Reviewerly/exHarmony huggingface dataset:
A Hybrid Video Based IoT Framework for Military Surveillance

Traditional border surveillance technologies like surveillance tower maynot always be feasible in hostile military area. Internet of Things (IoT)and Wireless Sensor Networks (WSN) has demonstrated great promisein serving applications like traffic monitoring, industrial process control,health care, surveillance etc. Using only scalar sensors suffers from highfalse alarm rate and failure to detect stealth intrusion movement. A hybrid system involving camera nodes increases the capture efficiency andreduces false alarm rate. Using camera nodes comes with additional challenges like high bandwidth demand and energy consumption. Continuouscapture and transmission of video streams can be highly energy consumingtask, given the resource constrained nature of battery operated nodes. Inmost applications like military patrolling, system should report the eventonly if a intrusion is detected. A framework to cater to needs of military area monitoring is proposed in the paper. The framework discussesthe system framework, protocol structure and suggested communicationprotocols
Bridging the Gap Between Requirements and Model Analysis : Evaluation on Ten Cyber-Physical Challenge Problems

Formal verfication and simulation are powerful tools to validate requirements against complex systems. [Problem] Requirements are developed in early stages of the software lifecycle and are typically written in ambiguous natural language. There is a gap between such requirements and formal notations that can be used by verification tools, and lack of support for proper association of requirements with software artifacts for verification. [Principal idea] We propose to write requirements in an intuitive, structured natural language with formal semantics, and to support formalization and model/code verification as a smooth, well-integrated process. [Contribution] We have developed an end-to-end, open source requirements analysis framework that checks Simulink models against requirements written in structured natural language. Our framework is built in the Formal Requirements Elicitation Tool (fret); we use fret's requirements language named fretish, and formalization of fretish requirements in temporal logics. Our proposed framework contributes the following features: 1) automatic extraction of Simulink model information and association of fretish requirements with target model signals and components; 2) translation of temporal logic formulas into synchronous dataflow cocospec specifications as well as Simulink monitors, to be used by verification tools; we establish correctness of our translation through extensive automated testing; 3) interpretation of counterexamples produced by verification tools back at requirements level. These features support a tight integration and feedback loop between high level requirements and their analysis. We demonstrate our approach on a major case study: the Ten Lockheed Martin Cyber-Physical, aerospace-inspired challenge problems.
Valency lexicon extracted from the Gigafida 2.1 corpus

The valency lexicon was extracted from the Gigafida 2.1 Corpus of Written Standard Slovene (https://www.clarin.si/noske/run.cgi/corp_info?corpname=gfida21) using specialized scripts for extracting data from corpora containing syntactic and semantic role annotations. The lexicon contains valency patterns for 14,595 Slovene verbs based on the JOS syntactic dependency system (http://nl.ijs.si/jos/bib/jos-skladnja-navodila.pdf) and the semantic role labelling system for Slovene with 25 semantic role labels.The lexicon consists of separate XML files for each verb. Each file contains the verb's lemma, its aspect, and its frequency in the Gigafida 2.1 corpus, followed by a list of all the semantic role labels present in all the verb's valency patterns, along with two measures for each semantic role label (listed in ): (1) valency_pattern_ratio, which indicates the percentage of the verb's valency patterns where the semantic role label is present; and (2) valency_sentence_ratio, which indicates the percentage of all the corpus sentences containing both the verb and the semantic role label out of a total of all corpus sentences containing the verb.The valency patterns (listed in ) contain the following:- the valency pattern's ID-number ( );- the number of corpus sentences in which the verb follows the valency pattern ( );- the semantic roles occurring in the pattern ( );- the syntactic structures occurring in the pattern ( ; if the syntactic structures contain prepositions, these are also included as additional information);- a human-readable representation of the valency pattern in Slovene ( , e.g. KDO/KAJ abdicira);- the corpus examples in which the verb occurs with the valency pattern ( ).In the examples, the components of the valency patterns are annotated with their semantic role labels and syntactic structures. Each valency pattern contains at least one example from the Gigafida 2.1 corpus and all the relevant examples from the ssj500k 2.2 corpus (http://hdl.handle.net/11356/1210).
Hand Gesture using Arduino

The modern world is filled with new things and technology. As we can see in present time most of the things are becoming gesture control. Gesture based interaction is becoming a necessity at home, office, gardens etc. This build will detect hand gesture from the motion sensor connected to Arduino. The hand gesture will work as an input which will act with PC or laptop. One of the key area of implementation of code using Python. We feel that we can help a little with our little contribution
The Human Person and Social Order: A Moral Perspective

The human person is the sacred element of every social and cultural initiative. It istherefore, the foremost presupposition of human sociality. The realization of its valuewithin the social order requires the recognition of its transcendent value. Thismetaphysical insight reveals ontological rapport of the person and society within thepurview of its moral and spiritual primacy. Individualism is a negation of society due toits inherent egocentric materialism. A social order of human rights, freedom and dignityis bound up with the spiritual resources of the person. A critique of metaphysics ofhuman nature reveals this truth as a fundamental pedagogy for socio-culturaldevelopment of contemporary society.
An analysis of third intermediate grade mathematics course book in the light of CFBT standards

The current research aimed to identify the availability of British (CFBT) standards in the mathematics course book for the third intermediate grade by analyzing its content, the research community consisted of the mathematics book in its first and second parts scheduled for third-grade intermediate students for the academic year 2020-2021. As for the research sample, it is the research community, while the research tool consisted of two parts, the first for content standards, and the second for process standards according to the list of standards. The validity of the tool was confirmed by presenting it to experts and referees. As for the reliability of the analysis,It has been calculated by two methods: reliability across others and reliability through time, where it appeared in a high percentage, the researcher relied on it on frequencies and percentages as statistical means in this research, the results showed the following:By analyzing the content of the mathematics book for the third intermediate grade In light of the standards (CFBT), which consists of two parts, the first section: content standards consists of three fields of arithmetic and algebra   in the first rank with a percentage of (60%), and engineering and measurement in the second rank with a percentage of (29%), and data processing in the last rank by (11%), As for the second section, Operations Standards, it consists of one fields, which is reasoning and solving problems, and it came at a percentage of (13%).In light of the research results, a set of recommendations and proposals have been written, including: Benefiting from the list of CFBT standards in developing a mathematics textbook for the third intermediate grade, and seeking to prepare national standards for curricula in Iraq in general and mathematics curricula in particular.
A New Technique for Managing Reputation of Peers in the Cooperation Approach for Privacy Protection

Protecting privacy of the user location in Internet of Things (IoT) applications is a complex problem. Peer-to-peer (P2P) approach is one of the most popular techniques used to protect privacy in IoT applications, especially that use the location service. The P2P approach requires trust among peers in addition to serious cooperation. These requirements are still an open problem for this approach and its methods. In this paper, we propose an effective solution to this issue by creating a manager for the peers' reputation called R-TTP. Each peer has a new query. He has to evaluate the cooperated peer. Depending on the received result of that evaluation, the main peer will send multiple copies of the same query to multiple peers and then compare results. Moreover, we proposed another scenario to the manager of reputation by depending on Fog computing to enhance both performance and privacy. Relying on this work, a user can determine the most suitable of many available cooperating peers, while avoiding the problems of putting up with an inappropriate cooperating or uncommitted peer. The proposed method would significantly contribute to developing most of the privacy techniques in the location-based services. We implemented the main functions of the proposed method to confirm its effectiveness, applicability, and ease of application.
Privacy-Preserving Electronic Healthcare with Self-Monitoring Devices using Trusted Execution Environments

The adoption of smart wearable devices has been on the rise over the past few years. These wearables are able to track the user's vital signs, making them valuable for use in the healthcare industry. Sharing this information with the user's healthcare provider has the potential to improve medical care by reducing medical misinformation. Currently, patients in the Netherlands are able to inspect their medical file at each healthcare provider they are attending, but they are unable to inspect all their medical files at one place. Moreover, they are not able to contribute to their own medical files. In this thesis, we propose the use of Trusted Execution Environments (TEEs) as an extension to the Polymorphic Encryption and Pseudonymisation (PEP) framework. PEP facilitates the exchange of medical data between multiple parties in a privacy-preserving manner. However, PEP suffers from collusion and scalability issues. The Distributed Polymorphic Encryption and Pseudonymisation (Dist-PEP) protocol is an improvement to PEP, and mitigates these issues. To make further improvements, the Distributed Polymorphic Access Management (Dist-PACMAN) protocol has been introduced to handle the access management more securely. By introducing TEEs, we make further improvements to the efficiency en scalability of the protocol. The result is a privacy-preserving framework that can be used to share the information gathered by the wearables with the user's healthcare provider securely and more efficiently. Additionally, the user can keep and inspect their own medical file at a cloud provider.
Emotion And Sentiment Analysis From Twitter Text

Social media like Twitter and Facebook are full of activities, emotions, and reviews from customers worldwide. Emotions are recognized improved through their adaptive use in maintaining basic services and lifestyles. Each emotion has individual characteristics: Anger, Surprise, Joy, Fear, disgust, sadness, etc. Each emotion also has characteristics in community with other emotions. We can distribute our moments, expressions, ideas, and mental state, national and international difficulties within the textual content, images, messages, and audio and video posts. Although we have different conversation types, text transmission is one of the most popular conversation techniques on social media. This paper aims to describe and understand the sentiment and emotion that humans have discovered from the text of their social media posts and apply it to generate advice. This paper collected tweet information and replies on a few special points and created a dataset with text, emotion, sentiment data, etc. We used 500 tweets data set to obtain feelings and emotions in Tweets and their re-tweets, and we covered user impact scores based on various people-based measures and tweets. The machine learning algorithm plays a vital role in sentiment analysis. In this paper, a machine learning-based Naive Bayes classifier is used to perform emotion-relevant text classification like Anger, surprise, joy, fear, sadness, etc. The experimental results show that the proposed algorithm provides better accuracy compared to previous algorithms of KNN and DT classifiers.
A Novel Approach to Seamless Image Stitching using S-FREAK and RANSAC Algorithm

Image stitching is increasingly becoming popular in the fields of image processing, computer vision, virtual reality, computer graphics, human computer interaction and multimedia. Image stitching or mosaicing is a technique in which several images of overlapping domain of view are combinedtogether for a panoramic image of high resolution. Image stitching surveys depict that it is still now a puzzling problem for the construction of panoramic images. The input to a stitching algorithm is multiple, overlapping images captured from different camera views and the output is a panorama of wider field of view made by merging and stitching the individual images. Feature extraction, feature matching, homography estimation and stitching are the steps performed to make panoramic images. Traditional image stitching methods based on different feature extraction techniques require long registration time for high resolution images. In this work, a novel image stitching method based on S-FREAK is proposed by combining SIFT (Scale Invariant Feature Transform) and FREAK (Fast Retina Keypoints). The feature descriptors from one image are matched with the other to find the best closeness and only the features with best closeness are kept while the rest ones are discarded. A transformation model is estimated from these features and the image is warped correspondingly. Image stitching is a technology for solving the field of view (FOV) limitation in images.
Pelatihan Tata Kelola Webinar Bagi Pengurus dan Anggota UKK KSR PMI Unit Iain Pekalongan

Currently, technological sophistication brings new innovative ideas to educational activities. Webinars are a solution for the effective use of online learning media. Webinar governance training For administrators and members of the KSR PMI IAIN Pekalongan unit, it really needs to be delivered with an interesting method adapted to the Z generation of internet generation. This community service aims to provide assistance on webinar governance as an introductory program on How to conduct online webinars and to explore digital programs during the Covid 19 pandemic which consists of training on making registration landing pages, training on making certificates quickly and training in zoom governance. Carried out by training or training methods as well as live appearances to carry out online activities. The participants were very enthusiastic in carrying out the webinar governance training event which was shown by 40 participants or 100% of the participants were happy to take part in the management training event and the results of observations made by the service team also showed that almost all participants 87% (35 participants) were able create a registration landing page, able to create certificates and e-certificates quickly and be able to operationalize the zoom application.
Distance Learning Policy (PJJ) in the New Normal era in the Perspective of Urban Communities

The Covid-19 pandemic which was declared by the Government of Indonesia as a national disaster in March 2020 made the world of education have to adjust the teaching and learning process from face-to-face to Distance Learning (PJJ). In the implementation of PJJ, digital technology is the key to the s
Using convolutional neural networks for binary classification of x-ray images

Within this study, we made a comparison of the efficiency of several convolutional neural networks with different architectures taken from the Tensorflow open-source library. The paper analyzes the parameters of these networks using validation curves. The InceptionV3 model showed the best results for the X-ray image binary classification task. The selected convolutional network with optimal parameters obtained in this study is easy to be retrained using its own data set and applied to solve classification tasks, select and segment objects on X-ray images.
Yayasan UMP provides free laptops for students

PEKAN, 16 April 2021 – Yayasan UMP provided 70 laptops to Universiti Malaysia Pahang (UMP) students in need to ease their burden in adapting to the online learning sessions.
Ask-The-Expert: Minimizing Human Review for Big Data Analytics Through Active Learning

In this CIF project, we worked toward semi-automating knowledge discovery from anomaly detection algorithms through the use of active learning. Active learning is an area of research within machine learning that uses an in the loop to learn from large data sets that have very few annotations or labels available, and where providing such labels is expensive. In our case, the task can be defined as the identification of safety events from flight operational data. Since traditional anomaly detection algorithms cannot differentiate between operationally relevant and irrelevant statistical anomalies, Subject Matter Experts (SMEs) have a lengthy and expensive burden of investigating every example identified by the detection algorithm, classifying and labeling them as relevant or irrelevant. Active learningidentifies the unlabeled example for which a label would most improve the classifier, asks the domain expert for a label, and repeats this process until there are no more resources (time, budget) available for labeling or a minimum required performance is reached. A positive label indicates an operationally significant safety event whereas a negative label indicates otherwise. Based on these few labels we propose to build an active learning system that utilizes the SME's time in the most effective manner by iteratively asking for labels for as few informative instances as possible. Our work was proposed to be a stepping stone toward implementation and deployment of the system with user interface to be pursued by the Aviation Operations and Safety Program (AOSP) given its interest in safety monitoring and discovery of safety incidents.
LibGuides: Test Preparation Materials: History

A guide to the test preparation materials available in the OHS Library, Frederick County Public Libraries, and online.
My name, my age, my favourite colour... [blog post]

Tik Tok has taken the world by storm. It has provided millions of people with entertainment and a creative outlet during a time where a large number of people have felt isolated. In amongst this creativity and community spirit, there is a growing concern of surveillance and data-farming in the app. There are subtle ways of acquiring data (location tracking/profile information). But, what if there are more direct ways to manipulate users into giving away personal information? This article will focus on the challenges of Tik Tok that (on the surface) promote a sense of community but also coerce the user to divulge a large amount of personal data. Does the acquisition of data need to be indirect when users can provide it freely? This paper aims to explore an insidious undertone of this creative powerhouse.
Artificial Intelligence on Information Services

Artificial Intelligence as a Service (AIaaS) is the outsourcing of an external artificial intelligence (AI) company. AI as a service allows people and companies to try AI for a variety of purposes without much initial investment and little risk. The test could allow for the sampling of multiple public cloud platforms to explore different ways of machine learning. Different AI provider platforms offer a wide range of machine learning and AI styles. This diversity can best fit the organizational needs of AI because organizations need to evaluate features and price to see what works for you. Cloud AI service providers can provide the special hardware needed for other AI tasks, such as GPU-based processing of deep workloads. Buying the hardware and software needed to launch an AI cloud is expensive. Combined with labor and repair costs, as well as hardware changes for different operations, it makes AIaaS costs deter many organizations. AI cloud computing including Amazon Machine Learning, Microsoft Cognitive Services and Google Cloud Machine Learning can help potential organizations with their data. Having the opportunity to try out algorithms and the services of various providers can allow businesses to find out what works and allow measurement before committing. When something measuring is found on the scale, the resources of these major providers are available to back up your computer-assisted scale.
예비 교사와 현직 교사의 영어 교수·학습에 대한 신념

The purpose of the current study is to investigate preservice teachers’ and in-service teachers’ beliefs about English teaching and learning in terms of an ideal teaching situation and a preferred lesson plan. For the study 50 preservice teachers and 38 in-service teachers were asked to write freely their thought about an ideal English teaching and learning situation and choose their preferred lesson plan among three. The data were submitted to statistical analyses and content analysis. The overall findings were that the preservice teachers’ belief in English teaching and learning was significantly different from that of the in-service teachers, and that the preservice teachers lacked in academic knowledge related to English education and on-sight practical teaching experiences when compared with their counterparts. The teacher education researchers and practitioners are required to take into account how to construct preservice teachers’ desirable belief in how to teach English effectively based on the findings of the current study. (Chungnam National University)
The Effect of Group Work Activities to Improve Students’ Speaking Skill

This research aimed to improve students’ speaking skill for the 8 th grade students of MTs Syekh Yusuf Sungguminasa by applying group work activities (Think Pair Share, Snowball and Jigsaw) in teaching English and to find out whether Group Work Activities is more effective than the conventional method in improving students speaking skills. A quasi-experimental research method was used and a number of 40 students participated in this research. These students were divided into the Experimental Group (EG) and Control Group (CG), with each group consisted of 20 students. The instrument used for this study was speaking test and recording which were conducted as a pretest before the application of group work activities and a posttest after it. The students’ scores, as data of this research were analyzed by using SPSS 24. This research indicated significant improving of the students speaking skill by using group works activities than using conventional method. The posttest mean score: pronunciation EC (6.490) > CC (3.070), grammar EC (6.830) > CC (3.905), vocabulary EC (7.075) > CC (3.740) and fluency EC (6.670) > CC (3.915). The results of this research by using group work activities showed that the students speaking accuracy consisting of vocabulary, pronunciation and grammar and fluency was effectively improving students speaking skill than conventional method.