Reviewerly/exHarmony huggingface dataset:
Kesunyian dan ekstraversi: kajian kes instrumental tentang personaliti mangsa jenayah cinta siber di Ibu Pejabat Polis Petaling Jaya, Selangor

Counterfeit profile identity through social media channels by cybercriminals arechallenging to prevent. This paper explores the characteristics of victims of cybercrime,in particular, the romance fraud cybercrime. The qualitative study involved twelvevictims of the roman fraud cybercrime, reported at the office of the Commercial CriminalInvestigation Division, Petaling Jaya Police Headquarters. The study employed semi-structured interviews and non-participatory observations technique to collect its primarydata. Two secondary informants who served as key informants from the Office of theDeputy Director (Cyber Investigation and Multimedia Division) of the Bukit AmanCommercial Crime Investigation Department and Communications and MultimediaCommission (MCMC) in Putrajaya were interviewed to gain further insight aboutindividual personality traits that is potential to become victims of romance fraudcybercrime. Victimology theory is used to assess the typology of victims targeted bycybercriminals. The study found that the dominant personality traits describing victimsof cyber-love crime in Petaling Jaya area are loneliness and extraversion. The paperbelieves that the education efforts and awareness campaigns organised by the PDRM andMCMC are not sufficient to raise social media users' awareness of the dangers of usingopen digital platforms.
Governance of Decentralized Autonomous Organizations

This paper draws parallels between the OECD principle on disclosure and transparency and the decentralized autonomous organization (DAO) governance on a blockchain. It provides an overview of the DAO concept based on self-executing smart contracts on a blockchain. The blockchain keeps a record of data and transactions in a decentralized and immutable form. The self-executing smart contracts on a blockchain ensure transparency and automation of the decision-making process in a DAO. The paper concludes that a DAO governance structure provides for transparency and enables shareholders to exercise their rights in an informed way. Considering the early stage of development of DAOs, however, caution is needed especially with regards to potential protocol vulnerabilities and legal uncertainties.
Young People at Destiny's Crossroads - Professional vocation

Adolescence, known as the most colorful period of personality development, deals with a variety of issues, one being the choice of a future profession. The formula for the right profession choice is: I want â€“ I can â€“ I must, where â€ I wantâ€ integrates personal interests, motivations and needs; â€ I canâ€ expresses individual inclinations, skills and abilities compared to those around them; â€ I mustâ€ implies the current and prospective needs and requirements of the workforce and the emergence of new professions. The changes proposed in the last decades within the socio-economic life on the whole, especially in the sphere of production and education, have determined the emergence of new characteristics and tendencies in the theory and practice of school and professional orientation. These tendencies and characteristics, outlined in accordance with the current dimensions of the technical-scientific revolution, are common to most national orientation systems and manifest both in terms of concepts and in the field of practice itself [1] in most contemporary countries, orientation has exceeded the stage of a psychodiagnostic action and professional guidance, becoming an educational action which aims to achieve a dynamic balance between the possibilities of the individual, the requirements of the professions and the social needs of the workforce. The assertion of this tendency in the practice of school and professional orientation is based on the expansion of the psycho-pedagogical conception about orientation in more and more countries of the contemporary world, where it is argued that school and professional orientation is a long educational process, which aims to develop the personality of young people in view of the school and professional options and their future social and professional integration.
SentEmojis: Sentiment Classification Using Emojis

These days people social media for expressing their thoughts, opinions, happiness, sadness, etc. Analyzing the sentiment of the content present on social media can have a profound effect on many applications. However, identifying the correct sentiment is very challenging because of the noise present in the data. In this paper, we propose a novel approach for sentiment classifications using emojis. The proposed approach is found to be effective.
Comparison of the Methods for Jointly Learning Objects and Actions Using Realtime Object Detector

Most of visual detection in videos are limited to focus on objects or human actions separately. In this work, changing the classification loss of well-known realtime object detector, we introduce a detection model to jointly detect object-action pairs in videos. For detecting objects-actions in videos, we present two methods to label object-action pairs, called Cartesian product (CP) and valid Cartesian product (VCP). In experiments on the A2D dataset, we compares results on detection of object-action pairs in terms of the mean average precision.
Kompresi File Aplikasi Hadist Dengan Menggunakan Algoritma Punctured Elias Code

The size of the application file is sometimes relatively large, where the better the quality of the application file, the larger the file size needed to store the application file. With a very large application file size, during the transfer process, the transfer process may fail because the media storage space exceeds the limit. The solution to this problem is that the application files can be compressed in order to speed up transferring and storing application files. Compression of application files can be done by reducing the size of the application files by reducing the bits in the application files, but not eliminating or creating corrupted application files. By compressing, large data will be reduced in size so as to save storage space. In this study, the algorithm used is Punctured Elias Code, by using this algorithm, the compression results of the values have different results for each value, and the compression results will make sending and moving application files easier. Keywords : Compression, Files, Hadith Applications, Algortima Punctured Elias Code.
Assessment and Estimation of Face Detection Performance Based on Deep Learning for Forensic Applications

Face recognition is a valuable forensic tool for criminal investigators since it certainly helps in identifying individuals in scenarios of criminal activity like fugitives or child sexual abuse. It is, however, a very challenging task as it must be able to handle low-quality images of real world settings and fulfill real time requirements. Deep learning approaches for face detection have proven to be very successful but they require large computation power and processing time. In this work, we evaluate the speed-accuracy tradeoff of three popular deep-learning-based face detectors on the WIDER Face and UFDD data sets in several CPUs and GPUs. We also develop a regression model capable to estimate the performance, both in terms of processing time and accuracy. We expect this to become a very useful tool for the end user in forensic laboratories in order to estimate the performance for different face detection options. Experimental results showed that the best speed-accuracy tradeoff is achieved with images resized to 50% of the original size in GPUs and images resized to 25% of the original size in CPUs. Moreover, performance can be estimated using multiple linear regression models with a Mean Absolute Error (MAE) of 0.113, which is very promising for the forensic field.
Arm Motion Classification Using Time Series Analysis of the Spectrogram Frequency Envelopes

Hand and arm gesture recognition using radio frequency (RF) sensing modality proves valuable in man–machine interfaces and smart environments. In this paper, we use the time-series analysis method to accurately measure the similarity of the micro-Doppler (MD) signatures between the training and test data, thus providing improved gesture classification. We characterize the MD signatures by the maximum instantaneous Doppler frequencies depicted in the spectrograms. In particular, we apply two machine learning (ML) techniques, namely, the dynamic time warping (DTW) method and the long short-term memory (LSTM) network. Both methods take into account the values as well as the temporal evolution and characteristics of the time-series data. It is shown that the DTW method achieves high gesture classification rates and is robust to time misalignment.
University student strategies to cope with anxiety in learning English

This article has been prepared to report a quantitative study that revealed the strategies of students of English major and non-English major to cope with anxiety in the learning of English as a foreign language, including the description of student anxiety in learning English and strategies to cope with English learning. The respondents consisted of 173 students from English major and 173 students from non-English major of a private university in North Sulawesi Province. The validated adapted constructs of the questionnaire, namely strategies and anxiety, were originally proposed by He and Horwitz, Horwitz, and Cope respectively. The research findings showed that both English major and non-English major students had no significant difference in their strategies to cope with anxiety in learning English and in their level of anxiety in learning English. However, there were four strategies to cope with anxiety in learning English which significantly contributed to the anxiety in learning English as a foreign language.
Assessment of the Security Threats of an Institution’s Virtual Online Resources

Web application is no denying one of the most effective ways to provide essential services to clientele. However, data breach and system insecurities are increasing concern in the field of information system. The growing number of concern is the basis of the authors for this research. Several Web vulnerability scanners are used for institutions’ online resources to test the security level of the online systems.
USING CORRECTIVE FEEDBACK TOWARDS STUDENTS’ WRITINGS ON JOURNAL BOOKS

Writing skill is considered as a difficult area of English learning, including for college students. Regardless of their proficiency levels, college students make errors in their writings. Thus, English lecturers need to apply appropriate strategies in order to minimize the errors so as to improve students’ performance in writing. This study was aimed to discover one of the appropriate tools in English teaching to improve the writing skills of nursing department students of Faletehan University Serang. This is a qualitative descriptive case study. There were three instruments employed in this study, namely writing documentations, questionnaire, and interview. The results showed that students experienced different difficulties in composing their writings, especially writings with health or nursing themes. However, those difficulties didn’t hinder them to keep on writing. They made different errors in their writings, including writing aspects and grammatical features. Then, by applying the direct corrective feedbacks to the students’ writings, the lecturer had helped them in recognizing the errors they made, so that they were willing to get more feedbacks in the future. Hence, it would be helpful to improve their writing skills later.
LibGuides: Ask the Right Questions: Home

When looking for information, one of the first steps is to develop a research question to figure out the scope of what exactly is needed. In this lesson, students will explore what it takes to narrow a search in order to find the best information.
Penerapan Metode Arithmetic Mean Filter Untuk Mereduksi Noise Speckle dan Salt And Paper Pada Citra Ortokromatik

Orthochromatic imagery is made using a visible spectrum from blue to partly green (0.4-0.56 micrometers). The object will appear clearer so this image is useful for coastal studies considering the film is sensitive to objects below the surface of the water to a depth of approximately 20 meters. The capture power of orthochromatic image recorder is almost the same as the sensitivity of the human eye when taking an image or image when using a camera often experiences noise in the image caused by a bad camera lens or camera position when taking an image that can cause noise in the resulting image . Noise or image greatly influences the clarity of an image where the results of the image are less clear when seen by the eye, so that noise in the image must be removed so that the image can be clearer and has a much better quality. Arithmetic Method The Mean Filter replaces the pixel value at position (x, y) with the average pixel value in the surrounding neighbor. The number of pixels about you is determined as a masking / carnel / window that is sized for example 3x3, 5x5, 10x10, and so on. Then the mean filter will be carried out for M images using the kernel matrix (5x5). Pixels also have a weighted filter approach. The ArithmeticMean Filter method for removing noise in orthochromatic images so that noise in orthochromatic images can be reduced using the Arithmetic method which has a good role in reducing speckle and salt and pepper noise.
Penerapan Metode Case Based Reasoing Dan Certainty Factor Dalam Perancangan Sistem Pakar Diagnosa Penyakit Flu Burung Berbasis Web

Bird flu caused by a virus is very susceptible to occur at this time, it is caused by a weak immune system. Most people who are infected with the bird flu virus are those who often have direct contact with poultry, one of the causes is touching infected birds and contact with poultry body fluids, namely poultry saliva. This expert system was built to diagnose bird flu caused by viral infections. From this expert system can provide information about disease, its definition, treatment and prevention. This expert system uses the Forward Channing method. The results of consultation tests with this system show that the system is able to determine the disease along with the initial treatment and treatment that must be carried out, based on the symptoms previously selected by the user. Keywords: Expert System, Diagnosis, Avian Flu, Case Based Reasoning, Certainty Factor.
Sustainability Transparency and Trustworthiness of Blockchain: A Comparison of Generations X and Y Fashion Customers

<p class="MsoNormal" style="text-align:justify;text-justify:inter-ideograph">The fashion industry struggles to maintain healthy environmental and social conditions while keeping the economic benefits. One way to inform fashion customers about the sustainability is through transparency of information. The blockchain technology is relatively new but provides the potential application for fashion companies in this regard. Thus, this study aims to investigate consumer interaction with blockchain data and the effect this have on sustainability by comparing Generations X and Y. A quantitative research method was employed for this study and a total of 200 usable data were collected. The results show that Gen X found the claims of the blockchain more effective than Gen Y. Also, Gen X put more trust in the claims made by a company than Gen Y. Thus, applying the blockchain will be a great opportunity for business to highlight the transparency of their supply chain or product that may differentiate them from their competitor.<o:p></o:p>
The grammar of graphics family of packages.

<title>Abstract</title> This chapter introduces a couple of advanced graphics packages that are becoming more popular because of their customizability (ggplot2, ggpubr, ggplotly). The 'gg' part of the names stands for 'Grammar of Graphics'.
Facial Expression Classification using Multi-Scale Histogram of Oriented Gradients

An automatic facial expression classification method, based on multiscale Histogram of Oriented Gradients (HOG) features extracted from sub-facial image patches, is proposed in this paper. A number of multiclass Support Vector Machines (SVM) are designed using the multiscale HOG features for classifying six basic facial expressions for frontal face images. The proposed method, with a simple design and few training data, achieves descent classification accuracy at a very low computational complexity. Keywords: multi-scale HOG, Support Vector Machine, Sub-facial patch, histogram. Cite this Article: Sagar Deep Deb, Manish Sharma, Chandrajit Choudhury, Fazal Ahmed Talukdar, Rabul Hussain Laskar. Facial Expression Classification using Multi-Scale Histogram of Oriented Gradients. International Journal of Image Processing and Pattern Recognition: 2020; 6(1): 5–13p.
PRACTICE OF PHYSICAL ACTIVITIES OF A MAN WITH POSITIVE RESULT FROM COVID 19

Practicing physical activity is essential for physical and mental health. In addition, this behavior can be a great way to increase immunity, especially in times of the coronavirus pandemic (COVID-19). In this sense, this study aimed to analyze the practice of physical activities performed by a man with a positive result of COVID-19 during his period of social isolation, as well as his perceptions and difficulties about this practice. Qualitative case study carried out with a man from the northwest region of the state of Rio Grande do Sul with a positive diagnosis of COVID 19. For this, a questionnaire with open / closed questions was used as an instrument for data collection, the same was applied through the whatsapp and interpreted by content analysis. The participant reported that while in social isolation he practiced physical activities with his own body weight and with tools, in addition to abdominals. He performed them in his own room due to social isolation and had no symptoms during practice. In addition, he reported that the greatest difficulty was performing physical activities alone, without company, as usual in the weight training gym. Even in the face of such a singular moment, it is observed that the study participant followed an exercise routine, which can be explained by the adherence to the physical training that he has, and may have benefited in the recovery of the clinical condition during the diagnosis of Covid 19.
NLBSIT: A New Lightweight Block Cipher Design for Securing Data in IoT Devices

Modern applications consist of different types of control devices and sensors that connect to the Internet. These applications are new approved technologies called the Internet of Things. Nowadays, these new technologies have gained a great interest in the field of research because of their existence in several diverse fields and due to the rapid development of these technologies. Communication between these devices generates a large amount of private and sensitive information and data between them. Therefore, maintaining the confidentiality of that data and information in the Internet of Things is of great importance. Mathematical cost (complex mathematical operations) and the number of cycles in traditional cryptographic algorithms leads to a large use of memory and energy waste for devices with limited resources, which makes traditional cipher algorithms inappropriate for Internet of Things devices. A fast and LW algorithm called NLBSIT has been proposed in this regard, which provides the requisite protection and resource constrained confidentiality of data on IoT devices. This algorithm (NLBSIT) uses a 64-bit key to encode 64-bit data, uses simple mathematical operations (XOR, XNOR, shifting, swapping), and uses the features of both the Feistel and SP Network architecture to achieve diffusion and confusion (increasing data security). The FELICS and MATLAB tools are used to simulate the NLBSIT algorithm. To execute this algorithm, various data types are used, such as text and images. The results of the simulation indicate the supremacy of the proposed algorithm in various areas, such as security, efficiency, less cycles (encryption and decryption), and less memory usage.
Learning adaptive spatial regularization and aberrance repression correlation filters for visual tracking

This paper proposes a correlation filter tracking algorithm based on adaptive spatial regularization and aberrance repression aiming at the problem that the spatial regularization weight of the background-aware correlation filter is fixed and does not adapt to the change of the target, and the problem that enlarging search area may introduce background noise, decreasing the discrimination ability of filters. First, FHOG features, CN features, and gray features are extracted to enhance the algorithm's ability to express the target. Second, aberrance repression terms are added to the target function to constrain the response map of the current frame, and to enhance the filter's discrimination ability to alleviate the filter model degradation. Finally, adaptive spatial regularization terms are added to the objective function to make the spatial regularization weights being updated as the objective changes, so that the filter can make full use of the target's diversity information. This paper involves experiments on the public data sets OTB-2013, OTB-2015 and VOT2016 to evaluate the proposed algorithm. The experimental results show that the speed of the algorithm used in this paper is 20 frames/s, evaluation indicators such as distance accuracy and success rate are superior to comparison algorithms, and it has good robustness in a variety of complex scenarios such as occlusion, background interference, and rotation changes.
Data Minimisation as Privacy and Trust Instrument in Business Processes

Data is vital for almost all sorts of business processes and workflows. However, the possession of personal data of other beings bear consequences. Data is prone to abuses through the exposure to adversaries in case of data breaches or insider’s illegitimate access and processing, hence adding to customer distrust. The data minimisation principle of the General Data Protection Regulation (GDPR), as a proactive approach, requires the collection of personal data to be limited to what is necessary for the legitimate processing purpose(s). Data degradation advocates for periodic inter-process data minimisation in a multi-process environment. In this context, we are proposing intra-process data degradation as a continuous data minimisation function during the process life. In our solution, the granularity or the information level of the process data is reduced at suitable instances in the process life to the minimum sufficient level for a successful completion of the remaining process. We devise three effective data degradation policies to realise and guide intra-process data degradation in business processes. We show through a proof-of-concept implementation the applicability of the introduced concept and the effectiveness of one of the policies. Our proposed approach intrinsically reduces privacy infringement damages which contribute to end-users trust in the processes.
The Decentralization Zeitgeist: Can the Revolution be Real?

Session Description: What does the future look like if blockchain is the foundation of the future economy? Join us to explore the culture, economics, and inner dynamics of this burgeoning industry. Who is leading the charge? What are the values and ideologies driving the growth of this technology and how might that impact the nature of the global economy five, ten, twenty years from now? Finally who is using these new decentralized tools? How does a tech-heavy enterprise like blockchain enable the average non-tech consumer to maximize its utility? What are the barriers to mainstream adoption and how can we best bridge them? In a decentralized industry what would it mean to come together? How might we pool resources to build the non-technical infrastructure necessary to meaningfully advance mainstream blockchain adoption?