Reviewerly/exHarmony huggingface dataset:
Face identification for Law Enforcement

We all recognize that face detection is a sort of synthetic intelligence (AI) era that has grow to be an imperative a part of our normal lives, with results on nearly each element of our lives. In diverse fields, there may be a want for better accuracy and better pace for detection and popularity. However, the accuracy of the identity isn't always precisely dependable in lots of cases. In this paper we gift a incredibly correct face popularity version the use of OpenCV and dlib libraries. One of the very best methods to become aware of someone's individuality is to examine their face. Face popularity is a machine for figuring out someone with the aid of using the use of private traits of the person. An individual's face is diagnosed with the aid of using a system such as phases, specifically face detection, in which this system happens in no time in humans, besides in situations in which the item could be very near with the aid of using, and the introduction, which identifies a face as a unmarried individual. Here, we've additionally mentioned approximately detecting faces in a video frame. The most important difficulty in identity and popularity of faces is the storage, on this paper we've additionally addressed that problem with the aid of using handiest storing the facial capabilities in place of storing faces directly. Key words – dlib, face detection, artificial intelligence, machine learning, deep learning, CNN.
Situational awareness and risk assessment during armed conflict using ceaseless video monitoring via IoMT

The project proposes to implement smart warfare techniques by analyzing the data obtained to diminish real-time combat consequences. An improvised system can be accomplished which can monitor the vicinity of the warzone through continuous video recording for actionable intelligence, And this system also involves sensors to examine the health condition of the soldier that will allow us to take appropriate action by sending an alarm to the nearest teams if the sensor outcomes are beyond the expected threshold. The ultimate aim of the project is to achieve an interface that can assess the risk and send much- needed data to the armed forces to plan accordingly. This approach can be attained by using IoMT (Internet of Military Things), Sensors like Temperature sensor, Heartbeat sensor, Arduino UNO, Global Positioning System(GPS) for coordinates, GSM for emergency SOS, Switches, Buzzer, Camera for live monitoring, and a Max232 module for serial communication which are all embedded into a garment. This kind of strategic approach can be helped for defense application purposes so that the army does not have to encounter unforeseen circumstances.
Strategies of Teaching and Learning Process for Young Learners during the Pandemic

This study was conducted to investigate the strategy and activities in the teaching and learning process during the pandemic in Aura Sukma Insani Kindergarten and to investigate the teachers’ problems during the process of teaching English to Young Learners during the pandemic. This research used a descriptive qualitative method, i.e., case study. The research data are derived from observation, interview, documentation, and document analysis. The subject of this research was 3 classes (with 18-21 students each class) in B level (age 5-7). The interview is semi-structured with three teachers and a school principal as informants. The theory used in this research is the teaching and learning theory from Brown (2001). This study concluded that Aura Sukma Insani Kindergarten applied blended learning and applied both synchronous and asynchronous modes of learning during pandemics. Besides, to support the teaching and learning process, the school has a special program namely, orientation and induction programs, and reflection and follow-up program. In addition, the problems of teachers are mainly about the adaptation, emotional bonding, limited time allotment, students’ mood and focus, students’ social skill and characters, teachers’ preparation, parents’ involvement, lack of facilities and technical skill and cost. The results of this study have important implications for classroom practice as it can be used as a resource and as the foundation for more detailed information strategy of the teaching and learning process during the pandemic.
Dimensions of the Learning University in Confronting COVID 19 Pandemic Challenges: A Field Study in Saudi Public Universities from a Leadership Perspectives

The present study aims to investigate the relationship and predictability between the roles of leaders in Saudi public universities in consolidating the dimensions of learning organizations (universities) and their abilities in confronting COVID 19 pandemic challenges. A total of 228 leaders in three Saudi public universities took part in the current study. A questionnaire was designed for collecting data, which consisted of general data, The Dimensions of Learning Organization Questionnaire (DLOQ), and Confronting COVID 19 Pandemic Challenges Scale (CCPCS) developed by the researcher of this study. The results of the study showed a positive relationship between the roles of leaders in Saudi public universities in consolidating the dimensions of learning organizations (universities) and their abilities in confronting COVID 19 pandemic challenges, and that these roles of leaders are good predictors of these abilities. Results also indicate that there are no significant differences in both study scales across gender, age, academic qualifications, and years of work experience. It is recommended to increase the leaders&amp;rsquo; roles in the Saudi public universities in consolidating the dimensions of the learning organization, as this has an impact on their abilities in in confronting COVID 19 Pandemic challenges.
3D Maps Integration based on Overlapping Regions Matching

&#x0D; This paper presents a method of 3D maps integration based on overlapping regions detection and matching.&#x0D; The algorithm works without an initial guess about transformation. The process of finding transformation between maps can be divided into two steps.&#x0D; The first one is the estimation of an initial transformation based on feature extraction, description, and matching.&#x0D; The assumption is that the maps have an overlapping area that can be used during feature based processing.&#x0D; Then the found initial solution is corrected using local methods, for example, Iterative Closest Point (ICP) algorithm.&#x0D; The maps are stored in the octree based representation (octomaps) but during transformation&#x0D; estimation, a point cloud representation is used as well. In addition, the presented method was verified in various experiments: in a simulation, with wheeled robots, and with publicly available datasets.&#x0D; Eventually, the solution can be applied to many robotic applications related to the exploration of unknown environments.&#x0D; Nevertheless, so far the implemented method was validated with a group of wheeled robots.&#x0D;
Multimedia Technology of Spatial Data Mining Based on Genetic Algorithm

In order to make key decisions more conveniently according to the massive data information obtained, a spatial data mining technology based on a genetic algorithm is proposed, which is combined with the k-means algorithm. The immune principle and adaptive genetic algorithm are introduced to optimize the traditional genetic algorithm, and the K-means, GK, and IGK algorithms are compared and analyzed. The results show that, in two different datasets, the objective functions obtained by the K-means algorithm are 94.05822 and 4.10373 <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <mfenced open="(" close=")" separators="|"> <mrow> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mn>6</mn> </mrow> </msup> </mrow> </mfenced> </math> , respectively, while the objective functions obtained by the GK and IGK algorithms are 89.8619 and 3.9088 <math xmlns="http://www.w3.org/1998/Math/MathML" id="M2"> <mfenced open="(" close=")" separators="|"> <mrow> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mn>6</mn> </mrow> </msup> </mrow> </mfenced> </math> , respectively. The difference between the three algorithms can also be reflected in the data comparison of the number of iterations. The number of iterations required for k-means to reach the optimal solution is 8.21 and 8.4, respectively, which is the most among the three algorithms, while the number of iterations required for IGK to reach the optimal solution is 5.84 and 4.9, respectively, which is the least. Although the time required for K-means is short, by comparison, the IGK algorithm we use can get the optimal solution in relatively less time.
Detecting Compiler Bugs Via a Deep Learning-Based Framework

Compiler testing is the most widely used way to assure compiler quality. However, since compilers require a large number of sophisticated test programs as inputs, the existing approaches in compiler testing still have a limited capability in generating both syntactically valid and diverse test programs. In this paper, we propose DeepGen, a deep learning-based approach to support compiler testing through the inference of a generative model for compiler inputs. First, DeepGen trains a Transformer-XL model based on a large corpus of seed programs, and uses the trained model to generate syntactically valid programs. Then, DeepGen adopts a sampling strategy in the inference phase to generate diverse test programs. Finally, DeepGen leverages differential testing on the generated programs to discover compiler bugs. We have evaluated DeepGen over two popular C++ compilers GCC and LLVM, and the results confirm the effectiveness of our approach. DeepGen detects 35.29%, 53.33%, and 187.50% more bugs than three existing approaches, i.e. DeepSmith, DeepFuzz, and Csmith, respectively. In addition, 30.43% bugs detected by DeepGen are not detected by other approaches. Furthermore, DeepGen has successfully detected 38 bugs in the latest development versions of GCC and LLVM; 21 of them have been confirmed/fixed by the developers.
Structurally R-Controllable and Structurally R-Observable Descriptor Linear Electrical Circuits

Structurally R-controllable and structurally R-observable descriptor linear electrical circuits are investigated.Sufficient conditions are given under which the Rcontrollability and R-observability of descriptor linear electrical circuits are independent of their parameters.
Focus Group Discussion on Students Perspective View on COVID-19 and Distance Education

Introduction: The COVID-19 could be a dangerous widespread that has influenced each angle of life including education. The educational institutes have been closed to avoid the spread of the infection, and they have changed over their system into distance education. Completing the semester there's a have to be address the risky issues within the modern framework to create it for future usage Objectives: 1-To explore the effects of Covid-19 on life style 2- To know the perceptions and suggestions regarding online education in pandemic Material and Methods Study design: Qualitative Settings: Rawalpindi Medical University Duration: Six months i.e. 1st January 2021 to 30th June 2021 Data Collection procedure: It was focus group discussion conducted via Zoom link. There were 15 medical students were selected from all five classes of MBBS randomly after taking informed consent. A variety of issues that were obtained from the discussion were identified. Results: The findings have uncovered that most of the members were influenced by the widespread period contrarily Anxiety, hope less, and fatigue. It is clear from the findings that education process has had its shortcomings instead of its advantages such as need of interaction, and communication which lead the students to segregation, issues about exams, conventional instructive habits, the load of assignments, and time administration. On the other side the advantages regarding flexibility of place and time to learn and comfort in assessment Conclusion: It is evident that the COVID-19 widespread process has influenced the students’ lives adversely. These negative sentiments have not been overcome by the instruction they uncovered all through the period. While, in conventional campus life they would be at the side their companions and teachers and they would overcome the issues together through socializing. Distance education system tried to facilitating teaching. The COVID-19 widespread period ought to be regarded as an opportunity for teachers to consider how to push the distance education framework forward. Within the light of the findings, it would be awesome to create the current distance education practices which we may well are beyond any doubt that long-term executions get a solid premise. Keywords: Covid-19, Pandemic, Focus group, Distance education, Higher education
DEVELOPMENT OF INNOVATIVE POWER OF STUDENTS IN TECHNICAL INSTITUTIONS

This article aims to provide an innovative direction of thinking through the development of person-centered pedagogical technologies that fully meet the level of intellectual, intellectual and social development of students in the educational process; the development of innovative potential, taking into account their extracurricular interests and life experiences.
Self-aware attentional image demotion fuzzy algorithm based on conditional generative adversarial network

Image has been widely used in various fields, but due to camera motion or scene change, the image will form different degrees of non-uniform motion blur. For image motion blur, the existing motion blur method based on conditional generative adversarial network still has a lot of room for improvement in quality and efficiency. As a result, In this paper, we propose a self-aware Attention Motion Deblurring Using Conditional Adversarial Networks, which is based on Conditional generative Adversarial Networks. (SAD-GAN), adding Self-aware Attention (SA)and Cascaded Parallel Dilated Convolution (CPDC) to the generator. The discriminator uses the ideas of global discriminator, local discriminator and relative discriminator, and the whole network works closely together to capture the context fuzzy information more accurately, so as to achieve high quality deblurring. Experimental results on existing public data sets show that the proposed method performs better than other advanced methods in image de-motion-fuzzy structure similarity (PSNR) and peak to noise ratio (SSIM) quantitative indexes.
Meningkatkan Kerja Sama Peserta Didik melalui Model Pembelajaran Student Teams Achievement Division (STAD) di Kelas IV SD Negeri 112/I Perumnas

This research was conducted with the aim of increasing student cooperation in learning through the Student Teams Achievement Division (STAD) learning model in grade IV SD Negeri 112/I Perumnas. This research is a classroom action research (CAR) which discusses how teachers improve student cooperation through the Student Teams Achievement Division (STAD) learning model in grade IV SD Negeri 112/I Perumnas. The Student Teams Achievement Division (STAD) learning model that will be used in the research is conveying the goals and motivations of students, dividing students into small groups of 4-5 people heterogeneously, presenting learning information, the teacher giving assignments to group members to work on. together, the teacher guides group discussions, the teacher gives quizzes or questions for students, awards for the group that gets the highest score, and the teacher provides evaluations and conclusions. Collecting data in this study using observation. This research consisted of two cycles and each cycle consisted of two meetings. At each meeting there will be four stages, namely planning, implementation, observation and reflection. The results of the research in cycle one show that the Student Teams Achievement Division (STAD) learning model can improve student cooperation in class IV SD Negeri 112/I Perumnas. It can be seen from the results of observations in the first cycle that the presentation of the successful collaboration of students in class IV SD Negeri 112/I Perumnas is 66.14% with a sufficient predicate (C). In the second cycle the results increased to 75.76% with a good predicate (B).
Trac: An Approach to Teaching Security-Aware Programming in Undergraduate Computer Science Courses

The unfortunate list of software failures, attacks, and other software disasters has made it apparent that software engineers need to produce reliable code. The Department of Homeland Security reports that 90% of software exploits are due to vulnerabilities resulting from defects in code. These defects are easy to exploit. They are potentially dangerous as they create software vulnerabilities that allow hackers to attack software, preventing it from working or compromising sensitive data. Thus, these defects need to be addressed as part of any effort to secure software. An effective strategy for addressing security-related code defects is to use defensive programming methods like security-aware programming. This paper presents TRAC, an approach to teaching security-aware programming. The acronym stands for Teach, Revisit, Apply and Challenge. It also describes the implementation of the approach and the results of a small case study (n = 21), in a senior-level elective course.
Research on the Development Status and Reform Direction of Vocational Education

In recent years, with the rapid development of our economy, the increase of population, the increase of the people, and the progress of the development of vocational education and the gap, the development of vocational education is getting faster and faster.
Bitcoin vs. Gold: Who is the Better Choice for Trading?

Venture capital led by Bitcoin and gold has become increasingly popular in the past several years, so the research of cryptocurrencies (such as Bitcoin) becomes deeper and deeper. Many researchers have studied the collaborative investment of bitcoin and gold, which is an expective portfolio. In this paper, the authors constructed a systematic model, achieving the combination among prediction, making strategies, solving profits, and evaluation. All the study in this paper is based on the given data and constructed model with accurate references.In this paper, the authors selected the long short-term memory model (LSTM) as the basis, then designed two models called the gold price prediction model (GPPM) and the Bitcoin price prediction model (BPPM) to estimate the price of both gold and Bitcoin, standing as a trader, not a “god economist”. The error analysis shows a good performance of GPPM and BPPM, and it gives the authors confidence to make strategies and calculate final profits (investment worth).Unambiguously, the final goal of this question is to maximize the total assets (profits), so the author set up a single objective optimization model (SOOM) called the trading strategy model (TSM). The total constraint conditions are divided into six directions, including the basic trading conditions, the evaluation of financial risk, and the difference between gold and Bitcoin. Additionally, the costumers with different trading risk tolerance will acquire different assets finally, which indicates that the prudent policy generally can lead to a better result. After calculation, the asset on 2021/9/10 is about 1.59×108 USD, a considerable number.The evaluation of TSM has two parts, one is the disturbance test. This test randomly sets that several days’ trading does not occur, then has a comparison between the original model prices and the prices after disturbance. The result proves that the strategy predicted by TSM is the best strategy. The result of the sensitivity test in section 4 finds the polynomial relationship between the assets and the transaction costs. Under current conditions, the final assets will decrease by 4.2% if the transaction costs of gold increase by 1%, and will increase by 2.1% if the transaction costs of bitcoin increase by 1%.Finally, the authors wrote a memorandum for different customers &amp; traders. We sincerely hope the memorandum can help them in the near future.
Cover Jurnal

Cover Jurnal Edisi Volume 14 Nomor 1 Tahun 2022
A Survey on Analysis of Crime Detection Techniques Using Machine Learning

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.
An Investigation of User Experiences on VR Videos in a Home Environment

As a typical 5G service, VR service quality has become the focus of attention of the network operators. Both 5G and Gigabit home broadband have the characteristics of high bandwidth and low latency, and could theoretically provide a good network support to the VR video playback, especially to 360-degree panoramic videos. In the current study, we explored the VR video playback quality and users’ viewing feelings under 5G and Gigabit home broadband network in a home environment. Our findings indicated that the video playback quality under 5G network was significantly lower than that under Gigabit home broadband network. In addition, we found that users were more sensitive to stalling frequency during watching, which considered to be highly related to the value of the network downlink rate. Our findings implied that the stability of 5G network performance should be further improved to better support the applications that require the network with high bandwidth and low latency.
Readability Level of Reading Texts in The English Textbook Published by Intan Pariwara for Junior High School Grade IX at Junior High School 2 Grogol Kediri

This study describes the results of research regarding: (1) The types of text listed in the English textbooks used by the teacher are books published by Intan Pariwara, (2) The level of readability of books used by teachers published by Intan Pariwara in class IX in SMAN Grogol 2 Kediri. This research uses descriptive qualitative as a research technique. The method used in this research is interviews with English teachers, calculations with FRY graph formulas, and documentation. The research results obtained are: (1) The types of text found in the English book entitled Bahasa Inggris published by Intan Pariwara are announcement text, advertisement text, procedure text, report text, descriptive text, narrative text, and recount text. (2) for the calculation of the readability level using the FRY graph formula, the researcher gave a limit to the type of text used for the study, namely Narrative text with a total of two reading texts and Report text with a total of two reading texts. The results obtained have different numbers, namely from those that are too easy or not according to the user level, namely for class VII, for class VIII, and there is one text that corresponds to the user level, namely for class IX, and one text for class X.