Reviewerly/exHarmony huggingface dataset:
Research on Elderly Behavior Monitoring Technology Based on WSN and Neural Network

Background: The elderly are prone to do some abnormal behaviors, such as tumbling or stepping out of the guardians’ monitoring area. These abnormal behaviors bring enormous hidden dangers to the health of the elderly, which need to be monitored effectively in order to be dealt with in time. Objective: Provide an approach based on Wireless Sensor Network (WSN) and Multi-Layer Perceptron (MLP) to establish the behaviors monitoring system for the elderly. Methods: A behavior monitoring system based on wireless sensor network and neural network is proposed in this paper, according to the behavior characteristics of the elderly. The system collects real-time behavior data of the elderly by wearing a bracelet with acceleration sensors wore on their hands. And then a behavior recognition model of the elderly is established through the MLP and the collected behavior data. The established behavior recognition model is used to classify and identify the five typical behavior characteristics of the elderly, such as walking, sitting, lying, standing and tumbling. At the same time, the location information of the elderly is estimated by the centroid localization technology based on Received Signal Strength Indication (RSSI) ranging. Results: The experiment results show that the designed system can timely acquire the behavior characteristic parameters of the elderly, and it can accurately identify the five typical behaviors with a 100% recognition accuracy rate. And also, it can timely give the warning of the abnormal behaviors of the elderly, such as tumbling or walking out of the active area. Conclusion: The proposed system in this paper can accurately identify the abnormal behaviors of elderly and timely inform the guardians. The proposed monitoring method can effectively reduce the hurt injury elderly, and can improve the work efficiency of guardians. And it has its theoretical and practical value.
Häxjakt, smutskastning och mord : en djupare inblick i True Crime gemenskaperna på Reddit och Websleuths

This thesis explores the communities surrounding true crime. This is explored in a qualitative manner, by studying four different communities surrounding criminal cases, as well as two interviews with people who consider themselves a part of the communities. The observations have been carried out on the forums: Reddit and Websleuths, as well as a chat-server on Discord. The aim of the thesis is to not only see how these communities work on these two forums, but also to find out how the community members interact with each other and what drives the members to engage in the community and with each other. The thesis showed that the communities differ alot between forums, and it is therefore hard to brand them as a single community. The Websleuth community appears more tightly knit, however it is also perceived by outsiders as more hostile. In comparison Reddit is more easily interactable and allows members to freely roam from subreddit to subreddit. The initial motivating aspect of members engagement seemed to be a need to contribute to the solving of an unsolved case, but also the satisfaction of justice being served. In the thesis it also became clear that many members relationships extends outside the online-communities and create “real life” friendships. (Less)
Pengaruh Pendapatan Orang Tua dan Percaya Diri terhadap Hasil Belajar pada Siswa Kelas Tinggi SD Negeri 03 Ngadirejo Mojogedang Tahun Ajaran 2018/2019

This study aims to understand the influence of: (1) parents’incomes to learning outcomes of high class student in SDN 03 Ngadirejo, (2) self confidence to learning outcomes of high class student in SDN 03 Ngadirejo and (3) parents’incomes and self confidence to learning outcomes of high class student in SDN 03 Ngadirejo. This study included in research deskriptive quantiative. The population of this research is all high class student (IV, V, VI) SDN 03 Ngadirejo which is 64 students. Technique chief and documentation. Technique of analysis data using analysis of simple linier regression and multiple linier regression which was preceded by normality test and linierity test. Based on the result of multiple analysis regression obtained equation: Y = 51,90 + 0,00000015 X_1 + 0,33 X_2. The results of the analysis of data with significance 5% obtained: (1) Parents’incomes impact on student learning outcomes that is 6,76%, (2) Self confidence impact on student learning outcomes that is 13,10%, (3) Parents’incomes and self confidence impact on student learning outcomes that is 4,76%. The result showed that there was a positive and significance influnce of parents’incomes to learning outcomes, there was a positive and significance influnce of self confidence to learning outcomes, there was a positive and significance influnce of parents’incomes and self confidence to learning outcomes of high class student in SDN 03 Ngadirejo.
트랜잭션 기반 머신러닝에서 특성 추출 자동화를 위한 딥러닝 응용

Machine learning (ML) is a method of fitting given data to a mathematical model to derive insights or to predict.In the age of big data, where the...
C3-FIow: Compute Compression Co-Design FIow for Deep Neural Networks

Existing approaches to neural network compression have failed to holistically address algorithmic (training accuracy) and computational (inference performance) demands of real-world systems, particularly on resource-constrained devices. We present C3-Flow, a new approach adding non-uniformity to low-rank approximations and designed specifically to enable highly-efficient computation on common hardware architectures while retaining more accuracy than competing methods. Evaluation on two state-of-the-art acoustic models (versus existing work, empirical limit study approaches, and hand-tuned models) demonstrates up to 60% lower error. Finally, we show that our co-design approach achieves up to 14X inference speedup across three Haswell- and Broadwell-based platforms.
HCCC Libraries: Foundational Learning Center: Student Workshops

This Guide contains general information regarding the Foundational Learning Center in room I-102 and room N-408
Effects of Voluntary Resistance Training on Health Improvement in Elderly Woman taking Lifelong Eduction Program

The purpose of this study was to verify that the elderly exercise program which is a part of lifelong education has physical and psychological effects when seven voluntary resistance exercises were applied additionally. To achieve this purpose, the study was conducted by dividing the control group that applied only existing class and the experimental group that added 11 weeks voluntary exercise program to existing class. The results are as follows. Firstly, there were no significant results in all seven indicators related to body composition. However, when compared with the control group, body weight, body mass index, body fat and abdominal fat of the experimental group tended to decrease and skeletal muscle tended to increase. Secondly, there were no interaction effects in strength between time and group, but each showed significant therapeutic effects (p.05). In other words, the fact that ‘the time spent sitting down 10 times’ was significantly reduced between the control and the experimental groups, both in advance and after, showed the effectiveness of the 11-week voluntary exercise program. However, ‘the speed of 5m’ was not significantly changed. Lastly, we found out whether the 11 week voluntary exercise program was effective in psychological indicators. When compared with the control group, depression and stress of the experimental group tended to decrease.
Voice Based Gmail Service for Visually Challenged People

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
DEVELOPING SUPPLEMENTARY READING MATERIALS FOR EFL YOUNG LEARNERS IN THE FIFTH GRADE AT SD 02 YAPINDO

The objectives of this research were to find out whether (i) to find out what are the fifth grade students’ needs of SD 02 Yapindo in learning reading English, (ii) to find out the appropriateness of the developed supplementary reading materials for EFL young learners of the fifth grade at SD 02 Yapindo.This research was Research and Development (R&D). The population of this research was the fifth grade students of SD 02 Yapindo and the sample of this research was chosen by using simple random sampling technique. The sample of this research was class V-C consisting of 27 students in age range between 9-11 years old. The instruments used in this research were needs analysis questionnaire, English teacher judgment questionnaire and expert judgment questionnaire and observation.Based on the students’ need analysis assessment result, it was found that the fifth grade students’ need in learning reading are coped in twenty two points which should be considered for the basic guidance in making supplementary materials. The points were dealing with target needs, learning needs, and general opinion and views about learning material.Based on English teacher’s and expert’s judgment results, it was found that the total of mean score of all aspects from those three units was 4.31, categorized as “Strongly Appropriate”. This suggests that the developed materials are appropriate to be used for fifth grade students at SD 02 Yapindo, Tulang Bawang. The findings and the process of this research can be used in teaching learning activity.
A Qualitative Study on the Factors Influencing the Quality of BSID-CR Test

Objective The factors that influence the clinical test of BSID-CR were discussed from two angles of the BSID-CR tester and the parents of the tested infants, so as to provide references for BSID-CR quality control intervention research and promote the improvement of BSID-CR test quality. Methods Based on phenomenological research method, the researchers went deeply into the BSID-CR test field observation. A purposive sample of BSID-CR tester and infantsâ€™ parents in a total of 21 depth interviews, of which were parents of infants in 16 copie, 5 copies of the BSID-CR tester at some Maternal and Child Healthcare Hospital in Wuhan city of Hubei province. Applying semi-structured interviews, Colazzi7 step analysis was used to analyze the data of in-depth interviews. Results the factors that affect the BSID-CR test includes the following four themes: the factors from subjects of infants and parents, BSID-CRtester factors, the environmental factors and factors derived from the scale itself. Conclusion it is suggested that clinical staff can establish the quality control intervention measures to further improve the test quality level, and ultimately promote the continuous improvement of medical quality.
The Realization and Optimization of Static Gesture Recognition System Based on Representation Learning

Gesture, which carries a large amount of human meanings is one of the most important and complicated way in human-computer interaction. Representation learning, the representation of complex objects and their eigenvalue can be discovered by machine learning. It can have an objective and comprehensive representation of experimental sample. This paper applies representation learning to the feature extraction of gestures and establishes a static gesture recognition system. The system uses Leap Motion as a teaching data collector. As a result, the process of gesture segmentation and the error from it would be avoided. In order to reduce model training and recognition time, this system uses support vector machine algorithm, an algorithm with fast response speed and high recognition rate, as a classifier. In the process of feature extraction, the machine learning algorithm itself is used to explore the representation of gestures and the extraction of feature. Therefore, the traditional empirical method of extraction would be replaced and the precision and stability of gesture recognition system would be improved. Experimental results show that compared with the traditional gesture recognition system, the improved gesture recognition system has higher recognition rate, accuracy and anti-interference ability.
Video Face Recognization Using Autoencoder and Softmax Classifications

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Feature Extraction Of Music Digital Drugs Properties Based On Contourlet Transformation

Digital Drugs become one of the most dangerous phenomena which effect the civil social and goes farther to destroy it. The big problem represented by that listening to any music is legal, so that this type of music not rejected by laws. In this research an approach to extiract some main properties of Music Digital Drugs in order to extnguishing the expansion of such type of music. Feature extraction of the music signal will be done based on contourlet transform by reconstruct the music signal, which normally used by patients to go relaxation, into two dimensional array to be decomposed to its coefficients in multi levels using contorlet transformation. The morphological properties (energy, correlation and homogeneity) of the high frequency coefficients will adopted to evaluate and study the ability to extract features that belong to that music. The three morphological properties show that the studied music signals hold some common properties which can classify them in special categories that help in future to diagnose any music broadcast online is it Music Digital Drugs or not. The practical simulated using MATLAB language.
Assessment of Shift-Invariant CNN Gaze Mappings for PS-OG Eye Movement Sensors.

Photosensor oculography (PS-OG) eye movement sensors offer desirable performance characteristics for integration within wireless head mounted devices (HMDs), including low power consumption and high sampling rates. To address the known performance degradation of these sensors due to HMD shifts, various machine learning techniques have been proposed for mapping sensor outputs to gaze location. This paper advances the understanding of a recently introduced convolutional neural network designed to provide shift invariant gaze mapping within a specified range of sensor translations. Performance is assessed for shift training examples which better reflect the distribution of values that would be generated through manual repositioning of the HMD during a dedicated collection of training data. The network is shown to exhibit comparable accuracy for this realistic shift distribution versus a previously considered rectangular grid, thereby enhancing the feasibility of in-field set-up. In addition, this work further demonstrates the practical viability of the proposed initialization process by demonstrating robust mapping performance versus training data scale. The ability to maintain reasonable accuracy for shifts extending beyond those introduced during training is also demonstrated.
ANALISIS PERFORMANSI IMAGE RETRIEVAL BERDASARKAN COLOR FEATURE DAN SCALE INVARIANT FEATURE TRANSFORM

Abstrak Berkembangnya kemajuan teknologi berpengaruh kepada gaya hidup yang terjadi pada masyarakat, contohnya sosial media yang banyak menggunakan citra sebagai objeknya. Karena banyakanya citra yang ada, sulit untuk mencari citra yang ingin ditemukan, dengan begitu Image Retrieval terbentuk sebagai teknik pengambilan citra dengan skala yang besar. Dalam kehidupan sehari-hari Image Retrieval sudah banyak dijumpai contohnya adalah Google Images yang berfungsi sebagai mesin pencari dengan menggunakan data citra. Berdasarkan permasalahan tersebut, dalam Tugas Akhir ini penulis merancang sistem dengan menggunakan metode Color Feature dan Scale Invariant Feature Transform untuk dapat menemukan data citra yang dicari. Color Feature merupakan metode yang digunakan untuk mengidentifikasi warna. Scale Invariant Feature Transform merupakan fitur untuk mendeteksi algoritma yang terdapat dalam citra. Namun penulis tidak menggunakan metode tersebut secara terpisah, metode yang digunakan dalam Tugas Akhir ini menggabungkan dua metode tersebut untuk mengoptimalkan pengambilan citra. Hasil yang diharapkan dalam penelitian ni adalah peningkatan akurasi dalam pengambilan data citra dalam skala yang besar, dengan harapan mendapat nilai Korelasi yang tinggi sehingga penelitian ini dapat dimanfaatkan untuk penelitian selanjutnya di waktu yang akan datang. Kata Kunci : image retrieval, scale invariant feature transform, color feature. Abstract The development of technological advances affects the lifestyle that occurs in society, for example, social media that uses a lot of images as objects. Because of the many existing images, it is difficult to find the image you want to find, so Image Retrieval is formed as a large-scale image retrieval technique. In everyday life Image Retrieval has often been found for example is Google Images which functions as a search engine using image data. Based on these problems, in this Final Project the author designs a system using the Color Feature and Scale Invariant Feature Transform methods to be able to find the image data sought. Color Feature is a method used to identify colors. Scale Invariant Feature Transform is a feature to detect the algorithm contained in the image. But the authors do not use these methods separately, the method used in this Final Project combines the two methods to optimize image capture. The expected result in this research is an increase in accuracy in image capture data on a large scale, with the hope of getting a high Korelasi so that this study can be utilized for further research in the future. Keywords: image retrieval, scale invariant feature transform, color feature.
Path Tracking Control of Omnidirectional Mobile Robot Based on Bidirectional Visual Navigation

A Mecanum-wheeled omnidirectional mobile robot with path tracking control system based on linear CCD camera is designed. According to the structural characteristics of the designed omnidirectional mobile robot, the kinematics equation of the robot is analyzed, and the trajectory deviation adjustment model of the robot is established based on the kinematics equation of the robot. The control system of the robot is designed. Two cameras are used to constraint the robot body posture. The principle of path tracking using cameras is analyzed. The following strategies are adopted in the image process: dynamic threshold method, adaptive exposure method, mean filter processing, binary processing method. Finally, the effect of the control system is investigated experimentally. The deviation of the robot can be measured stably and the robot path tracking control is realized.
Evaluating and Designing a Secure Text-Based CAPTCHA and Picture Password for Online Examinations

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Simulation of 4-Qubit Full-Adder Circuit by Mathematica

A correct simulation of a quantum circuit on a classical computer is more important because of their future use. The main purpose of this work is to illustrate a full adder circuit by using a standard Mathematica add-on package. The circuit can be constructed by using CNOT-based quantum gates. The program provides a curriculum unit, to generate the basic elements that make up quantum circuit.  This paper shows effective computational design by using analogy of classical circuits. We presented an explicit example to show efficiency of the 4 qubit full adder circuit on classical computer. The method given in this paper can be used to design various quantum circuits.
4 ways to prevent phishing attacks at your practice

Phishing is one of the most common methods hackers will use to attempt a digital break-in. Here’s how to protect your data.
Data Mining Technique for Temporal Association Mining using SPN-Sigmoid Neural Networks

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.