Reviewerly/exHarmony huggingface dataset:
Idiosyncratic Requesters

There are some requesters – even frequent requesters – that defy easy categorization. After all, FOIA’s design is to open up government for all to see, regardless of the reasons for the request, the value of the records, or the likely effect of disclosure, except where relevant to determining an exemption to mandatory production or fee category.1 As a result, it attracts all manner of requesters. First-person requesting largely reflects the fact that people who have no other way of obtaining their own file use FOIA as a last resort. Commercial requesting merely represents data on what information companies actually need and want from the government and may provide insights into how government can better manage its information flow. These information constituents are certainly dominant across government agencies.
Analytical Theory

Frequent pattern mining (FPM) holds a significant position in data mining. Researchers have been a lot more dedicated on this concept from the last couple of years. With its many applications to data mining challenges like clustering and classification, the topic has been widely researched. The advent of FPM into real-world businesses resulted in an increase in profits and also aided in the promotion of sales. FPM has been put into operation in many domains like recommender systems, bioinformatics, and decision making. The literature dedicated to this field of research is abundant and has achieved tremendous progress such as in the development of efficient algorithms for frequent itemset mining. It also has a lot of importance in several requisite data mining tasks as well as in association and correlation analysis, analyzing patterns in spatiotemporal data, cluster analysis, and classification. Among the main challenges of data mining such as clustering, classification, outlier analysis, and FPM, FPM is considered as a leading problem in data mining by researchers. This chapter will provide a comprehensive study on FPM. The chapter will explore the key algorithms for FPM, privacy concerns, resources available, and different applications of FPM. The chapter concludes by highlighting future advancements.
Proposal of Recurrent Attention Module for Capturing Subtle Facial Expression Changes

Facial expressions are expressed by subtle changes in the shape of the eyes and mouth, wrinkles between the eyebrows, etc. However, it is difficult to capture these changes. In this study, we propose a Recurrent Attention Module (RAM) and a facial expression recognition method using RAM to capture subtle changes in facial expressions. In our experiments, we used CK+ and eNTEFRACE05 databases. In CK+, the recognition accuracies of ConvLSTM and Enhanced ConvLSTM are 93.0% and 95.7%, respectively, while the addition of RAM improves the accuracies by 2.7% and 1.2%, respectively. Furthermore, the recognition accuracies of ConvLSTM and Enhanced ConvLSTM in the eNTERFACE05 database were 39.8% and 49.3%, respectively, while adding RAM improved the accuracies by 4.6% and 0.6%, respectively. In comparison with the conventional method, the proposed method could not outperform the conventional method in CK+. On the other hand, the proposed method improves the accuracy of the eNTERFACE05 database by 0.6% over the conventional method.
Path Planning for a Jumping Rover Team With a Charging Station in Multi-Waypoints Visiting Missions

This paper demonstrates an innovative group of robots, consisting of jumping rovers and a charging station, improved traversability and extended energy endurance when traveling to multiple target locations. By employing different jumping rovers with distinct energy consumption characteristics and jumping capabilities, we focus on searching for the most energy-efficient path of each jumping rover in a multi-waypoints visiting mission with obstacles. As jumping rovers can jump onto or over some obstacles without navigating around them, they have the potential to save energy by generating alternative paths to overcome obstacles. Moreover, due to the energy demands for the multi-waypoints mission and the limited battery capacity, a charging station is considered to provide extra energy for enhanced endurance during the mission. We first apply a refined rapidly-exploring random tree star (RRT∗) algorithm to find energy-efficient paths between any two target locations. Then, the genetic algorithm (GA) is applied to select the most profitable combination of paths to visit all targets with energy constraints. Finally, we verify the improved mobility and energy efficiency in both virtual simulation and experimental tests using a group of customized jumping rovers with a charging station and the proposed path planning and task allocation method.
Hundreds of thousands of firms at risk from Exchange bugs

Four zero-day flaws in multiple versions of Microsoft Exchange Server are being actively exploited by malicious actors. Some estimates say that as many as 60,000 organisations, including government departments, healthcare organisations and major enterprises, may have been compromised in the US and maybe 250,000 globally, but it may be some time before we know the true number.
Reviewer’s Recognition

The Editor and Editorial Board of the Journal of Computing and Information Science in Engineering would like to thank all of the reviewers for volunteering their expertise and time reviewing manuscripts in 2021. Serving as reviewers for the journal is a critical service necessary to maintain the quality of our publication and to provide the authors with a valuable peer review of their work. Below is a complete list of reviewers for 2021. We would also like to acknowledge three outstanding Reviewers of the Year.2021 Reviewers of the YearAkhil Garg — Indian Institute of Technology Delhi, IndiaDehao Liu — Georgia Institute of Technology, USAAlejandro Salado — University of Arizona, USAThe Reviewers of the Year Award is given to reviewers who have made an outstanding contribution to the journal in terms of the quantity, quality, and turnaround time of reviews completed during the past 12 months. The prize includes a Wall Plaque, 50 free downloads from the ASME Digital Collection, and a one year free subscription to the journal.
Formal verification of pipelined cryptographic circuits: A functional approach

Cryptographic circuits are essential in systems where security is the main criteria. Therefore, it is crucial to ensure the correctness of not only the cryptographic algorithms, but also their hardware implementations. Formal methods, unlike the other validation techniques, guarantee the absence of errors.The problem is that designers still use conventional Hardware Description Languages (HDLs), which are poorly suited for formal verification. This paper presents a verificationmethodology for the pipelined cryptographic circuits using for-mal methods in an automatic manner. It consists on using the functional HDL Lava to describe and verify the equivalence between the behavioral specification and structural implementation of a circuit. To the best of our knowledge, we are the first to use this functional HDL for that computpurpose. To show the features of the proposed approach, it was applied to verify the pipelined implemen-tation of the cryptographic circuit AES (Advanced Encryption Standard).
Antara Ada dan Tiada: Studi Terhadap Tingkat Kehadiran dan Keaktifan Mahasiswa dalam Pembelajaran Online di Era Covid-19

The study aims to analyze the level of students’ attendance and interaction as well the availability of internet access during online learning in the era of Covid-19 pandemic. The case study is conducted at the English Language Education Study Program, Faculty of Education and Teacher Training State Islamic University of Mataram. This research is a part of quantitative research design with surveys. The researcher developed a set of questionnaire in Google Form and shared it to the students via WhatsApp group. 215 students participated in this study. It was found that most of the students attended the class throughout the meetings, but it could not be concluded that they participated during the class from the beginning till the end of the meeting. The causes were by the lack of internet access, instability of signal as well as the availability of the devices. The phenomenon showed that students exist in the class but do not exist. A successful learning occurs when interaction and communication run smoothly among students and teachers.
Peningkatan Kemampuan Digital dengan Pelatihan Luring Menggunakan Media Pembelajaran Online

Corona virus pandemic have shocked all over the world. All human being activities have collapsed because of the covid 19 outbreak. Schools closed, workplaces shut down, and places of worship are closed. The process of teaching and learning should go on eventhough some schools close down. The ministry of education determine to close schools and also ask students study at their home in order to stop corona virus transmission. They are in collaboration with TVRI to convey educational content during certain time. Furthermore, many schools apply for students study at home. They try to link the teachers and the students through online learning platforms. Under these inconvenience conditions, the parents and students have had to rapidly adjust in this situation and condition to make sure that the online learning runs well. The obstacles for parents and students learning from home are they don’t understand how to use various features on the zoom cloud meeting and google classroom. Furthermore, most of parents feel that they are not able to assist their children in online learning from home during corona virus pandemic. This community service focuses on the online learning platform, namely Zoom cloud meeting and Google classroom. The aim of this community service is to develop parents and students’ competence at online learning platform. The community service was conducted in Tegal Besar Estate. The result revealed that parents and students are able to use the zoom cloud meeting and google classroom’s features as an online learning platform during covid-19 outbreak.
Megasites for Health Care Information

The World Wide Web is made up of a myriad “sites,” each of which contains multiple layers, or “pages.” Although these pages and sites have real and intellectual finiteness, they are interconnected into the wondrous, and often overwhelming, weave of the Web. Some megasites discussed fit into the other end of the spectrum, containing few links, but gathering, organizing, and mounting on their site quality health care information. For example, Mayo Health Oasis's medical glossary only provides concise definitions but also hyperlinked cross-references and an audio pronunciation guide. The Health On the Net Foundation is a nonprofit international organization dedicated to promoting quality health care information on the Internet and helping to realize the Internet's potential as a valuable medical information resource. All that said, what follows is a highly annotated list of some of the best megasites we have seen. A team of Mayo Clinic physicians, scientists, writers, and educators produces Mayo Health Oasis.
The Direction of Subjects-Related Career Education by Developing Teachers’ Training Program Reflecting Journey Map: Focused on the Application of Design Thinking Process

The purpose of this study is to suggest the direction of subjects-related career education by developing teachers' training program that applies the design thinking process reflecting the journey map.Through this study, the necessity of career education training and the level of detailed requirements recognized through the experiences of secondary school teachers were confirmed.Furthermore, the necessity of presenting a teaching and learning methodology that can be applied and spread to various subjects was verified.The journey map was prepared and analyzed as a method to examine the necessity of career education training for teachers and find solutions.As a result of the study, a design thinking process application training program was developed, and a framework of a highly effective teaching model that can be applied to actual subject-related career lessons was presented.Through the presentation of such training programs, teaching and learning methods, it was possible to promote the composition and implementation of diverse youth career education based on the subject expertise of teachers.In the entire process of developing a design thinking application training program that reflects youth career education competency, teachers were able to experience creative problem-solving on their own and improve career education-related competencies through contextual understanding.
Edge detection based on Improved Non-Maximum Suppression Method

Semantic Segmentation and edge detection are important research fields for scene understanding in computer vision. A hierarchical framework called Contextual Hierarchical Model (CHM) was proposed for semantic image segmentation and edge detection. It learned contextual information using a Logistic Disjunctive Normal Networks (LDNN) classifier. The class average accuracy of CHM was improved by defining a global constraint using Conditional Random Field (CRF), Hierarchical CRF (HCRF), Higher order HCRF (HHCRF). The LDNN was improved by using proximal gradient method which minimizes the quadratic error and it had high convergence rate than gradient descent method. The weight and bias terms of LDNN was optimized by using Grey Wolf Optimization algorithm (GWO) which improves the classification accuracy and it also reduces time complexity of LDNN. During the edge detection using CHM, a multi-scale strategy was adopted to compute edge maps. A Non-Maximum Suppression (NMS) was used to obtain the thinned edges in images. However, it is a post-processing step which consumes additional time in edge detection process. So, in this paper, the edge detection is interpreted as a classification problem where the thinned edges in images are obtained without any post-processing step. It reduces the time consumption. Two key ingredients such as loss and joint processing are included in NMS to improve the detection of thinned edges. The loss is used to penalize the double edge detection and the joint processing is used to reduce the loss of edge detection by including a pair features as additional feature for edge detection. The pair features, Haar, Histogram of Gradient (HOG) and SIFT features are given as input to LDNN to detect the edges that improve the efficiency of CHM based edge detection.
Comparison of Modelling ASR System with Different Features Extraction Methods Using Sequential Model

Speech recognition refers to a device’s ability to respond to spoken instructions. Speech recognition facilitates hands-free use of various gadgets and appliances (a godsend for many incapacitated persons), as well as supplying input for automatic translation and ready-to-print dictation. Many industries, including healthcare, military telecommunications, and personal computing, use speech recognition programmes. In our paper, we are including the comparison between the different feature extraction methods (BFCC, GFCC, MFCC, MFCC Delta, MFCC Double Delta, LFCC and NGCC) using neural networks.
Modified approximate quantitative spectral analysis of rocks

Two main methods of approximate quantitative atomic emission spectral analysis have traditionally been developed in the Central Laboratory of the Karpinsky All-Russian Research Geological Institute (VSEGEI): evaporation from the channel of carbon electrodes and a more efficient spill method. When comparing these two methods for introducing a sample into the arc discharge, two factors should be taken into account: the amount of material entering the discharge and the completeness of evaporation of chemical elements. A sample weighing about 40 mg is almost completely evaporated from the channel of a carbon electrode. The spill-injection method provides a uniform supply of a large powder sample (400 – 500 mg) into the arc discharge. The first method of analysis is well suited for determination of volatile and nonvolatile elements, whereas the second method provides stable conditions for evaporation and excitation during all the time when the sample is supplied into the discharge. The spill-injection method is more sensitive to changes in the bulk composition of the sample and the particle size of the sample material compared to evaporation from the electrode channel. These are the main factors affecting the magnitude of the systematic error in determining the concentrations of semi-volatile elements. The errors that make up the total error of approximate quantitative atomic emission spectral analysis are systematically analyzed in spectral laboratories. Comparison of the results of analysis of the same samples (state standard samples) with the results of chemical methods over a period of several years revealed that the maximum contribution to the total error is attributed to the visual assessment of the content and visual interpolation, as well as to a discrepancy in interpretation of results after a long time, etc. The impact of various errors has been reduced through the use of the MAES analyzer and the wide capabilities of the Atom software, which offer a correct consideration of the background with the option of individual settings, the use of coefficients accounting for the interference effect, and the possibility of analysis by several analytical lines of each chemical element thus allowing the use of constant calibration curves for a wide range of rock compositions.
Pragmatics Principles of English Teachers in Islamic Elementary School

This qualitative study presents the research results on Pragmatics politeness in the language of English teachers in Islamic elementary schools. The problem formulation of this research focuses on what and how Pragmatics politeness is in the language of English teachers in Islamic elementary schools. The objectives of this study are (i) to describe the form of Pragmatics speech in the language of English teachers; (ii) to describe the tools used in using Pragmatics politeness in the teacher's language, English. The research approach used is qualitative research. Data were collected from various communication events in teaching English in the classroom between teachers and students by participating in observation techniques, note-taking/recording techniques, and interviews. Structurally, the various sub-illocutions were delivered with one core speech unit alone or with a combination of core speech (TI) and supporting speech units (TD) in the form of asking questions, commanding acts, and opening speech units (TB) in the form of greetings. Pragmatics politeness speech acts of English teachers and students are generally expressed in imperative sentences (active and passive), declarative sentences, and interrogative sentences. Second, the tools of Pragmatics politeness in the language of English teachers in Islamic elementary schools found in the speech of the teaching process can function as an action stimulator, a request for approval of the action, an invitation.Keywords: Politeness, Pragmatics, Islamic elementary school.
Interpersonal Communication Skills of Dyslexic Children and Implications for Guidance and Counseling Services

Interpersonal communication skills are very important possessed by every individual. This study aims to examine how communication skills possessed by dyslexic children, given that dyslexic children experience language barriers. The study was conducted using a qualitative approach through the case study method of three students at Griya Baca Pelangi who had been diagnosed with dyslexia. Data was collected through observation, interview, and documentation techniques. Next, the data were analyzed with the concept of Miles and Huberman. The results were obtained that the dyspersic communication skills of dyslexic children differ. In guidance and counseling services, communication skills of dyslexic children can be improved through group guidance services and can also be combined with responsive services in the form of individual counseling or group counseling
Utilizing Apriori Data Mining Techniques on Sales Transactions

The establishment of a marketing strategy is important for every business actor in the competitive world of business. Business operators must be able to develop sound marketing strategies to influence the attractiveness of consumers and to buy interest in the products provided so that the enterprise they operate can compete and have a market share and to maximize sales sales. To implement marketing strategies, references are required so that promotions can reach the right target, for example by seeking similarities between items. By using data mining techniques, these studies apply the a priori approach to the promotion of customer product recommendations by association rules on product sales transaction datasets to aid in the formation of applications between product items. The dataset represents a sample of sales of products for 2020. The application used for analyzing is RapidMiner, where a support value of &gt; 20% and confidence of &gt; 60% is determined. Each product package promoted is made up of 2 products from the calculation results. The two best rules that have value confidence is combined with 2 items (Cre1Cre2), (Cre1Cre12) and (Cre9Cre10). Based on the minimum support and confidence values that have been set, the results of the a priori method can produce association rules that can be used as a reference in product promotion and decision support in providing product recommendations to consumers.
Deploying Trust-Based E-Healthcare System Using Blockchain-IoT in Wireless Networks

Blockchain is a technology that solves problems of trust. A blockchain is a distributed layout with a constantly growing list of records, called blocks, and secured using cryptography. Conventional technologies such as the Internet of Things (IoT), Networks, or others are not feasible for security mechanisms because these technologies are highly centralized and have limited resources. In this chapter, we will link blockchain to IoT and look at its various expressions. We will use IoT and blockchain technologies in a common domain, especially for e-healthcare. IoT devices are used to monitor healthcare, which involves collecting and evaluating patient data periodically. The data collected is kept in a secure block by the blockchain, and the patient will be directly connected to healthcare professionals. The record will remain in a secure block, and only the patient will view the report. The hospital will no longer share the report to any other medical agency, and the entire information is held by only the patient. We proposed the IoT-blockchain model that communicates to the e-healthcare devices and is stored in the blockchain. The person who has credits can access the e-healthcare data and the representation of accessibility is also labeled in the use case approach.