Reviewerly/exHarmony huggingface dataset:
Perceptions of Principals and Teachers regarding Students’ Mobile Phone use in Higher Secondary Schools of District Swabi

The present study was sought to explore the perceptions of principals and teachers regarding students' mobile phone use in higher secondary schools of District Swabi. The objectives of the study were to explore the perceptions of principals and teachers regarding the use of mobile phones. The population of the study comprises all of the Government Higher Secondary School (GHSS) Swabi, Khyber Pakhtunkhwa, Pakistan. The population of the study consisted of all of the Government Higher Secondary School (GHSS) Swabi, Khyber Pakhtunkhwa, Pakistan. The sample size comprises 100 subject specialists, 76 secondary school teachers, and 19 principals randomly selected from 19 Government Higher Secondary Schools of District Swabi. The research instrument for data collection was a closed-ended Questionnaire containing 10 items on the Likert scale. The collected data were analyzed through different statistical tools like mean, standard deviation, and chi-square. The findings of the study concluded that the majority of the respondents were against the use of mobile phones during school.
AT&T says it will accept payments in cryptocurrency

AT&T said in a statement that it will accept online payments BitPay, a service that helps companies accept payments through bitcoin.
Learning adaptive weighted response consistency correlation filters for real-time UAV tracking

Due to the high efficiency of discriminative correlation filter (DCF), it has attracted widespread attention in the field of UAV object tracking. To handle the problem of filter degradation, many trackers usually introduce temporal regularization to enhance the discriminative power of the filter. However, these temporal regularization methods only utilize the limited information between two consecutive frames, which are susceptible interference by previous corrupted information. Besides, regularization terms with predefined hyperparameters can not well adapt to the variations of the target across sequent frames, which may cause the model degradation or drift. We propose a tracker based on DCF framework to fully exploit the information hidden in the historical response map, namely adaptive weighted response consistency-based DCF tracking. Specifically, carefully selected historical response maps with fixed weight distribution are introduced in training phase to increase the robustness of the filter. Further, we present a unified loss for jointly learning the filter and the weight distribution, which can be solved by the alternate convex search method. The joint loss guarantees that reliable response maps contribute more to filter learning, leading to a more discriminative and adaptive filter for tracking the target. Extensive experiments show that the proposed method achieves state-of-the-art results on two datasets.
Peningkatan Hasil Bimbingan TIK Siswa melalui Penggunaan E-learning

The purpose of this research is to determine the increase in ICT learning outcomes through the application of E-Learning in class X MIA 1 students at SMA Negeri 1 Tambangan. The research method used is quasi experimental with a pretest-posttest control group design. The research divides the control class using conventional learning media and the experimental class using E-Learning media. The data analysis method is descriptive quantitative. The results obtained from this research is that the applied E-Learning can improve student’s learning achievement. It is evident from the pretest and posttest mean scores which increased from 67.03 to 86.09. The application of E-Learning is also more effective than the application of conventional learning, as evidenced by the normalized gain value of the experimental class of g = 0.54 is higher than the gain value of the control class of g = 0.30. Besides, the results of the posttest hypothesis test with t-test showed P (0.006) &amp;lt; ∝ (0.05) so that the research hypothesis is accepted. The conclusion obtained from this research is that the application of the E-Learning can improve the ICT learning achievement of class X MIA 1 SMA Negeri 1 Tambangan.
Deep Learning with TensorFlow Datasets

In the previous chapter, we demonstrated how to work with TFDS objects. In this chapter, we work through two end-to-end deep learning experiments with large and complex TFDS objects. The Fashion-MNIST and beans datasets are small with simple images.
A radical phenomenology of the body: subjectivity and sensations in body image and body schema

The role of sensations for body experience and body representations such as body image and body schema seems indisputable. This chapter discusses the link between sensory input, the experience of one’s own body, and body representations such as body image and body schema. That happens on the basis of Michel Henry’s radical phenomenology of the body, which unites body and subjectivity and reconsiders the role of sensory input for the experience of the body and related representations. Without supporting, but inspired by, Henry’s ontological dualism between subjective and objective body, it is argued that the traditional view that considers sensory signals as all-important for bodily experience misses out a bodily dimension crucial for subjectivity—the body’s subjective dimension, not reigned by current sensory input. Cognitive science seems willing to accept representations that are over and above sensory input but still experiential in nature. The exact status of these ‘offline’ representations is, however, unclear. If it is true that these offline representations are responsible for crucial aspects of bodily subjective life (e.g., unity, ownership, presence), then it is unclear how these representations bring this experience about. Whereas online bodily representations are based on sensory input, offline bodily representations seem to be based on bodily experience over and above sensory life. In other words, they seem to represent or mediate what they are supposed to explain—the subjective body.
20 years of physical document and product protection using digital methods

The human hand can copy all that the human hand creates", said Baron von Eichtal in 1843 when he was in charge of banknote issuing for the bank of Bavaria. Despite all the advancements in security printing and anti-counterfeiting, these words ring more true than ever. Indeed in the last thirty years, counterfeiters have greatly benefited from the globalisation of supply chains as well as from the digitization of production methods. Yet the development of digital technologies has also opened unprecedented possibilities for addressing the 3000 years old problem of counterfeiting. This presentation will review some of the counterfeit detection techniques developed in the last 20 years, including printed digital watermarks, copy detection patterns and secure QR Codes. These technologies not only open up the possibility for potentially anyone to verify authenticity with their smartphones, but they also enable the digitization of the trillions of physical documents, packaging and products that we produce every year. Real world examples from industrial applications as well as current research topics will be discussed.
HaptiColour: Haptic-assisted Digital Colouring Platform for Managing Anxiety and Increasing Mindfulness

Research suggests that mindfulness-based activities such as structured colouring are effective in reducing anxiety. Digital colouring is convenient but lacks the tactile experience of traditional media. We introduce HaptiColour, a haptic-assisted colouring platform that aims to help people manage anxiety and increase mindfulness. The platform is based on Haply, a 2-DoF grounded force feedback device, integrated with a graphical environment. We explored and implemented haptic guidance strategies and tool-tip effects that aid digital colouring experiences. We foresee the use of this platform in structured colouring practices. Initial evaluation shows that people would be interested in using a haptic-assisted colouring platform.
A Noninterference Model for Mobile OS Information Flow Control and Its Policy Verification

Mobile operating systems such as Android are facing serious security risk. First, they have a large number of users and store a large number of users’ private data, which have become major targets of network attack; second, their openness leads to high security risks; third, their coarse-grained static permission control mechanism leads to a large number of privacy leaks. Recent decentralized information flow control (DIFC) operating systems such as Asbestos, HiStar, and Flume dynamically adjust the label of each process. Asbestos contains inherent covert channels due to this implicit label adjustment. The others close these covert channels through the use of explicit label change, but this impedes communication and increases performance overhead. We present an enhanced implicit label change model (EILCM) for mobile operating systems that can close the known covert channel in these models with implicit label change and supports dynamic constraints on tags for separation of duty. We also formally analyze the reasons why EILCM can close the known covert channels and prove that abstract EILCM systems have the security property of noninterference with declassification by virtue of the model checker tool FDR. We also prove that the problem of EILCM policy verification is NP-complete and propose a backtrack-based search algorithm to solve the problem. Experiments are presented to show that the algorithm is effective.
Vehicle Speed Estimation Using Gaussian Mixture Model and Kalman Filter

Many countries use traffic enforcement camera to monitor the speed limit and capture over speed violations. The main objective of such a system is to enforce the speed limits which results in the reduction of number of accidents, fatalities, and serious injuries. Traditionally, the task is carried out manually by the enforcement agencies with the help of specialized hardware such as radar and camera. To automate the process, an efficient and robust solution is needed. Vehicle detection, tracking and speed estimation are the main tasks in an automated system which are not trivial. In this paper, we address the problem of vehicle detection, tracking, and speed estimation using a single fixed camera. A background subtraction method based on the Gaussian Mixture Model (GMM) is employed to detect vehicles because of its capability in dealing with complex backgrounds and variations in the appearance due to illumination and scale. Next, the detected vehicles are tracked in each frame by using the Kalman Filter. Finally, an estimate the speed of each vehicle is determined by using the perspective geometry model. The complete system is tested at our university campus and the results are promising.
Experimental investigation on the delamination onset and propagation in composite specimens subjected to compressive loads by using Digital Image Correlation

The continuous demand of lightweight structures characterized by high load-carrying capabilities has led to an increasing use of composite materials. However, despite the outstanding properties of this kind of materials, uncertainties still exist on their complex damage behavior. For such a reason, extensive investigation, from both an experimental and numerical perspective, is mandatory. This work aims to investigate the damage behavior of delaminated composite specimens subjected to compressive load. The strain and displacement fields are monitored by using Digital Image Correlation (DIC), in order to obtain information on the delamination propagation during the experiment. The acquired data can be used, supported by Finite element analyses, to help the understanding of such complex phenomenon.
THE ROUGH SET METHOD IN MEASURING EMPLOYEE PERFORMANCE

Performance has a very important role because performance is a form of the end result of an employee's process in completing his duties. Employees who can complete their duties properly and correctly will have high performance. Therefore Punctuality, Technical Knowledge Regarding Work, Communication between Employees, and the Ability to Manage Work are believed to be able to influence the performance of an employee. To further accelerate the measurement of performance, a method is needed to measure it. The thought set method is a solution for measuring an employee's performance in several steps, namely: Decision System, Equivalence Class, Discernibilty Matric, Reduction, and Rules. This study measures the performance of employees using the Rough Set method on employees of the Qiana Padang Wholesale Store with a sample of 10 employees, so the results of this study are based on 10 samples of employees of the Qiana Padang Store which were carried out by testing using the Rough Set application. The employees of Toko Qiana Padang showed good results as many as 4 employees and there were as many as 6 employees who had excellent performance
Enhanced Grasshopper Optimization Algorithm for Numerical Optimization

This paper presents an enhanced grasshopper optimization algorithm (EGOA) for numerical optimization and to optimize real-world optimization problems. EGOA is an improved and advanced version of its predecessor, grasshopper optimization algorithm (GOA). EGOA incorporates a novel randomization process through Gaussian walk alongside a new ranking and position modification system for better exploration and exploitation to provide a better optimal solution and enhance the diversity of the obtained solution. EGOA is rigorously tested for its performance parameters like better optimality, fast rate of convergence, lower standard deviation and better consistency. EGOA is compared alongside GOA on 23 benchmarking functions and a comparative analysis is done. The results show that the proposed EGOA outperforms the older GOA in terms of all benchmarking standards for the considered benchmark functions.
Pedagogical Mediation and Complexity. A Perspective on the Training of Economists

This research seeks to design a pedagogical strategies proposal for the economic sciences learning at a Faculty of Economics in Colombia; Methods: derived from complex thinking has three phases: resonance, bio-learning-relationality and holographic phase. These involve the following examples of pedagogical mediation: flipped classroom, gamification, socio-pedagogical cartography, virtual learning objects and Feeling methodology with the pillars of bio-pedagogy, knowledge construction, critical thinking and social transformation; the research shows the achievement of learning objectives in economics in line with the bio-pedagogical vision, using the proposed pedagogical mediation; Linking pedagogical innovations based on biopedagogy, allows improving the academic objectives proposed for the training of economists.
SISTEM INFORMASI KONTROL INDIKATOR WORKSTATION/ANDON BERBASIS ANDROID PADA PT.SCHNEIDER ELECTRIC MANUFACTURING BATAM

An Andon is a visual control that shows the status of the machine, Andon is often accompanied by an audible alarm and a sign light to remind the supervisor when there is a change in status. The problem that arises is the limited range of mark that is activated by Andon that makes support personnel or maintenance not respond quickly when urgent attention is needed. Because the control that is done directly through the manual button on andon will make it inefficient if more than one light signal indicates a problem in the active workstation and to reset it, maintenance must also disable it manually. The purpose of this research development is to use an android application on the smartphone so Visual access can cover a wider area and the information obtained becomes faster and more accurate.
Contribution of entrepreneurship to economic diversification in the Arab world

This paper highlights the contribution of entrepreneurship to economic diversification in the Arab world. Economic diversification increases sectoral output and reduces the risk of market volatility. The relationship between small and medium enterprises (SMEs) and economic diversification is drawn on previous research and literature. The paper uses international data to illustrate the contribution of SMEs to knowledge creation and productivity growth. Such analysis contributes to the development of SMEs in the Arab region. In the Arab world, the contribution of SMEs to the national economy remains inadequate to create linkages and foster growth. Governments in the region should encourage private enterprises to participate in the economy by providing greater financial, technical and managerial incentives. Across the region, public expenditure has been the main source of investment in the economy. 'SMEs' could increase productivity through knowledge sharing, technology transfer, innovation diffusion and collaboration. However, governments should create suitable business environment to encourage local firms taking greater role in the new economy.
Strategic Design of Platform Technology on the Cloud Service

Cloud is defined as an information processing system that enables flexible utilization of information and communications resources such as information and communications devices, devices and software integrated and shared through information and communications networks in response to changes in User Speed data. Especially in today's data-intensive environments, enterprises need to efficiently deploy, store, and process Bigdata. The purpose of this study is to analyze and gain insights from cloud service platform technologies. First, we define a technical analysis of cloud service platforms and analyze their characteristics. Then look at the analytics framework, reference models, and market trends for cloud services. To develop a detailed strategy, we will also look at technology trends in IaaS, PaaS, and SaaS, which are key cloud technologies. Finally, these technologies will be integrated to utilize platform technologies and explore the service market. Each IaaS, PaaS and SaaS strategy is designed from the perspective of public and private organizations.
Object in Object-oriented Ontology by Graham Haman

This article discusses the main provisions of the object-oriented ontology of Graham Harman. The four-fold structure of an object is analyzed in detail as the relationship of sensory qualities, real qualities, a sensory object and a real object, as a result of the interaction of which the fundamental ontological structures of time and space arise. Some problems arising from the basic postulates of the system, such as the lack of interaction between real objects and the indeterminacy of the &amp;quot;ego&amp;quot;, are also addressed.
A Descriptive Study of Students’ Writing Abilityin Recount Text Of The Eighth Year Students at Mts Rogojampi

The purpose of this research is intended to draw the students’ writing ability of recount text used by the English teacher in Eighth year student at MTs Rogojampi in the academic year 2017/2018. The general problem of this study is how is the students’ writing ability of recount text used by the English teacher in Eighth year student at MTs Rogojampi in the academic year 2017/2018. The primary data are taken from questionnaire and the secondary data are taken from interview. The respondents of the research are the Eighth year student at MTs Rogojampi in the academic year 2017/2018. The total numbers of respondents are 60 students in the population that uses purposive sampling. In this research, the researcher uses the questionnaire as data collecting method. There are 70,42% mean score of orientation, 76,7% mean score of series of events, 72,9% mean score of re-orientation aspect, 54,58% mean score of grammar, and 54,58 mean score of vocabulary aspects. The result of questionnaire is the Eighth year students at MTs Rogojampi in the academic year 2017/2018 are good enough in writing recount text. It is fair enough to say that the student needs more improvement from the way how they learn English, how to write a good paragraph and also knowing the category of the text, especially conducting to recount text. This research can be used as consideration in selection of writing ability, especially about recount text.
Behavioural pre-testing of COVID Tracker, Ireland’s contact-tracing app. ESRI Working Paper 687 December 2020.

Contact-tracing mobile phone apps have the potential to play a role in controlling the spread of COVID-19, but their success hinges on widespread uptake by the public. We report a study that behaviourally pre-tested COVID Tracker, Ireland’s contact-tracing app, prior to its launch with a large sample of smartphone users. The study was funded by the Department of Health and run in co-operation with the app’s developers, NearForm. Participants were randomised to receive different versions of a trial app. They responded to an online survey while downloading and using the app on their phones in real-time. The experimental manipulations focused on three broad areas: (i) the level of privacy assurance provided in the app, (ii) the goal-framing of the purpose of the app, and (iii) the structuring of the exposure notification received by users if they are recorded as a close contact. Almost one in five participants mentioned privacy concerns in relation to their likelihood of downloading the app. Including additional assurances regarding the privacy of users’ data in the app successfully lowered participants’ privacy concerns and boosted engagement. This finding fed into the final version of the app released in July 2020. We also found minor beneficial effects of restructuring the exposure notification but did not find any significant differences between two different types of goal-framing, other than a subtle effect on how the exposure notification is interpreted. Overall, our results demonstrate the value of pre-testing contact-tracing apps from a behavioural perspective to boost uptake, trust, and participation.
Minimax semi-supervised set-valued approach to multi-class classification

We study supervised and semi-supervised algorithms in the set-valued classification framework with controlled expected size. While the former methods can use only n labeled samples, the latter are able to make use of N additional unlabeled data. We obtain semi-supervised minimax rates of convergence under the α-margin assumption and a β-Hölder condition on the conditional distribution of labels. Our analysis implies that if no further assumption is made, there is no supervised method that outperforms the semi-supervised estimator proposed in this work – the best achievable rate for any supervised method is O(n−1/2), even if the margin assumption is extremely favorable; on the contrary, the developed semi-supervised estimator can achieve faster O((n/logn)−(1+α)β/(2β+d)) rate of convergence provided that sufficiently many unlabeled samples are available. We also show that under additional smoothness assumption, supervised methods are able to achieve faster rates and the unlabeled sample cannot improve the rate of convergence. Finally, a numerical study supports our theory and emphasizes the relevance of the assumptions we required from an empirical perspective.
Life-long love of reading

Learning to read is probably the single most important academic skill we acquire through formal education, affecting as it does, every other area of learning; from reading instructions in maths, to drawing upon inspiration from stories for art.