Reviewerly/exHarmony huggingface dataset:
Enhancing Physical Layer Security via Information Hiding and Chaotic Frequency-Hopping Signal

Abstract With the development of super computation ability and invention of quantum computer, the conventional calculation quantity based encryption system suffers great impact. Safeguarding data confidentiality in physical layer of wireless satellite communication system has attracted many eyes from academia and industry. In this paper, we propose a groundbreaking revolution method to enhance physical layer security (PLS) by information hiding technique, that is, embedding secret information into chaotic frequency-hopping signal using MFSK modulation. First, secret information to be transmitted is encrypted with chaotic binary sequence. Secondly, according to frequency-hopping pattern, select suitable modulation order and specific frequency corresponding to each encrypted data block under chaotic address sequence. Finally, the encrypted information is embedded into frequency-hopping Sine signal by MFSK modulation. The experimental results indicate that the proposed scheme is robust against various jamming attacks, such as power attenuation, noise adding, single-tone jamming, key exhaustive search, etc.
Blockchain Based E-Voting System

Abstract: Voting is the fundamental right for every nation. An Electronic Voting (E-Voting) system is a voting system in which the election process is notated, saved, stored, and processed digitally, which makes the voting management task better than the traditional paper-based method. Blockchain is offering new opportunities to develop new types of digital services. While research on the topic is still emerging, it has mostly focused on the technical and legal issues instead of taking advantage of this novel concept and creating advanced digital services. Blockchain-enabled e voting (BEV) could reduce voter fraud and increase voter access. Eligible voters cast a ballot anonymously using a computer or smartphone. BEV uses an encrypted key and tamper-proof personal IDs. Electronic credibility services have become an integral part of the information space. With the reliable implementation of basic services as an electronic signature and electronic authentication, it is possible to build more complex systems that rely on them, particularly the electronic voting system. In this project, the concept of developing an electronic voting system using blockchain technology is implemented.
A MATHEMATICAL PERSPECTIVE OVER THE MIND-BODY REDUCTION PROBLEM

Is mental phenomena reducible to body phenomena? Reductive Analytical Method (RAM) have algebraic roots. “To reduce” translates, in a Cartesian sense, to the action of isolating independent variables. If RAM were dismissed, multiple variable problems would either: require more time and resources; be prohibitively difficult or unsolvable. Arguably, this bears truth to the majority of hard science’s problems. Recent cognitive and neuro imagery studies included mental phenomena to RAM’s scope, defying the tradition. Information Theory (IT) provides quantitative methods for the information contained: in the whole; in the sum of its parts; and in their relation. Justifying why it seems useful in evaluating RAM. According to IT: no set’s information can be greater than the information in the sum of its parts; RAM only provides a partial account of neuronal dynamics. The negative and affirmative answers to the mind-body reduction question are, respectively: quantifying the whole as “greater than the sum of its parts”; extrapolating RAM’s scope. Both answers seem to imply some mathematical claims, but, if our IT interpretations are correct, lack the mathematical ground. Novel and Traditional research methods have tried untangling the mind. Methods accounting for mind’s tangled nature may contribute to debate as well.
Letter from the Editor

Dear Reader,&#x0D; &#x0D; This past season, the journal’s editorial board continued to engage with the scientific community through the release of our newest Spring 2022 issue, production of online content in the form of blogs, and a fundraising event for Help Ukraine 2022. With a combination of in-person and online meetings, the journal maintained an active campus-wide and online presence. &#x0D; &#x0D; The journal released its first print edition with the publication of the Fall 2021 issue, which was well-received and marked an important achievement for the editorial board. A copy of this printed issue will be kept in the Columbia Libraries archive. We credit the Production and Design team for their work in converting the online formatting into an issue suited for printing. We anticipate more print editions to be released in the near future for upcoming issues. &#x0D; &#x0D; This Spring 2022 issue explores a broad range of global health topics from the Breast Cancer Screening Programme in Nigeria to current issues with the information ecosystem. This issue also delves into ongoing public health concerns such as eradicating Guinea Worm Disease and addressing the healthcare needs of ethnic minority populations. We thank our authors and peer reviewers for their submissions and contributions without which our journal could not exist.&#x0D; &#x0D; We would like to thank our staff across all the teams – the Editorial Review Board, Production &amp; Design Board, Online Board and the Business &amp; Communications Board – for their dedication and commitment towards the journal. We are also especially grateful for the continued support from the Columbia University Libraries and the Faculty Advisory Board composed of Digital Publishing Librarian Michelle Wilson and faculty advisor Professor James Colgrove. &#x0D; &#x0D; Sincerely,&#x0D; Scarlet Au &amp; Sophia Spiegel&#x0D; Co-Editors-in-Chief, The Columbia University Journal of Global Health
“It's Frustrating, but…”: Brazilian and Indonesian Teachers’ Resilience to Assist Deaf Students’ Online Language Learning

Due to the recent increase in studies on emotions in Applied Linguistics and, especially now, in pandemic times, it opens more discussion to relate teachers' emotions with several other aspects including resilience. Therefore, this research aims to analyze language teachers’ experience in teaching deaf students in Recife, Brazil, and Malang, Indonesia. The methodology applied was qualitative. This study involved teachers in Recife, Brazil, and Malang, Indonesia. The teachers selected to be interviewed in this study were those who had experience teaching deaf students for at least five years and those who, during the pandemic times taught online. Two teachers were taken from each city. Findings point out, among other things, that decreasing the number of students per class and having parents involved in the process may help improve students' learning and teachers' experience and resilience. Based on the data on the implementation of language learning and the teachers' perception of the benefit, the constraints, and strategies in online language learning, resilience is triggered by the professional, personal, institutional, and community challenges.
Analysis Of Human Femur Bone At Different Orientation Under Three Point Bending Load Using Fea

The femur bone is the human body's largest and strongest bone.If this bone is affected in any accident, the injured person will be paralyzed.This work describes the fracture morphology of femur bone derived from the loading mechanisms of bending at various orientations over the femur bone.The maximum strain and displacement were determined using a finite element (FE) analysis, which was highly dependent on the precision of the recorded geometry and appropriate assignment of material properties.In this research, FE analysis was performed in a tantom three-point bending test.In actual life, loading cannot always be expected in a fixed direction.Here, the load was applied at the middle of the bone at eight different orientations, 45 apart.Maximum strain, displacement, and orientation over the femur bone were identified by this analysis.
Research Paper on Fake Online Reviews Detection using Semi-supervised and Supervised learning

Abstract: Today's business and commerce are heavily influenced by online reviews. Most online product purchase decisions are based on customer reviews. As a result, opportunistic individuals or groups seek to shake product reviews in their favor. Fake online reviews have a significant impact on the efficiency of online consumers, merchants and e-commerce markets. Despite academic efforts to study fake reviews, there remains a need for research that can systematically analyze and summarize their causes and consequences. This task provides a semi-supervised and supervised text mining model for detecting fake web reviews and comparing their effectiveness to hotel review datasets. Keywords: Semi-Supervised. Supervised, Detection, Fake Review, Marketing
Impact of Knowledge Management on Organizational Effectiveness: A Case Study of Health Department AJ&amp;K

The purpose of this study was to examine the impact of Knowledge Management on Organizational Effectiveness in the government sector AJ&K.A quantitative casual hypothetical study was conducted.Sample was drawn from Government Health Sector AJ&K and targeted the employees of Government health sector AJ&K, using non probability random sampling techniques.Questionnaires were distributed among the sample of 110.Results indicated that there is a significant impact of knowledge management of organizational effectiveness and it is an important organizational and social concern.This study examines knowledge management and its impact on organizational effectiveness.Dimensions of knowledge management like knowledge conversion and knowledge sharing has statistical impact on organizational effectiveness.The research's findings show that knowledge management strengthens the organization effectiveness through bringing innovations.This ultimately increases the productivity of the organization.This research helps policy makers and decision makers to focus on knowledge management strategies that help to increase the organizational effectiveness through increasing productivity and enhancing innovation and creativity within an organization.
AN EXAMPLE OF CHATBOT IN THE FIELD OF EDUCATION IN THE REPUBLIC OF SERBIA

Students can retrieve information from the website or use the services of an existing information system (provided the information system is on the internet). However, we know from experience that searching a website is time-consuming or even inaccurate, and the functionality of the information system is limited. Chatbot makes it more natural, efficient and faster. Chatbot can understand natural language, i.e. written text and voice messages. It gives precise answers and performs all actions intended by the website and / or the information system. But the website and the information system do not have the richness of language that the chatbot has. You have to log in to the information system and know how to use it, and each new version requires new learning. If you know how Viber or FB Messenger work, you probably know how to use chatbot. The services provided by chatbot are visible on communication platforms used by a large number of users, and thus the quality of these services is better. Due to the use of chats, the human resources of the educational institution are redirected/retrained to more responsible and creative jobs because the workload has been relieved. The paper presents a chatbot called ADA, developed at the Belgrade Business and Arts Academy of Applied Studies (BAPUSS), and shows basic usage statistics. It also points out the importance of chatbots as a communication channel in educational institutions.
Squeezing Limit of the Josephson Ring Modulator as a Non-Degenerate Parametric Amplifier

Two-mode squeezed vacuum states are a crucial component of quantum technologies. In the microwave domain, they can be produced by Josephson ring modulator which acts as a three-wave mixing non-degenerate parametric amplifier. Here, we solve the master equation of three bosonic modes describing the Josephson ring modulator with a novel numerical method to compute squeezing of output fields and gain at low signal power. We show that the third-order interaction from the three-wave mixing process intrinsically limits squeezing and reduces gain. Since our results are related to other general cavity-based three-wave mixing processes, these imply that any non-degenerate parametric amplifier will have an intrinsic squeezing limit in the output fields.
the influence of rule frames on inferences between disjunctive sentences

A current issue in natural language semantics and the psychology of reasoning is how people make inferences between two disjunctive sentences (e.g., inferences between There is A or B or C and There is A or B; inferences between There is at least one of A, B, and C and There is at least one of A, B, C, and D) with two different sets of elements. The interdisciplinary question whether different linguistic forms (OR versus quantifier rule frames) of equivalent disjunctive sentences make a difference to human inferences between two disjunctive sentences with two different sets of elements can distinguish between syntactic and semantic accounts for reasoning. Classical logic, the Bayesian approach, the original and revised mental models theory all answer “no” to the question. Alternatively, an epistemic rule relation account based on comparing explicit rules (that is, syntactic gestalts) of premise and conclusion sentences answers “yes” to the question. Three experiments found the effect of rule frames that quantifier frames elicited more correct inferences than OR frames, and these two rule frames elicited opposite response patterns. This finding favors only the epistemic rule relation account, and suggests the general implication that inferences between two compound sentences may primarily be based on the epistemic rule relation between both, which is modulated by rule frame.Keywords: inferences between disjunctive sentences; rule frame; or; at least one; the epistemic rule relation account; framing effects
Function Consuming sebagai Tingkat Kecakapan Literasi Media Digital Masyarakat Yogyakarta

Digital competence is one of the skills for users in using digital media. Research on mapping the digital competence category of the people of Yogyakarta was carried out to know the media digital positioning competence of digital media users. The position of digital media user skills is categorized by the k-NN (k Nearest Neighbor) technique data mining method. The objective of this research using the k-NN technique data mining method was carried out by compiling categories that refer to attributions where the attribution refers to the ten competencies of Japelidi's digital media users. The digital media user skills category has four quadrants: Function Consuming, Function Prosuming, Critical Consuming, and Critical Prosuming. This research was conducted in Yogyakarta from June-July 2020 because, during this period, there was a surge in digital media users due to the pandemic. The findings in this research provide information that the competence of using digital media for Yogyakarta residents in the period of June-July 2020 is in the Function Consuming section, and it is in the first quadrant
Polarity Detection and Feature-Based Summarization for Aspect Based Sentiment Analysis Dataset

Aspect Based Sentiment Analysis (ABSA) aims to perceive the opinion of the majority of reviewers for each feature (aspect category) of the product.We target both Aspect Term Polarity (ATP) and Aspect Category Polarity (ACP) subtasks of ABSA.We retrieve different word vector-based representations of sentence and augment them with n-gram and sentiment features using novel algorithm.We employ supervised machine learning approaches and propose the ensemble of Logistic Regression, k-Nearest Neighbor, and Support Vector Machine models for these subtasks.We experiment with four major domains from Hindi ABSA Dataset and report increase in performance accuracy by 16% for ATP subtask and 2% to 13% across domains for ACP subtask over results from researchers who released this dataset.Secondly, we also propose a novel WFBOS method to compute the Summary Score [range: -100 to 100] of each category from a particular domain.We make use of frequency of positive, neutral, negative, and conflict sentiment, of each aspect category from among the reviews of a particular domain in Hindi ABSA Dataset to do this computation.
People Counting in Crowd: Faster R-CNN

Abstract-Because of its vast range of operations, people counting in crowds is a significant challenge in the field of computer vision. To achieve further dependable results of crowd counting, head discovery grounded ways are used rather than viscosity chart grounded crowd counting ways. This is because, in case of viscosity charts, it isn't always the correct position which contributes to final crowd count. This leads to unreliable results especially in case of false positives. This makes the entire task of head discovery in crowded scenes a grueling one to be solved. While face discovery has reached maturity, the more general task of chancing people in images and videotape still remains to be veritably challenging. Count of people may also be demanded for the statistical purposes which help to concoct marketing strategies or it may be used for crowd control in colorful situations image processing is a fashion for applying operations on an image in order to ameliorate it or prize precious information from it. In our design, input to the system is an image/ videotape of the surveillance system which further divided into image frames. Our proposed system gives the count of people in the scene using the Faster R- CNN object discovery algorithm.
PENINGKATAN PRESTASI BELAJAR MELALUI METODE RESITASIPADA PELAJARAN MATEMATIKA

The background of this research is the lack of student achievement results and the low understanding of reading assignments given by the teacher. &nbsp;This research is an action research that aims to determine the results of student achievement in class IV C SD N Pujokusuman 1 Yogyakarta City, Special Region of Yogyakarta. &nbsp;Implementation of activities in October to December 2021 by going through two cycles. Educators need methods to support the learning process so that students can absorb and understand the knowledge from the teacher. &nbsp;This study uses the method of recitation or assignment. &nbsp;With this method, it is expected that student learning achievement can increase. &nbsp;The data from the study were presented descriptively with the data collection technique using sampling through the data from the test results.This research was conducted through two cycles in each cycle there were two meetings. &nbsp;After the action was taken , the results showed that there was an increase in the percentage of achievement in cycle 1 which obtained an average of 52.79 while the second cycle obtained an average of 81.94 and had an increase of 29.5% so that the recitation method could improve student learning outcomes. &nbsp;.
Text Similarity Using Siamese Networks and Transformers

Abstract-- In result-oriented conversational models like message renders and chatbots, finding the similarity between the input and output text result is a big task. In general, the conversational model developers lean to provide a minimal number of utterances per instance, and this makes the classification a difficult task. This problem becomes more difficult when the length of the processed text per action is short and length of the user input is long. Identical sentence pair detection reduces manual effort for users with high reputation. Siamese networks have been one of the best innovative architectures designed in the field of natural language processing. A Siamese network was initially designed for computer vision applications. Later the core concept of this algorithm was designed for NLP ,to identify similarity for two given sentences. Siamese networks are used in this algorithm. It's an artificial neural network also known as a twin neural network that works in tandem on two independent input vectors to calculate equivalent output vectors using the same weights. Also there are few commonly addressed drawbacks like word sense disambiguation and memory intolerance of initial inputs for sentences having more than 15-20 words. To tackle these issues, we propose a modified algorithm that integrates the transformer model implicitly with the core part of the siamese network. Transformer model helps to generate each output position based on the semantic analysis of overall sentence and can also deal with homonyms, by extracting its meaning based, which is syntactic based and semantic based on the overall sentence or paragraph or text.
EVALUATION OF GROUNDWATER IRRIGATION NETWORK PERFORMANCE TO IMPROVE THE OPTIMAL FULFILLMENT OF IRRIGATION WATER REQUIREMENT

The deficit of SDTA 608 groundwater discharge in the Kesambi Village, which is used as a source of the irrigation networks, occurs due the nature issues and the transformation of farmer’s socio-economics. This study observes the irrigation network’s performance related to water needs based on the mandate of the Minister of PUPR No. 12/PRT/M/2015. The irrigation network’s performance projected by six parameters, i.e: productivity, infrastructure, supporting facilities, organization, documentation, and the Water User Association (P3A). The technical aspect of the irrigation network’s performance is studied by observations and measurements of the irrigation network efficiency to assess the performance of infrastructure and supporting facilities. Its economic aspect is studied by calculating the value of productivity using K-factor, fulfilling water needs, realizations of planting areas, rice and secondary crop productivity, and the harvesting value. The social aspect was studied with interview with the sample of 24 WUA’s members. The result of the technical aspect performance was 72.5% or minor issues that require maintenance and cares. From the economic aspect, irrigation network’s performance got 74.6% or in a good category, but still need to improve the right rotation’s system to prevent the water shortages. From the social aspect, irrigation network’s performance got 73% or in a good category, but still need a strategy to strengthen the role of WUA at the irrigation management through technical training and developing the human resources.
Real Time Sign Language RecognitionReal Time Sign Language Recognition

Abstract: With regard to hearing and vocally impaired individualities, communication with others is a way longer struggle for them. They are unfit to speak with traditional individualities duly. They face difficulties in getting jobs and living a traditional life like others. In this paper, we are introducing a smart communication system for hearing and vocally impaired individuals and also for normal people. The overall delicacy of the system is 92.5, with both the hands involved. The main advantage of this system being proposed over the former system is that in the former system the signs can be detectedby the camera only when the hands are covered in gloves whereas in this proposed system, we have tried our swish to overcome that disadvantage handed by the former system. Keywords: Open CV, Google API, Raspberry Pi video core GPU, image pre-processing, feature extraction.
Assessing Deep Generative Models on Time-Series Network Data

This paper explores whether Generative Adversarial Networks (GANs) can produce realistic network load data that can be utilized to train machine learning models in lieu of real data. In this regard, we evaluate the performance of three recent GAN architectures on the Telecom Italia data set across a set of qualitative and quantitative metrics. Our results show that GAN generated synthetic data is indeed similar to real data and forecasting models trained on this data achieve similar performance to those trained on real data.