Reviewerly/exHarmony huggingface dataset:
Fog detection application in basin

The Toushe Basin in central Taiwan is a local tourist attraction. Because the local dense fog often traps tourists in it, the main research purpose of this paper is to solve the problem of dense fog detection. Because the edge characteristics of fog images will disappear with the increase of fog concentration, analysis The proportion of the image that the edge occupies is used as the basis for fog concentration. In addition, the characteristic that the chroma of the image decreases as the fog concentration increases is used to convert the image to histogram, and the fog concentration is determined by analyzing the histogram of the image. In order to be more in line with the local fog in the Toshe Basin, the fog film data collection used in this paper is all taken on-site. The two fog concentration methods proposed in this paper are not only effective for analyzing the local area of the Toshe Basin. In addition to the fog concentration, it can also be used in places where various fogs are often generated after the threshold is adjusted.
Remote Sensing and Integrated Geophysical Investigations of Unstable Sections of Ibadan-Iwo-Osogbo Highway, Southwestern Nigeria

High records of road accidents due to bad roads and failure of other engineering structures globally have necessitated this study. Geophysical investigation was carried out on six failed sections and two stable ones along the Ibadan-Iwo-Osogbo highway to examine the geological factors responsible for the highway failure in the area. A Landsat ETM+ (Enhanced Thematic Mapper Plus) imagery of the study area and its environs was acquired and processed for lineament analyses. Magnetic and Very Low Frequency Electromagnetic (VLF-EM) measurements were taken at a 5 m interval along each traverse established parallel to road pavements. The electrical resistivity method involving Schlumberger Vertical Electrical Sounding (VES) and 2-D imaging using the dipole–dipole array were utilized. Lineaments were identified across failed localities. Lateral magnetic variations in the near-surface, geologic materials characterized the study area. The generated 2-D VLF-EM models showed conductive zones corresponding to the fractured zones or conductive clay materials within the basement rocks. Subgrade soils below the highway pavement along the failed sections are typical of incompetent clayey and sandy clay/clayey sand formation with resistivity values between 20 and 475 Ωm, while subgrade soils beneath the stable sections have moderate to high resistivity values of 196–616 Ωm. The 2-D subsurface resistivity structures across the failed sections identified low resistivity, water absorbing clay, and lithological contacts. Water absorbing clay-enriched subgrade soils, identified in near-surface linear features, are major geologic factors, along with a poor drainage network, causing the highway failure. Remote sensing and geophysical investigations of highways should be carried out before construction to effectively complement routine geotechnical studies.
Helsinn v. Teva: Lingering Ambiguity after the U.S. Supreme Court Holds the AIA Did Not Alter the On-Sale Bar to Patentability

The American Innovation Act of 2011 (AIA) retained §102 of the pre-AIA Patent Act’s “in public use” and “on-sale” bars to patentability, but introduced an additional “or otherwise available to the public” category of prior art. Federal Circuit precedent pre-dating the AIA has held that, as a general matter, a sale or offer for sale can create an on-sale bar to patentability even if the sale or offer for sale is “secret” and does not render the invention available to the public. Some believed that the AIA’s introduction of the phrase “or otherwise available to the public” altered the meaning of “on sale,” introducing a requirement that a sale or offer for sale render an invention “available to the public” in order to create a statutory bar to patentability. In other words, under this interpretation a “secret” offer for sale would no longer constitute an on-sale statutory bar. In January, 2019, the Supreme Court addressed this contention in Helsinn v. Teva, and essentially held that the AIA had not changed the meaning of “on sale” for purposes of §102. This article provides a historical overview of the pre-AIA on-sale bar, considers the argument that in enacting the AIA Congress intended to do away with non-public prior art, reviews Helsinn, including the decisions below and amicus curiae briefs filed with the Supreme Court in connection with the case, and concludes with a discussion of lingering questions with respect to the judicial interpretation of the on-sale and public use bars.
Research and Implementation of Web-based Integrate Network Service Management System

This paper introduces a web-based integrate network service management system, which combines web technology and network management technology to create an organic structural model. It brings together browser/server setup structure, modularization model, PHP and ASP to realize the purpose of network services management for users integrating network disposal management, user services management, MIS business management.
KFC: A clusterwise supervised learning procedure based on the aggregation of distances

Nowadays, many machine learning procedures are available on the shelve and may be used easily to calibrate predictive models on supervised data. However, when the input data consists of more than one unknown cluster, linked to different underlying predictive models, fitting a model is a more challenging task. We propose, in this paper, a three-step procedure to automatically solve this problem. The first step aims at catching the clustering structure of the input data, which may be characterized by several statistical distributions. For each partition, the second step fits a specific predictive model based on the data in each cluster. The overall model is computed by a consensual aggregation of the models corresponding to the different partitions. A comparison of the performances on different simulated and real data assesses the excellent performance of our method in a large variety of prediction problems.
Disease Mapping of Leprosy in Maluku Province, 2019 using Hierarchical Bayes

Abstract Leprosy is a chronic disease caused by Mycobacterium.lepreae that affects the nerves of the extremities, skin, nasal mucosa, and upper respiratory tract. As of today, some countries include Indonesia facing difficulties to fight leprosy. The health ministry of Indonesia noted that the majority of leprosy cases occurred in the eastern region, like Maluku Province. Therefore disease mapping is needed to develop a map of leprosy so that the handling of this disease could operate optimally, especially in Maluku. One of the disease mapping techniques is Hierarchical Bayes (HB), which involves a measure of uncertainty compared to other methods such as Standardized Mortality Ratio (SMR). The results showed that the relative risk of leprosy in Maluku was almost the same in each region. It indicates that the disease is prevalent in Maluku, with the highest value in Ambon City and the lowest value in the Aru Islands.
Soccer game optimization based forgery detection of digital images

Copy move tampering (CMT) is commonly applied for forging digital images employing user-friendly image processing tools. Interest-point (IP) based forgery detection methods are very popular as they involve a comparatively lower computational burden than those of block-based methods. The IPs in existing methods may not spread over the entire region of the image and concentrate on regions with high gradients. If the tampering region contains low gradients, then that region has very sparse or no IPs, thereby making the algorithm to fail in detecting the forgery. This paper attempts to spread a minimum number of IPs over all regions of the image and evaluate scale-invariant features transform (SIFT) descriptors, and employ soccer game optimization (SGO), a metaheuristic algorithm inspired from the intelligent behaviour of soccer game players, for transforming the feature space into cluster space. The paper studies the performance of the suggested method on 500 digital images and presents the results.
تعليم اللغة العربية للطلاب الكوريين بواسطة طريقة التعلم المقلوب

This research aims to study the effectiveness of the flipped learning method in teaching Arabic to Korean students. The term ''flipped learning'' can be translated in a variety of ways, and it refers to overturning the traditional form of class, which used to take lectures at school and do homework at home. Before students come to class, they watch the lecture video provided by the teacher in advance and study, and during the actual class time, they do the homework they did at home or group activites with the teacher and colleagues, so that it enables more interesting and effective teaching and learning. From this standpoint, this research aims to shed light on the concept of the flipped learning, its techniques, features and to present the flipped learning model for teaching Arabic to Korean students in order to improve the four language skills and motivate them to study more effectively. In this research, Arabic lessons were conducted on a pilot basis using the flip-learning method, and it became clear that flip-learning lessons gave learners a positive change in their attitude toward Arabic subjects, teachers, and fellow students through a survey of students'' perceptions after class. And It was also confirmed that the motivation for learning has also changed very positively.
Development of teachers’ professional skills in education for sustainable development

The article considers the skills and features of the personal development of a teacher in education for sustainable development (ESD). It contemplates over the influence of age differences on the formation of the professional and communicative culture of a specialist in higher education. Moreover, it describes the necessary conditions for the professional formation of the professional and communicative culture of a teacher in the development and promotion of her or him as a professional that is capable of raise the environmental awareness in students and help them to nourish their sustainable citizenship. In addition, it discusses the role of teacher training in education for sustainable development and stresses the importance of reorienting teacher training to take sustainability into account in the context of education policy and the implementation of the Sustainable Development Goals (SDGs).
Discussion on the Application of Computer Science and Technology in Computer Education

Computer science and technology have developed rapidly and have gradually become a new technology for development and innovation in various fields. In addition to promoting the process of education and teaching reform, it can also promote the development of school management methods and management work models. Innovation. The computer science and technology application in university education management is essentially to promote the construction of education information management, use computer science and technology to reform university education management methods, introduce Internet and other technologies to build education management platforms, and realize the innovation of university education management models. This article is mainly aimed at the current situation of college education in China, with the purpose of promoting the development of overall education in colleges, exploring the effective application of new computer technology in college education management, and further promoting the level of college digital education management, in order to promote college education Information management process.
Research on Online Platform of Multimedia Teaching Based on Network Engineering

Abstract With the rapid development of the Internet, the business models of all walks of life have changed a lot, and the application of multimedia technology and network technology has become more and more extensive. In the current educational environment, the traditional one-to-one teaching model no longer exists. Multimedia technology and network technology have been widely used in the teaching process. It has established a new teaching environment for distance education institutions, making the online teaching platform more convenient and realizing more possibilities.
Investigation of Mobile Machine Learning Models to Preserve the Effectiveness of User Privacy

Machine Learning (ML) has become one of the dominant technologies in the research world. It is being applied without exception in every field where automation and future predictions are required such as cyber security, computer vision, data science, search engines and various other disciplines. The application of ML in search engines creates a high risk of breaching user's privacy because this involves using data gathered from user's browsing history, purchase transactions, searching videos and queries. The user's information gathered from the search engine queries stored in computers, mobiles, other handheld devices is privately uploaded to a centralised cloud location and is then utilised in designing various ML models. As most ML models use a trained model that requires large datasets, user data gathered this way plays an important role in the development of the ML models. This however creates a significant privacy issue for individuals who may not want to reveal their personal information for ML training yet, prevention of this is beyond their access and control. In this article, we focus on the use of ML in mobile devices and address privacy concerns that can be raised by practising ML in mobile devices. The primary area of study in this research is the comparison of ML on mobile devices with ML on the cloud and figuring out its feasibility of becoming an essential ML for preserving user's privacy. Sequentially, this study first explores the need for using the ML algorithm to address privacy issues. Next, a pre-chosen ML algorithm will be tested on mobile devices and cloud to get the comparison outcome that justifies the adoption of privacy-preserving ML model on mobile devices to preserve the user's privacy.
Digital Humanities: Prototype Development for Balinese Script

In Indonesia there are more than 600 ethnic groups and 719 mother-tongue languages spoken. A significant 13 Indonesian mother-tongue languages have vanished and been forgotten as they are no longer used for daily communication. When a language is forgotten, not only is the structural aspect of the language lost, which becomes the main focus of the linguistic domain, but also the cultural and historical knowledge that is attached to the language. The Balinese language is a mother-tongue spoken on the islands of Bali and Lombok, and the Balinese script (Aksara Bali) is a traditional script that is used to write the Balinese language in the form of Balinese short stories, history (itihasa), proverbs, poetry, music, and spells (mantra) on the top of palm leaves (lontar). Recently, fewer members of the young generation of Balinese are able to speak this language due to its complexity and the widespread use of the national language (Bahasa Indonesia) in all levels of formal education. This study aims to preserve, protect, and continue the use of Balinese language and script by adopting modern technology that can be utilized by the younger Balinese generation. In this study, a physical non-QWERTY keyboard specifically for Balinese script has been designed, developed, and tested to work for multiple devices (e.g., computer, tablet, and smartphone), diverse operating systems (e.g., Windows, macOS, iOS, and Android), and various applications (e.g., Word processor, instant messenger, and social media applications). Through consultation with professors from Udayana University with expertise in Balinese language and script, a total of 89 out of 185 Balinese scripts are included in our IT artefact that can be utilized for daily use.
In the Footsteps of Pierre Duhem: How a Modern Theory of Value Relates to XIX Century Physics

Having in the last 40 years focused on a function generated from a theory of morphogenesis called Elementary Catastrophe Theory (ECT) [], the Swallowtail, to show its fitting the most respected landmark criteria of Utility or Value in Economics I felt the need to explain the resolution of the controversy surrounding the shape of this function via a polynomial solution against the trend of mainstream literature []. A little noticed theorem dating back to 1963 by Rene Thom, the author of ECT [], set the ground for the development of ECT while linking it to the thermodynamic Potentials (Entropy and Internal Energy) as the XIX century ended up characterizing them with an exclusive feature: Differentiability []. The importance of the synthesis attempted by P. Duhem comes from not assuming any atomism without precluding it while seeking a unified field theory between gravitational, electrical, magnetic and chemical theories based on Newton law as reinforced with Coulomb law for electrical charges []. One of my basic finding was the negativity of the Schwarz’ derivative the highest order (the third) differential invariant coming from the heart of Pratt’s paper on risk in Economics [] as a characteristic displacing concavity. My result so far has been that only for a polynomial representation we have a theory of self-observation fitting uniquely with the procedure of Stimulus-Response known since 150 years under the title of Psycho-Physics and opening up vistas to the world of Linguistics [].
Search for Falsifications in Copies of Business Documents

The present article is concerned with methods of comparison of scanned copies of business documents. Such a problem arises when comparing two copies of business documents signed by two parties to detect possible changes made by one of the parties. This problem is relevant, for example, in the banking sector when concluding contracts in paper form. It considers the partial matching method for the flexible form that allows modifying text attributes and inadvertent modifications of common words. It proposes the method of comparison of two scanned images based on recognition and analyses of N-grams words sequences. The proposed method has been tested on its private data set. The proposed method has demonstrated high quality and reliability of searching for differences in two copies of the same Agreement document.
Forecasting the Number of Prisoners in Nganjuk With Integer-Valued Pth-Order Autoregressive (INAR(P))

Abstract The most used time series model is the time series model which assumes the variables being tested are continuous in a discrete time period and produces continuous values. Whereas in many applications, such as number of monthly accidents, number of doctor visits per year a person makes, etc., needed a discrete time series model to handle discrete variables and produce discrete values as well. Time series model that handles count or non-negative integer data is the Integer-valued Autoregressive model with the pth-order or INAR(p). INAR(p) is the counterpart of AR(p) model for integer data. To get integer results, this model uses binomial thinning operator which implements probabilistic operations with discrete distribution that are suitable to model count data such as Poisson and Binomial, also use median forecasting method. Model parameters will be estimated using the Yule-Walker method. In this research, INAR(p) time series model will be applied to number of prisoners in Nganjuk from April 2013 until July 2016 to help tackle overcapacity problems in prisons that led to many negative impacts. Through model specification, the best model for forecast the case is INAR(2). In this data, based on the measure of AIC, BIC, and AICc, the INAR(2) model achieved better performance than its AR(2) counterpart.
Decision support system through automatic algorithms and electronic request in diagnosis of anaemia for primary care patients

An appropriate management of anaemia laboratory tests is crucial for a correct diagnosis and treatment. A non-sequential "shotgun" approach (where every anaemia related test is ordered) causes workload and cost increases and could be potentially harmful. We have implemented a Decision Support System through our laboratory information system (LIMS) based on reflexive algorithms and automatic generation of interpretative reports specifically in diagnosis of anaemia for primary care patients.When a request contained an "Anaemia Suspicion Study" profile, more than twenty automatic reflexive rules were activated in our LIMS based upon laboratory results. These rules normally involved the addition of reflexive tests. A final report was automatically generated for each interpretation which was always reviewed for their validity by two staff pathologists. We measured the impact of this system in the ordering of most common anaemia related tests and if a proper treatment was established based on the interpretive report.From all the studies performed, only 12% were positive being "iron deficiency" and "anaemia of chronic disease" the most frequent causes, 62% and 17%, respectively. Proper treatment was established in 88% of these anaemic patients. Total iron, transferrin, ferritin, folate and vitamin B12 demand decreased substantially after implementation representing a cost reduction of 40% only for these five tests.Our system has easily improved patient outcomes, advising on individual clinical cases. We have also noticeably reduced the number of over-requested tests and laboratory costs.
Tunnel image stitching based on geometry and features

Abstract In the fast tunnel detection of multi-camera, a disease distributed in multiple images is prone to be misidentified as multiple diseases, which affects the evaluation of the status of the tunnel. This paper proposes a high-precision stitching method driven by data and scene based on multi-camera sequence images. Firstly, geometric rough calculation is performed to generate the theoretical stitching mode using the geometric positional relationship between the cameras in the scene and the image relationship is renewed after theoretical stitching. Secondly, feature points are extracted and matched for adjacent overlapping images by SURF algorithm. Therefore, pixel-level data registration is performed to achieve the image stitching. Finally, an integrated stitching mode is proposed based on the theoretical stitching and pixel-level data registration, which utilizes the stitched sequence images with high physical resolution to extract cross-section information. Practical results show that the method can achieve image stitching of the tunnels with high accuracy and good reliability.
A Machine Learning Framework for Prediction Interval based Technique for Short-Term Solar Energy Forecast

The stochastic nature of photovoltaic (PV) power generation can have significant impacts on the power grid stability and reliability. Hence, it is essential to have an accurate forecasting of the PV power generation. In this paper, a new machine learning (ML) framework is presented for short-term solar energy forecast based on prediction interval (PI) technique. Simulation results conducted show how PI is more reliable and accurate as compared to deterministic methods using evaluation metrics.