Reviewerly/exHarmony huggingface dataset:
Single MR Image Super-Resolution using Generative Adversarial Network

Spatial resolution of medical images can be improved using super-resolution methods. Real Enhanced Super Resolution Generative Adversarial Network (Real-ESRGAN) is one of the recent effective approaches utilized to produce higher resolution images, given input images of lower resolution. In this paper, we apply this method to enhance the spatial resolution of 2D MR images. In our proposed approach, we slightly modify the structure of the Real-ESRGAN to train 2D Magnetic Resonance images (MRI) taken from the Brain Tumor Segmentation Challenge (BraTS) 2018 dataset. The obtained results are validated qualitatively and quantitatively by computing SSIM (Structural Similarity Index Measure), NRMSE (Normalized Root Mean Square Error), MAE (Mean Absolute Error), and VIF (Visual Information Fidelity) values.
Intersection density of imprimitive groups of degree $pq$

A subset $\mathcal{F}$ of a finite transitive group $G\leq \operatorname{Sym}(\Omega)$ is \emph{intersecting} if any two elements of $\mathcal{F}$ agree on an element of $\Omega$. The \emph{intersection density} of $G$ is the number $$\rho(G) = \max\left\{ \mathcal{|F|}/|G_\omega| \mid \mathcal{F}\subset G \mbox{ is intersecting} \right\},$$ where $\omega \in\Omega$ and $G_\omega$ is the stabilizer of $\omega$ in $G$. It is known that if $G\leq \operatorname{Sym}(\Omega)$ is an imprimitive group of degree a product of two odd primes $p>q$ admitting a block of size $p$ or two complete block systems, whose blocks are of size $q$, then $\rho(G) = 1$. In this paper, we analyse the intersection density of imprimitive groups of degree $pq$ with a unique block system with blocks of size $q$ based on the kernel of the induced action on blocks. For those whose kernels are non-trivial, it is proved that the intersection density is larger than $1$ whenever there exists a cyclic code $C$ with parameters $[p,k]_q$ such that any codeword of $C$ has weight at most $p-1$, and under some additional conditions on the cyclic code, it is a proper rational number. For those that are quasiprimitive, we reduce the cases to almost simple groups containing $\operatorname{Alt}(5)$ or a projective special linear group. We give some examples where the latter has intersection density equal to $1$, under some restrictions on $p$ and $q$.
Adversarial Reweighting for Speaker Verification Fairness

We address performance fairness for speaker verification using the adversarial reweighting (ARW) method. ARW is reformulated for speaker verification with metric learning, and shown to improve results across different subgroups of gender and nationality, without requiring annotation of subgroups in the training data. An adversarial network learns a weight for each training sample in the batch so that the main learner is forced to focus on poorly performing instances. Using a min-max optimization algorithm, this method improves overall speaker verification fairness. We present three different ARWformulations: accumulated pairwise similarity, pseudo-labeling, and pairwise weighting, and measure their performance in terms of equal error rate (EER) on the VoxCeleb corpus. Results show that the pairwise weighting method can achieve 1.08% overall EER, 1.25% for male and 0.67% for female speakers, with relative EER reductions of 7.7%, 10.1% and 3.0%, respectively. For nationality subgroups, the proposed algorithm showed 1.04% EER for US speakers, 0.76% for UK speakers, and 1.22% for all others. The absolute EER gap between gender groups was reduced from 0.70% to 0.58%, while the standard deviation over nationality groups decreased from 0.21 to 0.19.
FLIP: A Utility Preserving Privacy Mechanism for Time Series

Guaranteeing privacy in released data is an important goal for data-producing agencies. There has been extensive research on developing suitable privacy mechanisms in recent years. Particularly notable is the idea of noise addition with the guarantee of differential privacy. There are, however, concerns about compromising data utility when very stringent privacy mechanisms are applied. Such compromises can be quite stark in correlated data, such as time series data. Adding white noise to a stochastic process may significantly change the correlation structure, a facet of the process that is essential to optimal prediction. We propose the use of all-pass filtering as a privacy mechanism for regularly sampled time series data, showing that this procedure preserves utility while also providing sufficient privacy guarantees to entity-level time series.
Study of Global Solar Radiation in Duhok Province

This paper studies and analyzes the ground-based global solar radiation (GSR) data available in the Dohuk governorate. The data was collected from the Meteorological Directorate in Duhok for six stations: Kani Masi, Bamarni, Amedi, Mangesh, Akre, and Semel.&#x0D; The highest monthly average values of GSR in Duhok were in June and July, and the lowest values were in December and January. Among all stations, Amedi has the highest value of the monthly mean of GSR (8.7041 kWh/m2/day) followed by Kani Masi at (8.5265), Mangesh at (8.3249), Bamarni at (8.072), Semel (7.0506) and finally Akre 6.1171(kWh/m2/day), while the lowest values of GSR were in December 2018 mostly, except for Semel was in December 2016.&#x0D; The annual mean of GSR in (kWh/m2/day) for these stations were 5.0168, 4.8311, 4.817, 4.7546, 4.3155, and 3.6183 for Amedi, Kani Masi, Mangesh, Bamarni, Semel, and Akre respectively.&#x0D; The monthly mean of the daily clearness index of the study area peaks is in the mid months of the year (May, June, July, August, and September). KT values experienced a dramatic decrease in March in all stations except Mangesh showed a slight increase. Among all the stations, Akre saw the lowest values in KT ranging from 0.32997 to 0.50686 with an annual average of 0.42443.
Efficient malicious node detection system for forest fire monitoring by trust calculation using EDENN algorithm in WSN environment

Abstract Wireless Sensor network (WSN) works in exceedingly advanced surroundings wherever it's troublesome for folks to achieve or work. The forest fire observation is that the promising application in WSN. However within the WSN openness of nodes ends up in security threats at risk of numerous attacks of nodes that are denoted because the malicious nodes. Recognition of malicious node is the encounters Janus-faced by the sensors in WSN for any application, protection of fire observation knowledge is critical for save the wild life animals. Existing analysis ways aren’t absolutely save the network lifespan and correct detection. To resolve that downside this analysis methodology projected a completely unique method for malicious node detection in WSN surroundings for fire observation. The projected methodology consists of seven steps. At first, the sensor nodes are initialized then, the residual energy is calculated within the pre-processing stage. By the assistance of calculated price the cluster is created mistreatment NCD-KM. Then, in every cluster the malicious node is detected mistreatment EDENN, if the cluster has malicious node then the malicious node is severally hold on for stop the cluster. Then, the cluster head is chosen by mistreatment the GDSHO formula. Finally the data transmission is managed by cluster head and super cluster head. In experimental analysis the performance of the projected methodology is analyzed with the present analysis methodologies. Within the analysis the projected methodology attains higher performance than the present analysis methodologies.
Traffic Analytics Development Kits (TADK): Enable Real-Time AI Inference in Networking Apps

Sophisticated traffic analytics, such as the encrypted traffic analytics and unknown malware detection, emphasizes the need for advanced methods to analyze the network traffic. Traditional methods of using fixed patterns, signature matching, and rules to detect known patterns in network traffic are being replaced with AI (Artificial Intelligence) driven algorithms. However, the absence of a high-performance AI networking-specific framework makes deploying real-time AI-based processing within networking workloads impossible. In this paper, we describe the design of Traffic Analytics Development Kits (TADK), an industry-standard framework specific for AI-based networking workloads processing. TADK can provide real-time AI-based networking workload processing in networking equipment from the data center out to the edge without the need for specialized hardware (e.g., GPUs, Neural Processing Unit, and so on). We have deployed TADK in commodity WAF and 5G UPF, and the evaluation result shows that TADK can achieve a throughput up to 35.3Gbps per core on traffic feature extraction, 6.5Gbps per core on traffic classification, and can decrease SQLi/XSS detection down to 4.5µs per request with higher accuracy than fixed pattern solution.
Training And Mentoring Google Apps For Education (GAFE) To Support Teacher Performance In Online Learning

The covid-19 pandemic has forced the education system in Indonesia to use the online method. This is explained in his research, which states that teachers have used various platforms such as Google Classroom, Edmodo, Zoom, or Schoology. The use of various learning platforms is considered a bit difficult, where teachers need to install various applications on their devices. Installing these various applications will certainly make the device work harder, so it’s possible for errors or hangs to occur when running the applications. The purpose of this mentoring activity is to provide training and mentoring on Google Apps for Education to teachers at SMA Panjura Malang. The method of implementing this community service activity begins with FGD, GAFE training, GAFE assistance and monitoring and evaluation of GAFE activities. The result of this service activity are: (1) service activities attended by 34 teachers, (2) pre test result are 41,1% and post test result are 91,1% so that there is an increase 50%, (3) 94% of teachers implement GAFE in learning.
Minat Baca Siswa SMP: Faktor Latar Belakang Ekonomi dan Pendidikan Keluarga (Middle School Students Reading Interests: Factors of Economic Background and Family Education)

This study aims to analyze students' reading interests based on economic background and family education. The population of this study was 203 students of SMP Negeri 3 Tarowang, Jeneponto, South Sulawesi. Data were collected through questionnaires and documentation. Data were analyzed by descriptive and inferential statistics. The results showed that (1) students' reading interests based on family economic background and family educational background were in the moderate category, (2) there were significant differences in students' reading interests based on family economic background, and (3) there were significant differences in students' reading interest. based on family educational background. This finding indicates that economic factors and family background have a relationship with the level of students' reading interest. Penelitian ini bertujuan unuk menganalisis minat baca siswa berdasarkan latar belakang ekonomi dan pendidikan keluarga. Populasi penelitian ini adalah 203 siswa SMP Negeri 3 Tarowang, Jeneponto, Sulawesi Selatan. Data dikumpulkan melalui kuesioner dan dokumentasi. Data dianalisis dengan statistik deskriptif dan inferensial. Hasil penelitian menunjukkan bahwa (1) minat baca siswa berdasarkan latar belakang ekonomi keluarga dan latar belakang pendidikan keluarga berada pada kategori sedang, (2) terdapat perbedaan signifikan minat baca siswa berdasarkan latar belakang ekonomi keluarga, dan (3) terdapat perbedaan signifikan minat baca siswa berdasarkan latar belakang pendidikan keluarga. Temuan ini mengindikasikan bahwa faktor ekonomi dan latar belakang keluarga memiliki hubungan dengan tingkat minat baca siswa.
THE COLLABORATION OF AUDIO-VISUAL MATERIALS AND INSTRUCTIONAL DIGITAL GAMES IN HALF-DAY INSTRUCTION PROGRAM IN MATHEMATICS

The purpose of the study is to determine the impact of collaboration of instructional digital games and audiovisual materials in "Half-day" Instruction Program to the performance of grade six students in Mathematics at Balanac Elementary School, Magdalena Laguna.Specifically, it sought to respond the following:(1) the level of the half-day instruction program in mathematics in terms of instructional digital games and audio-visual materials.(2) the learner's performance in mathematics in terms of Pretest and Posttest.(3) if there is a significance difference on learners' performance in terms of pretest and posttest.( 4) If there is a significant effect of the Half-day instruction program in mathematics on the learner's mathematical performance.The researcher prepared the necessary materials that will used to enhance the learner's performance in mathematics.The use of audio-visual materials and digital games were presented to the experimental group in a halfday scheduled and tradition teaching for the controlled group.The pretest and posttest were administered before and after the presentation of the lesson.The level of perception of the learners on the use of instructional digital games was Very High.And the level of perception of the learners on the use of audio-visual materials was High.This indicates further the usefulness of the Half-day Instruction Program in Terms of instructional digital games and audio-visual materials help the learners to continue the education and motivates to attain the desired competencies for a specific learning area.The instructional digital games and audio-visual materials has significant effect on the learner's mathematics performance.Therefore, the null hypothesis of the study is hereby rejected.This implies also that the Use of collaboration of the instructional software games in the half day instruction can help the students to improve their performance.
THE USE OF COMPUTER-BASED INSTRUCTION TO IMPROVE THE LEARNERS MATHEMATICS PERFORMANCE

The main purpose of the study was to determine the significant effect in the use of Computer Based Instruction to the mathematical performance of the Grade Three learners of Lewin Elementary school, S.Y 2021 -2022.Specifically, it sought to respond the following: (1) the respondents level of perception on the use of computer base-instruction in terms of; teachers prerecorded video lessons, online tutorial videos, PowerPoint presentation; (2) the mean percentage score of the learner's mathematics performance in terms of pretest and posttest; (3) if there is a significant difference between the control and experimental group's mathematics performance in posttest; (4) if there is a significant effect the use of Computer Based Instruction to the mathematical performance of the Grade Three learners of Lewin Elementary School.Based on the data gathered, the learners perceived that the use of computer-based instruction was very effective.The level of controlled and experimental group's mathematics performance in pretest was below average while the posttest of the controlled group is average, and the experimental group is very good.The test of difference between the pre-test and post-test of the experimental group resulted to rejecting the null hypothesis which implies that there is a significant difference on the performance of students.Moreover, it showed how the use of computer-based instruction affect the experimental group mathematics performance in terms of teachers pre-recorded videos but does not significantly affect in terms of online tutorial videos and powerpoint presentations.These resulted to partially rejecting the null hypothesis.It can also be concluded that the use of computer-based instruction was significant effect on learners' mathematics performance.The researcher highly suggests that he use of Teacher's pre-recorded video lesson and online tutorial videos can help to reach out the learners amid COVID-19 pandemic.It must be included on their School Improvement Plan on the learner's development.Classroom teachers may also sustain the usage of the computer-based instruction in teaching mathematics.The teachers may devote more efforts to learn and apply new and different use of educational technology that can be useful to keep classroom well managed and conducive for teaching-learning.
ELECTRONIC GADGETS TO THE MATHEMATICAL PERFORMANCE OF GRADE 5 LEARNERS OF PULONG STA. CRUZ ELEMENTARY SCHOOL

The ubiquity of electronic devices together with its potential to bridge classroom learning to real-world has added a new angle to contextualizing mathematics learning.The study aimed to determine the mathematical performance of Grade 5 learners using electronic gadgets.In conducting this study, a descriptive study method was used to collect the data and information needed to test the hypothesis and to answer questions concerning the "electronic gadgets to the mathematical performance of Grade 5 learners."The instrument used was questionnaire in the form of checklist.The respondents of the study composed of one hundred (100) respondents.Statistical treatment utilized in this study consisted of weighted mean, standard deviation, and frequency.This study found that there is an equal distribution of respondents with respect to their genders.It was also seen that the respondents of the study are almost approaching their teens.Also, it can be inferred that the majority of the students have a more stable internet connection and accessible gadgets.This study found that the level of the electronic gadgets with regards to usability, functionality, and ease of use of electronic gadgets was very high among the students.The level of mathematical performance of grade 5 learners using electronic gadgets from Quarter 1 to Quarter 3 was also found very satisfactory.The study concluded that there was no significant effect observed from the profile of the students to their performance.Therefore, the null hypothesis stated is true.In this case students' profile doesn't affect their mathematical performance because of the device and internet availability nowadays.Using electronic gadgets to students' mathematical performance was no significant effect.Moreover, it is suggested that even though there is no significance between the variables, using gadgets in their math class were more likely to achieve higher mathematical performance as they enjoy using those in their learning process, it also motivates them because they can explore more and do more using different kinds of application in those gadgets.Also, students find electronic gadgets more convenient and easier to use.
Privacy accounting εconomics: Improving differential privacy composition via a posteriori bounds

Differential privacy (DP) is a widely used notion for reasoning about privacy when publishing aggregate data. In this paper, we observe that certain DP mechanisms are amenable to a posteriori privacy analysis that exploits the fact that some outputs leak less information about the input database than others. To exploit this phenomenon, we introduce output differential privacy (ODP) and a new composition experiment, and leverage these new constructs to obtain significant privacy budget savings and improved privacy-utility tradeoffs under composition. All of this comes at no cost in terms of privacy; we do not weaken the privacy guarantee. To demonstrate the applicability of our a posteriori privacy analysis techniques, we analyze two well-known mechanisms: the Sparse Vector Technique and the Propose-Test-Release framework. We then show how our techniques can be used to save privacy budget in more general contexts: when a differentially private iterative mechanism terminates before its maximal number of iterations is reached, and when the output of a DP mechanism provides unsatisfactory utility. Examples of the former include iterative optimization algorithms, whereas examples of the latter include training a machine learning model with a large generalization error. Our techniques can be applied beyond the current paper to refine the analysis of existing DP mechanisms or guide the design of future mechanisms.
Learning to Behave: Improving Covert Channel Security with Behavior-Based Designs

Censorship-resistant communication systems generally use real-world cover protocols to establish a covert channel through which uncensored communication can occur. Unfortunately, many previously proposed systems use cover protocols inconsistently with the way humans normally use those protocols, leading to anomalous network traffic patterns that have been shown to be discoverable by real-world censors. In this paper, we argue that censorship-resistant communication systems should follow two behavior-based design properties: (i) behavioral independence: systems should isolate the operation of their covert channels from the operation of their cover protocols, and (ii) behavioral realism: systems should either opportunistically use existing genuine cover protocol instances or run new protocol instances that are modeled after genuine ones. These properties ensure that the behavior of a system’s users will not degrade its security. We demonstrate how to achieve these properties through the design and evaluation of Raven, a censorship-resistant messaging system that uses email cover protocols identically to the way humans use email. Raven uses a generative adversarial network that is trained on genuine email data to control the timing and sizes of the email messages it sends and receives, and these messages are transferred independently of user actions. Our evaluation shows that, compared to the state-of-the-art email-based Mailet system, Raven raises the false-positive rate from 3% to 50% when detecting covert channel usage with 100% recall.
The International Conference on Geomatics and Geospatial Technology 2022 (GGT2022)

1. Introduction Greetings from the editorial team of GGT2022. Papers in this proceeding were presented in the International Conference on Geomatics and Geospatial Technology 2022 or GGT2022. This year conference jointly organised by Universiti Teknologi MARA (UiTM) and Royal Institution of Surveyor Malaysia (RISM) was held virtually as many other international conferences in the era of the pandemic. Universiti Teknologi MARA, Shah Alam, Malaysia was selected as the base for this conference where we had used Zoom as a platform for conducting this conference. List of Committee, Virtual Conference Dates, Location of Organisers, Platform, Information on Keynote Sessions, Information on Parallel Sessions, Conference’s Participants, are available in this pdf.
ANALYSIS OF THE POSSIBILITIES OF IMPLEMENTING THE RESULTS OF RESEARCH ACTIVITIES INTO THE TEACHING OF THE MODERNIZED STUDY PROGRAM CRISIS MANAGEMENT

Information about the paper titled "ANALYSIS OF THE POSSIBILITIES OF IMPLEMENTING THE RESULTS OF RESEARCH ACTIVITIES INTO THE TEACHING OF THE MODERNIZED STUDY PROGRAM CRISIS MANAGEMENT" at IATED Digital Library
Privacy Preserving Text Document Summarization

Data Anonymization provides privacy preservation of the data such that input data containing sensitive information is converted into anonymized data.Hence, nobody can identify the information either directly or indirectly.During the analysis of each text document, the unique attributes reveal the identity of an entity and its private data.The proposed system preserves the sensitive data related to an entity available in text documents by anonymizing the sensitive documents either entirely or partially based on the sensitivity context which is very specific to a domain.The documents are categorized based on sensitivity context as sensitive and not-sensitive documents and further, these documents are subjected to Summarization.The proposed Privacy Preserving Text Document Summarization generates crisp privacy preserved summary of the input text document which consists of the most relevant domain-specific information related to the text document without defying an entity privacy constraints with the compression rate of 11%, the precision of 86.32%, and the recall of 84.28%.