Reviewerly/exHarmony huggingface dataset:
Radio Broadcast and Indigenous Language Development in Nigeria: Contributions of the Radio Service of BRTV Maiduguri Toward the Promotion of Kanuri Language

Nigerian indigenous languages are facing challenges due to many factors including the ever-present long-term effects of colonialism and the use of English as the official language of communication and education, as well as urbanization, internal migration, and the mass media (both traditional and new). The preservation of indigenous languages has received global attention over the decades by notable international non-governmental organizations such as UNESCO and The British Council. In fact, the preservation of traditional cultural heritage, language inclusive, is one of the cardinal functions of mass media. Kanuri language, which is the main spoken language in Borno State in the northeast of Nigeria, is one of the several Nigerian indigenous languages facing challenges. Khaddamari, the headquarters of Jere Local Government Area, is a town very close to Maiduguri, a cosmopolitan city with population of about 1 million. Being so close to a large urban center it is known whether Kanuri language faces similar challenges it faces in the urban center, and if it does, what role does the media broadcasting from the city play toward promoting the language? This study examined the impacts of the Kanuri broadcast service of BRTV Radio, Maiduguri in the promotion and preservation of Kanuri language among the people living in Khaddamari town. Using the snowball sampling technique, 14 participants were recruited for in-depth interviews from BRTV radio and Khaddamari town. The study found that BRTV’s Kanuri broadcasts’ contribution toward the promotion of Kanuri language at Khaddamari is progressively diminishing compared to how much it could have done so three decades ago and that some of the listeners were dissatisfied with several BRTV’s Kanuri programs/news broadcasts. The study concluded that BRTV radio’s contribution toward the promotion of Kanuri language in Khaddamari town is crucial but was minimal, often hampered by the dwindling broadcast power and reach of BRTV radio signals. Therefore, BRTV should address its infrastructural deficits and formulate articulate broadcast language policy. Keywords: Radio broadcast and indigenous language, Radio program, BRTV Maiduguri, Indigenous language preservation, Kanuri language DOI: 10.7176/NMMC/99-01 Publication date: October 31 st 2021
Integrating blockchain technology in 5G-enabled smart healthcare: a SWOT analysis

Chapter Contents: 7.1 Introduction 7.1.1 Motivation of the chapter 7.1.2 Contribution of the chapter 7.1.3 Organization of the chapter 7.2 Overview of blockchain technology 7.2.1 Blockchain structure 7.2.2 Key characteristics of blockchain 7.2.3 Applications of blockchain in healthcare 7.3 Overview of 5G networks 7.3.1 Relevance of 5G in the healthcare sector 7.3.2 Performance driving with 5G 7.3.3 Advance features of 5G technology 7.3.4 Potential applications of 5G technologies 7.4 Potentials of integrating blockchain and 5G technology 7.5 Perceptual overview of integrating blockchain and 5G technology in the healthcare sector 7.5.1 Challenges of incorporating 5G and blockchain in the healthcare sector 7.6 Use case scenario 7.6.1 Characteristics of mobile application interactions between 5G and blockchain technology for serving the patient requirement 7.6.2 Challenges arise in mobile application interactions between 5G and blockchain technology for serving the patient requirement 7.7 SWOT analysis of incorporating blockchain and 5G technologies in the healthcare sector 7.8 Conclusion References
Analysis of e-learning problems during covid-19 pandemic

The occurrence of the Covid-19 outbreak requires the implementation of distance learning by implementing a learning system such as e-learning. There must be problems during the learning process using e-learning. The purpose of the research is to describe the difficulties of e-learning during the Covid-19 pandemic for class X students at SMAN 1 Keruak. The population in this study was all students in the class of X IPA SMAN 1 Keruak, divided into four courses with 120 people. The sample was taken randomly. The research method used is a descriptive research method with a qualitative approach. The research results in e-learning were carried out in 3 stages, namely learning planning, learning process, and evaluation. Students experienced difficulties in the e-learning learning process during the Covid-19 pandemic regarding the readiness of educational institutions, internet connection, internet packages, inadequate devices, and obstacles to understanding the material. During implementing e-learning, students experienced difficulties with the highest percentage of 78%. Based on these results, it can be stated that students experienced difficulties in the e-learning process during the Covid-19 pandemic regarding facilities and infrastructure.
Perancangan Aplikasi Untuk Kompresi Ayat-Ayat Di Dalam Qanun Aceh Menerapkan Algoritma Huffman

The Aceh Qanun data stored in digital form has several advantages compared to printed data, including data that is safe from rodents, data can move around easily, but digital qanuns have problems, there are many articles and verses. paragraph causes the file size to be large so that it uses a very large memory. The solution to the problem above is how large files can be compressed in order to speed up moving and saving the file. The compression of the text file is done by reducing the size of the file by reducing the bits in the saved file. By applying the Huffman algorithm to perform compression techniques, large files will be reduced in size so as to save storage space. In this study, using this algorithm, the compression results will be beneficial in making sending and moving text files easier.
Synectics with flashcards functioning to improve students’ writing skill of Bahasa Indonesia in Khon Kaen University

This action research aimed at determining the outcome of a designed intervention strategy called Synectics with flashcards that would increase Bahasa Indonesia's writing skills of Thai university students by estimating at least 70% or up of the total students to pass the criteria with a mean score of not less than 70%. This research belongs to Classroom Action Research (CAR) by adopting the concept of Plan, Act, Observe, and Reflection (PAOR) from Kemmis and McTaggart. There were 27 university students selected as the target group under the course of Intermediate Bahasa Indonesia II, ASEAN Language Centre, Faculty of Humanities and Social Sciences, Khon Kaen University. The instruments outlined in this research were three big lesson plans implemented into three cycles, subjective writing test, and behavioral observation forms for both teacher and students. The data was analyzed by conducting Mean (X), Standard Deviation (S.D.), and Percentage (%). The result of this study designated a massive improvement of Bahasa Indonesia writing skills. It was found that the students had a mean score of 14.87 out of 20 (X= 14.87, S.D.= 4.92) or representing 74.35% of the full score. Similarly, there were 22 out of 27 students met the passing criteria or 81.48% of the total number of students. It indicates that the Synectics with flashcards worked well in improving students writing skills of Bahasa Indonesia in Khon Kaen University.
Machine learning recognition of vibrational modes in ESPI data

We present a neural network (NN), constructed in Mathematica, that classifies images generated by electronic speckle pattern interferometry (ESPI). The goal of this project was to use the program to identify features in the images representing resonance behavior of the object. Much of our data was collected from unfinished wood surfaces, resulting in only the appearance of nodal lines in our ESPI data rather than the concentric rings that are hallmarks of data from finished instruments. The NN described here was trained to give four different output classifications: no resonant features, concentric ring patterns, clear nodal line patterns, and weak resonance features that correspond to ambiguous features observed at the high and low edges of the resonance band. The NN was trained using a collection of images from scans by an interferometer of multiple wood plates, an aluminium plate, and guitar top plates. In order to improve the accuracy of the classifier, we also explored image filtering techniques to increase the contrast of the images. This NN will eventually automate the process of finding resonant frequencies in real time when scanning new surfaces.
ANALISIS SALURAN SEKUNDER TERHADAP KEBUTUHAN PETANI DI BENDUNG JANGKOK KECAMATAN NARMADA KABUPATEN LOMBOK BARAT

The purpose of the study was to determine the available discharge to irrigate the rice fields and to calculate the dimensions of the irrigation channels needed. The research method used is the Irrigation Planning Criteria issued by the Ministry of Public Works of the Republic of Indonesia as the basis for placing the dimensions of irrigation canals. The first step in writing this thesis is the Hydrological Analysis of Rainfall. The results of the analysis with the 4 initial alternatives to the planned cropping pattern obtained that the net water requirement in the fields (NFR) was 0.877 lt/sec/ha and the irrigation water requirement (DR) was 1.581 lt/sec/ha which occurred in mid-April, and obtained the dimensions of the canal. primary and secondary trapezoidal shapes in the Montang Irrigation Area, respectively, are for the width of the channel bottom (b) 2.0 m, the water depth in the channel (h) 1.5 m with a guard height of 0.5 m
The Impact of Privacy Regulations on DB Systems

Personal data usage and collection are activities that used to grow unrestricted. However, several laws in the physical world ensure rights to people regarding their privacy and information usage. In the last years, legislators passed many laws, regulations, and acts to replicate these rights to the digital world. By doing so, new constraints, rights, and duties appear on every component of the data usage and collection workflow. In this paper, we discuss legislations’ implications, identifying impacts that these regulations introduce to current DBMS, and survey recent works that aim to solve the problems raised by these impacts, highlighting research opportunities and identifying how solutions can be achieved for the problems.
Trajectory planning and kinematics analysis of IRB2400 robot based on Matlab

The IRB2400 robot is studied and analyzed by using the homogeneous coordinate transformation theory. The coordinate system is established and the parameters are determined by using the DH parameter method. The robot modeling and simulation is completed by using the Matlab Robotics Toolbox. The joint space trajectories planned by cubic and quintic polunomial interpolation algorithms are compared, and the quintic polynomial interpolation algorithm is determined to be the ideal joint space trajectory planning algorithm. Given the initial and final pose of the robot, the end trajectory is analyzed, and the motion curves, angular velocity curves and angular acceleration curves of each joint are obtained. The forward kinematics and inverse kinematics are carried out to verify the rationality of the structure design of the robot.
Deep Learning based Gender Responsive Smart Device to Combat Domestic Violence

Around the clock, women face harassment and violence. Most of the time it involves harmful weapons. As this is increasing in an enormous rate, police officers are challenged to bring the situation under control time after time. In some rural areas, there are no laws regarding weapon prohibition, which questions the security of the citizens residing there. Hence, this paper aims to provide a unique solution that can prevent any mishaps as well as predict the crime well in advance. The basic idea is to detect harmful weapons such as knives and pistols as well as any suspicious activities in the surroundings. Deep Learning and transfer learning have proven to produce significant results in the field of image processing. The agenda of this paper is to develop a thoroughly automated computer-based system to detect any harmful weapons mainly pistols and knives. This is done [3] by using YOLO (You Only Look Once), a deep learning algorithm, for successful real time detection of weapons. Although there are other algorithms for object detection namely CNN (Convolutional Neural Networks), whose variants include R-CNN (Region based convolutional neural networks) and F-CNN (Faster convolutional neural networks) and SSD (Single Shot Multi-box detector, YOLO is highly preferred because of its speed and accuracy, and also its ability to pass only one image once through the neural network. The dataset used for object prediction consists of two classes, that is knives and pistols. Once any weapon or suspicious activity is detected, an alert message along with the location coordinates as well as a link to live stream the video of the crime scene is sent to the concerned pre-defined contacts.  Hence, this helps in crime reconnaissance thus mitigation.
University Computer Network Vulnerability Assessment

University Computer Network (UCN) being large, diverse and open in nature is highly vulnerable to attacks. This demands for high level of network security to maintain the confidentiality, integrity and authenticity of crucial data that university deals with on daily basis. This paper presents the scanning of a UCN using scanning tools Qualys and Nexpose. The scan results were analyzed to provide remediations for vulnerabilities detected according to severity. Priority is given to vulnerabilities having critical severity. From scan results, CVE IDs of vulnerabilities were determined and then the risk associated with a vulnerability was evaluated using National Vulnerability Database (NVD) of National Institute of Standards and Technology (NIST). From CVE ID of a vulnerability, CVSS Base Score was noted from NVD. The Common Vulnerability Scoring System (CVSS) is used for scoring of vulnerabilities based on their severities form score of 0 to 10. Risk score is also given in the scan results of Nexpose. Based on the risk that a vulnerability possesses on a network, further decisions on remediations can be taken by the concerned authorities. Critical vulnerabilities need to be dealt on priority basis else there are high chances for them to be exploited by attackers which in turn might create a serious damage to the host or network. Current paper presents vulnerability assessment and risk level estimation of critical vulnerabilities of University Computer Network.
A STUDY ON WHOLE INTIMIDATION NUMBER AND CHROMATIC NUMBER OF A FUZZY GRAPH

The study of fuzzy unit notations has been growing at an exponential rate. A development is a subset S of V; each within mathematics and it is a dominance set in G when every vertex V-S applies. The traditional ties form is adjacent to at least one vertex in S. Logic and topology are examples of mathematical disciplines. A dominating set is claimed to be fuzzy algebra,evaluation etc.As a result, the fuzzy total dominating set has energised as a capacity zone next to a minimum of one vertex in S of multidisciplinary research, and the fuzzy graph minimum cardinality taken over all total concepts is of fresh importance.
Phishing Websites, Detection and Analysis: A Survey

Phishing is the despicable utilization of electronic interchanges to trick clients. Phishing assaults resolve to increase delicate data like usernames, passwords, MasterCard information, network qualifications, and the sky is the limit from there. Phishing assaults endeavor to increase touchy, secret data, for example, usernames, passwords, charge card data, network qualifications, and then some. Phishing Websites copy the first sites so clients believe that they are utilizing the first sites. On account of phishing assaults, each individuals and associations are at threat. Phishing assaults might be forestalled by identifying the sites and serving to clients to detect the phishing sites. To distinguish the phishing sites, there have been various strategies applied. Diverse machine learning methods, information mining procedures, neural organization and different calculations have been utilized for anticipating or ordering or distinguishing the phishing sites. This paper aims at surveying on recently proposed phishing detection techniques.
Deep Learning of Traffic Volume (Vehicle Recognition & Counting)

Neural Network (NN) and Deep Learning are considered to learn abstract representations through their hierarchical architecture, which is inspired by the brain. Today, however, it is not widely understood how this happens. This is the technique through which a moving vehicle is recognized with a camera. Capturing automobile from the monitoring camera in video sequence is a challenging application to improve tracking performance. It increases the number of applications like traffic control, traffic monitoring, traffic flow, security etc. This technology. The expected costs will be much lower with this technique. These data provide three comparisons of the prominent method of recognition by vehicles: Local Binary Pattern (LBP) and Transform Scale-Invariant Features (SIFT) and for my research I’m using Neural Network (NN). For the Local Binary Pattern (LBP), the primary finding is 64.6%, for the Scale-Invariant Feature Transform (SIFT) 78.3%, and with the Deep Neural Network (DNN) 88.4 percent. In addition, the Convolutional Neural Network approach is compatible in the Neural Network method. This comparison is based on the compatibility, accuracy (percentage). These discoveries may also explain how the human brain learns abstract. Proof here that Neural Network (NN) learns abstract representations through a demodulation process. The activation function is introduced and it is used to indicate that the neural network (NN) is best studied and performed for demodulation.
Finite element modeling of guitar top plates

Here we describe the results of finite element method modeling of the resonant vibrations of a guitar top plate in various stages of construction using COMSOL. These models were completed in parallel with electronic speckle pattern interferometry ESPI measurements on three different top plates made of Engleman spruce purchased from Stewmac. The modeling was first set up for a thin piece of wood in a rectangular shape. Subsequent modeling was done at each step as the bode shape was cut, then a tone hold cut, and finally bracing was added. Care was taken to rotate the stiffness matrices for the braces in the model. Normal mode eigenfrequencies and mode shapes were calculated at each step in the fabrication process. Good agreement between the model and the measured data was obtained at low frequencies, but the model deviated from the measured results at higher frequencies.
An Efficient Blind Fragile Watermarking Scheme for Tamper Localization

Bharti, Shambhu Shankar Shivani, Shivendra Pandey, Sudhir Kumar Agarwal, SuneetaNowadays, many cases of image tampering on social media are reported. Attackers collect the images from social media and share those images by altering the original one to harm their goodwill and reputation. Thus, there is a need of an efficient technique to verify the originality of an image and localize the tampering if any occurs in the image. This paper presents an efficient blind fragile watermarking scheme to identify and localize the tamper using self embedding techniques. For this, two authentication bits for every pixel are generated by the proposed algorithm and those bits are embedded into two LSBs of the corresponding pixel in the image. Proposed approach is able to detect more than 90% tampered region. Experimental results show the efficacy of the proposed approach during embedding and detection.
The Effect of Email Keypal Project on the Enhancement of the Writing and Reading Skills of Elementary School ELF Children in Saudi Arabia: أثر مشروع صديق المراسلة على تحسين مهارات الكتابة والقراءة لدى دارسي اللغة الإنجليزية كلغة أجنبية في المرحلة الابتدائية في المملكة العربية السعودية

The aim of this study was to investigate the effects of an email Keypal project on the English reading and writing skills of a group of Grade 5 elementary school students studying English as a Foreign Language in Saudi Arabia. A mixed methods approach was used with a quasi-experimental procedures, interviews were used to collect data. 10 pupils studying at a girls’ school in Saudi Arabia participated in an email project with partners from a Muslim school in Canada. The Saudi pupils were pre- and post-tested on their reading and writing skills, and the t-tests on the mean scores indicate that the Keypal project helped the participating pupils improve their reading and writing skills significantly more than the pupils who did not participate over this term. The results of this study seem to indicate that Keypal projects could be a useful way of including technology in Saudi schools as they provide learners with a genuine audience for their work and could help to motivate learners and develop their language skills.
Application and User Interfacing

Objective: Gain a broad understanding of tactics for interfacing with associated applications, as well as approaches to graphical user interface development through Userforms, designs for user experience enhancement, and add-in packaging.
NILAI PENDIDIKAN KARAKTER DALAM KUMPULAN CERITA RAKYAT NUSANTARA DARING DAN RELEVANSINYA TERHADAP MATERI PEMBELAJARAN TEKS NARATIF DI SMA

The selection of literary works as teaching materials is difficult for an educator/teacher. Teachers have to consider the criteria of 'validity' and 'suitability' in sorting and selecting literary works. This study aims to find forms of character education values in eight Indonesian legends from the BRITISH COURSE website. In addition, the eight stories are sought for relevance to narrative text material in SMA N 1 Nusa Penida.The research subjects were eight short stories in English and Indonesian. They were collected using documentation and observation methods.All stories were read and filtered using note-taking and elicitation techniques. Stories that meet the criteria of validity and suitability are recorded in the checklist while the rest will be elicited. The data were analyzed descriptively with three working steps: coding, categorizing, describing and interpreting. Coding is given to the title to be analyzed with abbreviations. Next, the data is grouped by character value. Finally, the data is described and interpreted. The results of this study indicate that eight folk tales from the archipelago are determined, namely: ((1) The Legend of Catu Island, (2) The Little Sawah, (3) The Legend of Pesut Mahakam, (3) The Legend of Belumbak Island, (4) The Legend of Singaraja, (5) The Legend of Telaga Warna, dan (6) The Legend of Situ Bagendit. The eight legends contain validity criteria, such as: (a) six values of character education: the value of hard work, the value of social care, the value of honesty, the value of religious, the value of love of peace, and the value of independence; (b) interesting and useful, and (d) easy to reach because it is presented online. Suitability criteria, the legends (a) use English and Indonesian which is not too difficult, (b) is in line with the socio-cultural environment because it is in the form of Indonesian folklore, (c) according to age, interests, psychological development, and (d) fostering curiosity. Keywords: character values, legend, narrative prose