Reviewerly/exHarmony huggingface dataset:
Finding Minimum Connected Subgraphs With Ontology Exploration on Large RDF Data

In this paper, we study the following problem: given a knowledge graph (KG) and a set of input vertices (representing concepts or entities) and edge labels, we aim to find the smallest connected subgraphs containing all of the inputs. This problem plays a key role in KG-based search engines and natural language question answering systems, and it is a natural extension of the Steiner tree problem, which is known to be NP-hard. We present RECON, a system for finding approximate answers. RECON aims at achieving high accuracy with instantaneous response (i.e., sub-second/millisecond delay) over KGs with hundreds of millions edges without resorting to expensive computational resources. Furthermore, when no answer exists due to disconnection between concepts and entities, RECON refines the input to a semantically similar one based on the ontology, and attempts to find answers with respect to the refined input. We conduct a comprehensive experimental evaluation of RECON. In particular we compare it with five existing approaches for finding approximate Steiner trees. Our experiments on four large real and synthetic KGs show that RECON significantly outperforms its competitors and incurs a much smaller memory footprint.
An Approach to Inconsistency-Tolerant Reasoning About Probability Based on Łukasiewicz Logic

In this paper we consider the probability logic over Łukasiewicz logic with rational truth-constants, denoted FP(RPL), and we explore a possible approach to reason from inconsistent FP(RPL) theories in a non-trivial way. It basically consists of suitably weakening the formulas in an inconsistent theory T, depending on the degree of inconsistency of T. We show that such a logical approach is in accordance with other proposals in the literature based on distance-based and violation-based inconsistency measures.
The Assistance of English Learning during the Covid-19 Pandemic in Jakarta’s Orphanage

The community partnership program was administered in the form of online assistance for English learning of the grade X of senior high school students. The partner was an orphanage belonging to the local government in DKI Jakarta Province. The objective of the assistance program was to motivate the English learning and find the solution for their problem in understanding English at school. Fourteen boys participated in this program. One meeting was held in the orphanage with the person in charge and four asynchronous meetings with the participants were conducted in three months. In practice, most of the students showed their motivation in terms of involving the English discussion and completing the tasks as well. Unfortunately, the signal of internet connection did not support the online learning and some of the students were in quarantine due to coronavirus infection. In conclusion, they were not ready to study online as several obstacles arose such as the weak internet signal and their absences. Therefore, they need to study English in a room with a teacher where all of them can communicate with each other in a friendly atmosphere. By doing so, they are possible to improve their English mastery.
Photocatalytic Degradation of Phenol in Wastewater: A Mini Review

A major public health concern in many developing countries, including Nigeria, is the quality of their water supply. Everything a live entity does depends on water, a fundamental component of the biosphere. To ensure that water is safe for industrial and home use, it must be treated before consumption. However, phenolic compounds are found in our water bodies due to the polluted wastewater from industrial, agricultural, and home activities. Nature also has a role in their occurrence. These substances are poisonous and can cause long-term harm to both humans and animals. This paper reviewed research on the photodegradation of phenol utilizing nanoparticles in water treatment. This provides additional information and facts on cost-effective methods of treating wastewater and mineralizing phenol into valuable chemicals.
The Insertion of Person References Motivated by Pragmatic Differences in Estonian-English-Japanese Facebook Communication

Sociopragmatic differences have been examined between many languages and cultures, including English and Japanese. However, Estonian and Japanese have yet to be compared, and thus this data of EstonianEnglish-Japanese communication on Facebook offers a look at a type of code-switching that is caused by the sociopragmatic differences between Estonian and Japanese – i.e. the insertion of person references from Japanese to Estonian and English utterances by native Estonians. I am using the Estonian-English-Japanese Facebook communication dataset from Kilp (2021) with new added conversations. The data consist of synchronous private Facebook messages between 2015 and 2021: a total of 7 informants, 50 conversations and 14,681 tokens. A usage-based approach and a qualitative analysis are applied to the data from individual informants and particular cases. These data show that a perception of pragmatic differences causes the insertions of the Japanese person references, senpai ‘senior’ and sensei ‘teacher’, in various forms (affixed to the name, replacing the name, elongated, capitalised, in the Latin alphabet, in Japanese script) in Estonian and English utterances, while factors such as vertical hierarchy, horizontal solidarity and (situational) salience play an important role in facilitating insertion. Keywords: deixis, code-switching, vocative, usage-based approach, contact linguistics, computer-mediated communication, salience, Estonian, English, Japanese
Students’ Self-regulation in English Reading Comprehension during Online Class in Yogyakarta Private Senior High School

The learning process in Indonesia has predominantly been conducted online since March 2020 due to the COVID-19 pandemic. This online learning mode has also influenced students’ motivation in learning, especially in comprehending reading texts. Considering that problem, the researchers sought to investigate how the students regulated their comprehension in reading during an online class. This research used a mixed-method. The questionnaires were distributed to 30 students and analyzed as quantitative data. Then, the researchers chose four students randomly for interview purposes. The interview transcript was used as qualitative data. In conclusion, not all of the students could regulate themselves in comprehending English text during the online class well. Based on the data, students who could regulate themselves in comprehending the English texts during online class should develop the following procedure: (1) implementing learning autonomy, (2) implementing learning focus, and (3) using critical thinking. Meanwhile, students who could not regulate themselves well were inclined to perform minimally. Since students had different ways to regulate themselves, the teacher needed to monitor the students in online learning process so that the students could achieve a meaningful learning process. To improve students’ regulation in reading comprehension, the teacher can implement suitable learning activities.
PENGARUH PENERAPAN MODEL PEMBELAJARAN KOOPERATIF TIPE THINK PAIR SHARE TERHADAP HASIL BELAJAR MATEMATIKA PESERTA DIDIK KELAS XI MIPA SMA NEGERI 1 PASAMAN

Mathematics learning outcomes are benchmarks that can be used to see how far students understand in the concepts that being taught. But in reality, students of class XI MIPA SMAN 1 Pasaman have mathematics learning outcomes that have not been achieved optimally. To fix that problem, the Think Pair Share (TPS) learning model can be applied. The research aims to determine whether students who learn with the TPS have better outcomes of mathematics learning than students who learn to use direct learning model and to describe how the development of mathematics learning outcomes of students who learn with the TPS learning model. This research is a combination of descriptive research and quasi-experimental research. The design of the research that used was a nonequivalent (posttest only) control group design. The results of this research are the experiment class and control class students have an average of each class 88.67 and 81.56. The conclusion of this research is that the experiment class had better learning outcomes than the control class. Its obstained based on the hypothesis test, with P-value 0,000. Keywords–Mathematics Learning Outcomes, Think Pair Share Learning Model, Quasi Experiment
Research on COVID-19 document fine-grained classification based on graph neural network

Since the outbreak of COVID-19, academia has published tens of thousands of new papers. Facing so much literature knowledge, how to realize the fine-grained classification of covid-19 literature and help researchers carry out research? This is an urgent problem to be solved. This paper makes COVID-19 text classification graph data set, designs covid-19 scientific literature fine-grained classification model LC-GAT based on graph attention network, adds attention mechanism at word level, sentence level and graph level, effectively retains the classification information contained in article title and key words, and significantly improves the performance of covid-19 scientific literature fine-grained classification. This paper has positive significance for the classification of COVID-19 scientific literature.
Sistem Informasi Akuntansi Penerimaan dan Pengeluaran Kas Berbasis Web : Studi Kasus pada Praktik Dr.Aminah Barabai

Accounting information system (AIS) is a system that is useful for collecting, storing and processing financial and accounting data used by decision makers. Accounting information is a generally computer-based system and method for tracking accounting activities in relation to information technology resources. This study aims to create an accounting information system for cash receipts and disbursements. The method used is R&amp;D (research and development) for making an accounting information system for cash receipts and cash disbursements, a case study in the practice of dr.AMINAH Barabai. The results of this study can be used as a web-based cash receipt and disbursement application program and can help dr.Aminah's practice to record patient data, record transactions and find out information related to cash receipts and disbursements
A Vulnerability based Attack Detection and Mitigation in Cloud SaaS Framework

Cloud computing provides various cost-effective on-demand services to the user and so it is rising up as a real trend in the IT service model.More particularly, the security is the ultimate question in the mind of each cloud user.A huge interest is being paid by the research community to detect the attack exist in the network.This research work intends to introduce a novel framework that combines the attack detection and mitigation, which gives the SaaS provider to decide relevant fields to be extracted, when huge traffic is available.Deep learning-based attack detection is carried out and based on the vulnerability in the network, the model switches to mitigation process.Initially, the feature selection is carried out by Opposition Based Crow Search Algorithm (OCSA).The selected features are subjected to attack detection process via Deep Belief Network (DBN) model, where the presence of attacks is determined.Subsequently, the 'vulnerability assessment' is carried out by evaluating the risk level via correntropy variation features.This phase decides 'how vulnerable the network is' with the presence of attack.This decision is based on fixing a threshold on risk level (RL).Moreover, the decision tells whether to execute the 'mitigation process' or not.In the attack mitigation phase, bait-based mitigation process is carried out.The proposed vulnerability-based attack detection and mitigation system beat the traditional methods with a packet loss ratio of 16% and a throughput of 92%.
Optimalisasi Saluran Komunikasi Berbasis Gelombang Mikro Sebagai Alternatif Sistem Pemantauan Curah Hujan

As a vast archipelagic country with diverse topographic conditions and has an annual average rainfall of more than 2000 mm, Indonesia is prone to hydrometeorological disasters. Based on Indonesia's disaster data, throughout 2021 there were 3,658 incidents of floods and landslides distributed throughout Indonesia. This makes real-time rainfall monitoring with high density indispensable. Indonesia currently has a rainfall monitoring system about 1000 automatic rain gauges, so an increase in the spatial resolution of network is necessary. The increasing density of monitoring equipment using rain gauges and weather radar poses the problem of high procurement and operational costs. Therefore, several alternative rainfall monitoring systems are needed. In this article, we review several studies that focus on the utilization of terrestrial and satellite communication link operating in high frequency bands as an alternative for measuring rainfall. Optimization of the satellite communication system network is more suitable than terrestrial networks to be applied in Indonesia with archipelagic areas because it has a large number of point distributions with wider coverage. The use of artificial intelligence with deep learning techniques such as one dimensional convolutional neural network (1D-CNN) is also very promising to estimate rainfall intensity because it has a high accuracy of 93%..
Reorganization of the National Network of Mass Libraries: From the History of the State Library Policy of the 20th Century

The centralization of libraries in the works of domestic experts has received an ambiguous assessment. The experience of the zemstvo system, the development of network construction by mass libraries were negatively interpreted for ideological reasons. A negative assessment of the work on the creation of a unified library network in the pre-war period prevented its development. It took decades for the party-state leadership to revise the criticism of the idea of centralization. During the second half of the 20th century, the centralization of library management structures was supplemented by technologies of interlibrary interaction. The introduction by mass libraries of standards for the bibliographic description of documents, the systematization of funds based on domestic tables of library and bibliographic classification allowed to join the work of interlibrary subscription, depository storage of funds.
Robust Training with Feature-Based Adversarial Example

Adversarial training is an efficacious defense approach to protect classification model against adversarial attacks. In this paper, we reveal that a significant difference exists between the feature map of the original sample and that of its corresponding adversarial version. Based on this main insight, we propose a novel robust training on feature-based adversarial examples approach called FPAT, where training examples are generated by maximizing the loss function between the clean and the adversarial feature maps. We show via extensive experiments on MNIST, SVHN and CIFAR-10, that our proposed method is as effective as the state-of-the-art robust training methods. Especially, when the adversarial perturbation is of a large radius or the number of adversarial steps of training samples is small, FPAT achieves leading robustness.
A GEOMETALLURGICAL PERSPECTIVE ON RESOURCE ESTIMATION AT LEGACY MINE SITES

Traditional approaches used to define mineral resources are not directly translatable to legacy mine sites. For example, elemental enrichment relative to crustal abundance provides valuable insight when defining a mineral deposit, but at legacy sites extra caution is necessary because unlike a new mine, the material has already been processed. This processing provides several benefits such as reduced comminution requirements, substantial knowledge from the outset, and the opportunity to perform waste remediation. However, elements previously unrecovered are going to be more difficult to recover than would be expected given equivalent assays at a greenfield operation. Additional factors must be considered in assessments of the critical mineral potential of legacy sites. Critical elements produced as byproducts, such as In, Te, and V, are not major economic motivators for operations. In these instances, recovery is only economical feasible due to production of the primary commodity. Further, most byproduct recovery is only possible due to concentration during the downstream metallurgical processes applied to the primary commodity. Assaying alone does not address the interdisciplinary relationship between mineralogy and metallurgical processing. Assay based estimates can grossly overestimate the producible critical elements contained at legacy mine sites by including the fraction that would not be enriched into downstream processes. This presentation examines tellurium production and other examples to highlight and address the challenges in resource estimations for legacy sites. The presentation explores the substantial role historical processing methods have on the recoverability of contained elements, in addition to the potential routes for recovery based on technologies available today and under development.
ANALYSIS OF SHARIA ACCOUNTING AS INFORMATION SYSTEMS IN INDONESIA

Accounting is an information system that identifies, records, summarizes, classifies, and reports data related to economic events to enable users to make informed decisions. While in sharia accounting, the word 'sharia' generally means the path that we must go through. A Muslim certainly cannot escape from Islam. after saying the shahada, he must follow the rules of Allah and the Messenger," he added. This research is alibrary research, namely a special exploration where the study is carried out by following and evaluating literary works and which focuses on examining library materials. The information investigation strategy used is a substance examination technique or also known as content examination, which is an exploratory technique used for an intelligent and substantial resolution of information given the unique circumstances. The results of this study indicate that Islamic accounting is one of the efforts to rearrange current accounting in a humanist and dignified structure. The reason for holding sharia accounting is to develop business with humanist, emancipatory, supernatural and philosophical knowledge. Therefore, through sharia bookkeeping, social reality will be built through satisfying videos of monotheism and divine accommodation, all of which are equipped with the point of view of khalifatullah fil ardh. Basically the sharia accounting information system underlines the characteristics of Islam both in the object of the bookkeeping and the data frame, so that the Islamic accounting data framework has an extraordinary obligation in moral matters.
Resumable Zero-Knowledge for Circuits from Symmetric Key Primitives

Consider the scenario that the prover and the verifier perform the zero-knowledge (ZK) proof protocol for the same statement multiple times sequentially, where each proof is modeled as a session. We focus on the problem of how to resume a ZK proof efficiently in such scenario. We introduce a new primitive called resumable honest verifier zero-knowledge proof of knowledge (resumable HVZKPoK) and propose a general construction of the resumable HVZKPoK for circuits based on the “MPC-in-the-head" paradigm, where the complexity of the resumed session is less than that of the original ZK proofs. To ensure the knowledge soundness for the resumed session, we identify a property called extractable decomposition. Interestingly, most block ciphers satisfy this property and the cost of resuming session can be reduced dramatically when the underlying circuits are implemented with block ciphers. As a direct application of our resumable HVZKPoK, we construct a post quantum secure stateful signature scheme, which makes Picnic3 suitable for blockchain protocol. Using the same parameter setting of Picnic3, the sign/verify time of our subsequent signatures can be reduced to 3.1%/3.3% of Picnic3 and the corresponding signature size can be reduced to 36%. Moreover, by applying a parallel version of our method to the well known Cramer, Damgård and Schoenmakers (CDS) transformation, we get a compressed one-out-of-N proof for circuits, which can be further used to construct a ring signature from symmetric key primitives only. When the ring size is less than $$2^4$$ , the size of our ring signature scheme is only about 1/3 of Katz et al.’s construction.
Implementation of convolutional Neural network in FPGA for image Recognition

Neural Networks (NN) are being researched and improved to a degree that machines can closely resemble the capacity to execute complex tasks that only an intelligent animal is capable of.Vision used in the interpretation and recognition of the environment is one of such tasks that is being researched so future technologies can simulate vision in autonomous vehicles to further improve self-driving capabilities, increase driver convenience, help avoid accidents, and even autonomous delivery.Convolutional neural networks, inspired by the mechanics of animal vision, are utilized for the complex task of image recognition.Field Programmable Gate-Arrays (FPGA) recent developments have given it more parallel processing and processing speed making it a prime candidate for the implementation of NNs efficiently, with more processing capabilities and low response times compared with the alternatives.The objective of this work is to evaluate the performance viability of FPGA implementation of an image classification NN with acceptable accuracy and low response time.
A Python Library for Forensic File System Analysis

The search and recovery of information is a basic and foundational part of any digital investigation.In cases where the digital forensics experts work against storage media, filesystem analysis is a cornerstone upon which they will build their investigation.In this work, we present a Python library that lets programmers and examiners interact with the low-level structures and data from a filesystem in a simple, yet powerful manner.We also give a brief discussion on the use of this library in academic environments, to teach and show examples of operating systems concepts, and in specific digital forensics courses.
Investor Relation, Corporate Governance and Internet Financial Disclosure; Evidence from Pakistan Stock Exchange Listed Companies

Corporate governance is a system of rules and practices through which a business is directed and controlled. It also assists in balancing the interests of various corporate stakeholders. Earlier studies constructed certain instruments to achieve good corporate governance. In line with earlier studies, the main aim of the current study is to investigate the impact of investor relations and corporate governance on the internet financial reporting (IFR) disclosure. Quantitative data of the selected companies were analyzed. The results showed that ownership diffusion, type of auditor, firm size, and profitability of the firm have a positive and significant relationship with IFR, whereas institutional ownership and type of business activity are negatively associated with it. This study is useful for all types of stakeholders and specifically for policymakers, as well as for the academia.Keywords: business activity, corporate governance, institutional ownership, internet financial disclosure (IFR), profitability