first cycle was 62.5% and increased in the second cycle to 93.75%. This improvement proves the success of descriptive text learning through the Who Am I Quiz learning model.
Using Project-Based Learning To Improve The Students’ Speaking Skills: An Action Research Project At Dong Nai Technology University

Nowadays, English becomes more and more important in almost aspects of life. English is a global language, so it is a compulsory subject at schools and universities. Communication is one of the most important skills in study, and work. Being a lecturer at a university, I recognize that we should help our students find the better way to improve their speaking skills and feel confident when talking or speaking in front of the class or the crowded or making a conversation with foreigners. After learning about some methods to help the students improve their speaking skills. We chose Project – based Learning to apply for our speaking classes in experiment. After doing this experiment, we found out two issues: (1) the students’ attitudes to using Project – based Learning in speaking classes; (2) the result of students in Speaking classes when applying Project – based Learning. I randomly chose a Class with class code 0070133 to carry out my action research project with the participants: 30 the first-year students a Dong Nai Technology University. We performed this study in 12 weeks and used questionnaires, pre- testing, post-testing and interviews for collecting data instruments. The research findings us that the students has positive attitudes to using Project – based learning in speaking classes and PBL was a good way to help students improve their speaking skills. With the result we got in the findings, both the lecturers and the students could find the own way for teaching and learning to achieve the best result in speaking skills in speaking classes.
Automatic Integrated Scoring Model for English Composition Oriented to Part-Of-Speech Tagging

Part-of-speech tagging for English composition is the basis for automatic correction of English composition. The performance of the part-of-speech tagging system directly affects the performance of the marking and analysis of the correction system. Therefore, this paper proposes an automatic scoring model for English composition based on article part-of-speech tagging. First, use the convolutional neural network to extract the word information from the character level and use this part of the information in the coarse-grained learning layer. Secondly, the word-level vector is introduced, and the residual network is used to establish an information path to integrate the coarse-grained annotation and word vector information. Then, the model relies on the recurrent neural network to extract the overall information of the sequence data to obtain accurate annotation results. Then, the features of the text content are extracted, and the automatic scoring model of English composition is constructed by means of model fusion. Finally, this paper uses the English composition scoring competition data set on the international data mining competition platform Kaggle to verify the effect of the model.
Analisis Hasil Elektroforesis DNA dengan Image Processing Menggunakan Metode Gaussian Filter

DNA gel electrophoresis plays an important role in the development of science. However, the process of manually analyzing DNA size is still relatively difficult, time-consuming, and often results an error. This study proposed electrophoresis process using image processing with Gaussian Filter method. Gaussian Filter is used to improve the quality of the image which makes the image clearer. The method was applied using python programming and then embedded into Raspberry pi 3 module. This modul processed images taken by Raspberry pi V1 camera. To realize these taken images, tracking mouse was used. All the images which had been processed were displayed on LCD touchscreen 5 inch. The result shows that the study using Gaussian Filter indicates good performance. This is proved by the lowest error percentage of 0,20% . In addition, compared to previous studies, the largest error percentage is still relatively smaller at 12.41%.
Developing Prezi Media to Enhance Students’ Short Story Writing Skills In Senior High School 3 Muhammadiyah Tangerang City

This research aims is to develop Prezi media to enhance students’ short story writing skills of class XI high school students in the city of Tangerang in the digital era. The method used in this study was research and development (RND). In the development process, this research used the Borg and Gall model. The results of the study were based on the results of the validation of five experts of Prezi learning media. It was obtained that the average of the validity is 85.2% or categorized as feasible. Validation of five short story writing skills experts in average of 86.8% or categorized as feasible. The Prezi media trials already conducted in several high schools in Tangerang. The average results of the Prezi media trial in the short story writing skills of class XI high school students in all Tangerang areas scored average of 78.6. In Senior High School 3 Muhammadiyah Tangerang City, the average score was 65,5 out of 20 students. To conclude, Prezi media is considered to be appropriate to enhance students’ short story writing skills in digital era.
Secure Data Distribution Systems And Improving Synchronization Efficiency In Cloud Computing

Now a day's Mobile cloud storage is most popular in the storage and Exchange of the Data .in the paper to identify, investigate and address the synchronization inadequacy problem of current mobile cloud storage services. In the Existing Synchronization, it fails to the available bandwidth. It generated a large amount of data. It unwanted data is Synchronization to create traffic. We implement the Quick Synchronization of the data using three different technique used to improve the Synchronization efficiency to any other services and its improve the performance of the Synchronization time to the system. Data is generating day by day in cloud computing data is saved on the cloud. So here we have to combine mobile computing with cloud computing so that we can handle the mobile-based application with the cloud platform. So when we store our data on the cloud. Here the existing commercial system fails to compose full use of obtainable Bandwidth and generate a large amount of superfluous traffic. It happens because of the inbuilt restrictions of the sync set of rules and the distributed architecture. The probable of selectively distribution encrypted data with dissimilar users via public cloud storage may seriously ease protection concerns over involuntary data leaks in the cloud. A key confronts to underhanded such encryption schemes trickery in the skillful administration of encryption keys. The favored limberness of distribution any group of preferred identification with any group of users demands different encryption keys to be used for dissimilar documents. However, this also entails the indispensable of self-assuredly distributing to users a large numeral of keys for both encryption and search, and those users will have to strongly store the conventional keys, and submit a uniformly large number of keyword trapdoors to the cloud in categorize to carry out appear for over the communal data. The roundabout needs for a sheltered announcement, storage, and complication undoubtedly render the move toward unworkable. In this paper, we take in hand this sensible predicament, which is largely abandoned in journalism; by proposing the novel concept of key-aggregation.
ERROR ANALYSIS ON SIMPLE PRESENT TENSE OF STUDENTS’ SENTENCES

Learning English nowadays is very important for students. Knowing the patterns of English is important as well. It is essential because it can assist students in order to write a good sentence. Teacher or lecturer has a responsibility to help the students to improve their writing, especially in present tense sentences. Teacher or lecturer should know and try to correct the mistakes that the students have done. This research is related to error analysis done by students when they made sentences in the class. It has to do with the use of Simple Present Tense that exist in students’ answer sheet. The purpose of the research is to analyze the error on students’ sentences when they made sentences by using Simple Present tense, especially students of Universitas Pamulang. First of all, lecturer asked students to write sentences by using simple present tense. After doing it, the research done identify based on the pattern of sentence. Third, as the last step the researcher analyzed the students' sentences. The data of the research were collected by asking students to make sentences in Simple Present Tense. Then the sentences were analyzed by using Surface Strategy Tax0nomy by Dullay (1982). The research’s result was presented descriptive qualitative. Based on the result, the most errors were about omission of auxiliary verbs and omission of inflection.
Estimating the Position of a Student's Face from Classroom Video in a Low-Quality Environment

Currently, we are developing a system to take pictures of a class and estimate the atmosphere of the class from the images. We are developing a system to determine whether the students are taking the class seriously or not. In order to determine if a participant is taking the class seriously, the position of the participant's face needs to be determined from a low-quality image. To achieve this, we used two special integrals and a combination of them. We also developed the system with perspective weighting and exclusion of non-human areas in mind. As a result, the system was able to output 80% of the expected value correctly when the appropriate photographic environment was set up. In addition, non-skin areas such as the floor and coat are no longer considered to be faces. To improve the accuracy further, it is necessary to narrow down the area where the face can exist and to take measures against wearing a mask.
FAWE: JOGO MULTIPLAYER ONLINE USANDO HTML5 E WEBSOCKET

Online games allow people to have fun together from different places. For thesegames to be created it is necessary to know different technologies. In order to demonstrate thetechnologies of HTML5 Canvas and Websocket, this work focuses on the development of theFawe game. From that, a bibliographic search was carried out to better understand these webtechnologies. The project was developed together with the creation of a Game DesignDocument detailing all the information and concepts of the game. The game was modeledusing software engineering concepts with class and activity diagrams. At the end of theproject, 17 people evaluated the game using an online questionnaire and the results werecompared.
Memory Performance Optimization

Many of the implementation technology scaling trends the computing industry has historically relied on have started to taper off or are posing increasing design challenges. This has led to the proliferation of many-core processors and accelerators, advanced packaging technologies, and innovations in memory architecture which, in aggregate, are enabling increasingly sophisticated node organizations. However, these nodes also consist of complex memory organizations that necessitate careful data management to achieve high hardware utilization. The need for such data management is making memory performanceoptimization particularly important. This talk will illustrate examples in memory access monitoring and memory-aware data structures that show the significant performance potential that can be realized by treating memory as a first-class citizen. Further, motivated by these specific point examples, the talk will also highlight general areas for further hardware-software collaborative research and innovation aimed at further improving memory performance in future computing systems.
An Evaluation of Critical Success Factors for Knowledge Management in the Financial Sector: Evidence from Developing Country Context

This study sought to determine the critical success factors for knowledge management in the Jordan financial sector. These factors were identified via extensive literature review and through descriptive and inferential statistics. Using a cross-sectional survey design, data were collected from 310 respondents, where the majority (48%) were middle-level managers followed by first-line managers and top-level managers, who accounted for 42 and 10%, respectively. All managers had taken part in identifying knowledge, sharing knowledge, and using knowledge. The findings highlighted that organization, organizational leadership, information technology infrastructure, and human resource management practice significantly affect knowledge management. Further structure equation modeling showed that organizational leadership significantly affects the organizational structure, which significantly affects knowledge management. Organizational leadership significantly affects information technology infrastructures that significantly affect knowledge management, and organization leadership affects human resource management practices, affecting knowledge management. There should be an evaluation of how the current organization structure, human resource management practices, leadership, and information technology infrastructure are likely to affect the successful implementation of knowledge management initiatives.
Pragmatic Needs-Oriented Evaluation of Visibility, Impressions, Aesthetics and Eye Movement for Platform Display Design

In today’s strict business environments, one key success factor for a platform display company seems to be making a product be different from those sold by other competing companies. The differentiator should be not only a functional one such as visibility, but also symbolic/experiential one such as impressions/aesthetics perceived. Considering this, effective/efficient evaluations of visibility, impressions and aesthetics that can be performed rapidly and easily are required. The objective of the present paper is to develop a pragmatic needs-oriented evaluation method to examine platform displays’ visibility, impressions and aesthetics, which is scientifically rigorous yet also very simple and time-saving, and therefore acceptable for practitioners. By breaking down the needs of a company’s need, multiple dimensions of evaluations were elicited. By performing a series of experiments, the multiple dimensional evaluations of visibility, impressions and aesthetics of a new product as well as its competing products were carried out. Results of each dimension as well as feasibility of the analysis procedure are discussed.
探討服務品質、顧客滿意度、顧客忠誠度之相關研究 ─以品牌形象為干擾變數

Along with the changing times, the development of hypermarkets has become the lifeline of Taiwan’s economic growth. The consumption patterns and concepts of modern customers are continuously changing, leading to the constant shifts of their purchase decisions. Meanwhile, price difference narrows due to mutual competition whereas customers attach greater value to service quality. As a result of the increase in income, customers are also becoming more and more interested in enjoying high-quality service. In recent years, how to improve service quality so as to gain customers’ recognition has become a burning topic amongst scholars. This study conducts in-depth discussions and research from the perspectives and emotions of customers by way of questionnaire survey. In this study, customers in Taiwan’s central region who have shopped in Hypermarket C were taken as research subjects, samples are collected by means of questionnaires according to random sampling, and the hypotheses are verified by SPSS. According to the research results, service quality exerts positive impacts on customer satisfaction and customer loyalty, and brand image has a moderating effect on service quality and customer satisfaction.