Reviewerly/exHarmony huggingface dataset:
A Demonstration that Correcting for Completeness and Reliability Is Critical for Robust Occurrence Rates

A measurement of planetary occurrence rates based on a planet catalog should be robust against details of how initial detections were classified as planets or false positives. This is accomplished by supplying the catalog’s rate of missed planets (completeness) and rate of non-planets incorrectly called planets (reliability). The final Kepler data release (DR25) includes products that can be used with the DR25 planet candidate catalog to correct for completeness and reliability in occurrence rate estimates. This is made possible by the Kepler Robovetter, which algorithmically and uniformly selects planets based on a variety of metrics and thresholds. Completeness, reliability, and occurrence rates potentially depend on these Robovetter thresholds. We study the impact of varying these vetting thresholds using the techniques of Bryson et al. 2019 (arXiv:1906.03575). We explore sets of thresholds that result in more or fewer planets (trading off completeness for reliability), as well as thresholds tuned to pass DR25 false positives identified as possible planets by the Kepler False Positive Working Group. We find that when correcting only for completeness, and not reliability, the resulting occurrence rates have a strong dependence on these threshold sets. For example, the value of SAG13 eta-Earth varies by over a factor of 4 when not corrected for reliability. However, when correcting for both completeness and reliability, occurrence rates using our threshold sets are statistically indistinguishable, with differences being well inside 1-sigma error bars. We present occurrence rates integrated over several period-radius ranges. For example, SAG13 eta-Earth is consistent with 0.127 (+0.094)(-0.054) (from Bryson et al. 2019) for all the Robovetter threshold sets. This result emphasizes the importance of correcting occurrence rates for both completeness and reliability. This suggests that inconsistent completeness and reliability correction may be a significant contributor to the large variation of occurrence rates in recent literature. We plan to make the Robovetter results for our threshold sets available, and encourage the community to use them to examine whether other occurrence rate methods yield similarly robust results.
Trust, Blockchain-based Technologies, Public Sector, and the Social Good

Many public institutions, government bodies, municipalities are experimenting with blockchain based systems, decentralized ledgers, smart contracts to deliver new innovative services to citizens, or improve the speed, efficiency, accuracy of existing ones. This short policy analysis looks at the potential mismatch between usually high-trust public institutions, and trust-minimizing technological infrastructures.We warn that, in general, we should avoid replacing a high-trust environment with a trust-minimizing technology. Pre-existing trust is very valuable, and no new technology should endanger trust which is extremely hard to build but very easy to destroy. Of course, not all institutions enjoy the trust of the citizenry. In low-trust environments the implementation of trust minimizing technologies need to consider the relative benefits and harms of the different approaches to dealing with low-trust environments. One can decide to implement a technology that is able to operate in such low-trust settings. The alternative to this is to try to implement technologies and policies that foster the emergence of trust. What is the preferable way forward: replacing distrusted public entities with trust-minimizing technologies, or improving their trustworthiness? Should we implement a trust-minimizing architecture, or a trust-maximizing one? Our institutions may be imperfect, and often produce arbitrary outcomes; sometimes they are downright oppressive. But at least there are clear lines of social, public, institutional, political and economic accountability and oversight. Such mechanisms of trust are yet to mature with regard to blockchain technologies. Unless these technologies can be brought into the fold, they remain largely unaccountable, thus fundamentally untrustworthy. And even if they are, we still don’t know which is preferable: a polycentric system of power of checks and balances, which involves democratic oversight, or an ideally decentralized and disintermediated one, where power concentration is prevented?This should be a warning to well-intentioned public servants, institutions and private actors who are looking at implementing blockchain systems in order to better their domain or be seen as innovative, or simply because they fear missing out on a technology development sold to them as a revolution. It may be worth their while not to rush. It is OK to be slow and cautious. Disruptive digital innovation that targets trust should be treated with extreme caution.
Family-Based Sleep Technologies: Opportunities and Challenges

Sleep is a critical component of overall wellness, and pervasive and ubiquitous computing technologies have shown promise for allowing individuals to track and manage their sleep quality. However, sleep quality is also affected by interpersonal factors, especially for families with young children. In this study, we adopted a family informatics approach to understand opportunities and challenges for sleep technologies at the family level. We conducted home-based interviews with 10 families with young children, asking them about their current practices, values, and perceived role for technology. We describe challenges across three phases: bedtime, nighttime, and waking. We show that family-based sleep technologies may have the greatest impact by supporting family activities and rituals, encouraging children's independence, and providing comfort.
Impact of Class Imbalance on Convolutional Neural Network Training in Multi-class Problems

Image classification is the process of assigning an image one or multiple tags that describe its content. To perform the classification, a model must be designed for learning the labels to be assigned to a given image. The assignment is made through a learning process that uses a set of previously labeled training images, which must be large enough to guarantee efficient training. Many approaches have been researched to find optimal solutions to classification problems, however, databases with large amounts of images and the increased processing power of GPUs have made convolutional neural networks (CNNs) the best choice, as they outperform traditional algorithms. This paper presents a systematic analysis aimed at understanding how the issue of class inequality affects the efficiency of a convolutionary neural network trained for a task of image classification, and presents a technique for correcting the overtraining and that the network generalization.
LibGuides: Library / Open Access Database Tools and Tips: Database Tools

Most databases have common elements which help streamline your research and save time. This How-To guide shares tools and tips for using the library databases at ACC.
How to Check Lottery Sambad Result Online: Concise Details

Sambad is an extensive playing of lottery in Western Bengal. It has a draw three times in a day in Nagaland. One lottery result can change someone’s ...
ВЕРТИКАЛЬНАЯ МИНЕРАЛЬНАЯ ЗОНАЛЬНОСТЬ КОЛЧЕДАННОГО МЕСТОРОЖДЕНИЯ САН-ФЕРНАНДО. КУБА

From ten to fifteen percent of the global supply of copper, zinc and lead, as well as a significant amount of silver, gold, cadmium, selenium, tin, bismuth and barium are mined from massive sulphide deposits. Massive sulphide deposits of copper and zinc containing minor lead, gold and silver are located in the region of Central Cuba. These deposits are localised in sedimentary-volcanogenic rocks of the Lower Cretaceous Los Pasos Formation, which are considered the oldest manifestations of magmatism in the island arc of the Caribbean Sea. These deposits include massive sulphide ores and are referred to as volcanogenic massive sulphides (VMS), common among the volcanic deposits of the Greater Antilles. The San Fernando deposit is the most important industrial site featuring stratiform deposits of massive, breccia and disseminated sulphide ores and chalcopyrite-pyrite stockworks localised in the covers and tuffs of rhyolites and dacites. Lenticular ore bodies lie on three levels with an en-echelon overlapping. This article set out to indicate the vertical and lateral mineralogical-geochemical zonality of the San Fernando deposit using 1075 ICP MS analyses of ordinary geochemical samples, a core documentation of 65 exploratory wells and ore microscopy of 146 polished sections. Data for the study was obtained during 2009—2012 exploration work. The main ore bodies of the deposit are lenticular. The relative abundance of chalcopyrite, sphalerite, galena, pyrite, and pyrrhotite was estimated across ore-bearing levels using ore polished sections, which was compared with Cu, Zn, Pb, Cd, Au, and Ag concentrations. An analysis of the data was carried using the QGIS geographic information system. The distribution of copper and zinc-copper ores at the upper level, as well as pyrite ores at the lower level of the deposit, was established. The established geochemical regularities were generally confirmed by the prevalence of the main ore minerals — chalcopyrite and sphalerite. The relatively independent distribution of gold and silver in the Cu and Zn concentration contours indicates possible superimposed processes of noble metal concentration. According to the conducted mineralogical and chemical analysis, the highest  concentrations of useful components were determined at two depth levels of 60—85 and 125—160 m within the limits of the most productive north-eastern and south-western flanks of the deposit.
DYNAMICALLY MOVING OBJECT DETECTION BY USING YOLOALGORITHM

Classification of different objects in an image has become very difficult task few years ago. Very importantlyfinding the important objects inside the image by drawing the rectangular boundary boxes to that object. With substantialincrease in the computer vision field that uses Deep Learning based Convolutional Neural Network in which the image isassigned a label based on the contents in the image that is pre-trained by using a computer system. When it comes to speedof the system identifying the objects inside an image is still in the intermediate stage. To increase the speed and accuracy ofdetecting the objects an Machine Learning based YOLO algorithm that uses Python, OpenCV and Deep Learningtechniques. By using this algorithm vehicle speed, traffic signs, logos inside an image, front and rear views of the vehicle.The system can track the multiple moving objects in real-time environment. In this algorithm, a localisation technique isapplied in which the captured video is divided into multiple frames then localisation is applied to identify the object insidethe frames that are divided by using localisation technique. The main objective of the proposed system is to improveaccuracy and performance of the object detection using single stage method in the different moving objects inside the videoframes
Blockchain Drivers and Challenges in Supply Chain Management: Multiple Case Studies in Emerging Economies

Currently, Blockchain Technology (BT) is still in the early stages of development. However, this technology has been used in some governments, organizations, companies, and research institutions. The novelty of BT led to the needs of an organization to understand what drives them to implement it. Besides understanding the drivers of implementing BT, it is also equally necessary to understand the challenges of BT implementation in a particular organization. However, some research only analyzed in developed countries, which cannot be generalized worldwide. Therefore, to expand this research, researching emerging countries will be beneficial to know which drivers and challenges that influence the implementation of BT in SCM context.This research has aim to identify the drivers and challenges of implementing Blockchain in two emerging countries: Indonesia and China. Once it is successfully identified, a framework will be proposed to address them. Several research questions will be addressed.The methodology of this project was divided into three phases: Preliminary, Data collection, and Analysis. In the first phase, a systematic literature review is adopted as the method of literature review to establish the theoretical framework. In the second phase, data collection methods, interviewees, and interview documents are stated. The data of multiple cases study in this project are collected from semi-structured interviews of six companies. The final phase is to conduct within-group analysis and cross-case analysis, which can help readers understand similarities and differences between different cases.Based on the theoretical framework and the data collected from six interviewed companies, this project established a new theoretical framework, which is composed of the drivers and challenges companies faced when implementing BT in the SC field, and connected it with supply chain flow. Data integration and information sharing in information flow is the most powerful driver that Indonesia and China face in the implementation of BT in SC. The Cooperation and Information Sharing from information flow and High Investment and ROI Uncertainty from cash flow are the most apparent challenges facing both countries.
Epidemiological study on malarial infection in district Pishin Balochistan, Pakistan

Malaria is one of the serious health issues throughout the world, caused by vector borne diseases of the genus Plasmodium. The word malaria comes from the Italian words ‘mala’ and ‘aria’ means bad air. Five species of Plasmodium parasites, P. vivax, P. falciparum, P. ovale, P. malariae and fifth specie P. knowlesi have been reported in some countries. Malarial parasite completes their life cycle in two hosts, one is female anopheles’ mosquitos (insect vector) and 2nd is human beings. Malaria is reported from June to September and becomes more common in rural areas as compared to urban areas in Pakistan. A total no of about 3031 malarial blood slides were carefully arranged from both genders’ male and female population from 13 diverse villages, their BHUS laboratories and the main populated Pishin city. In month wise incidence of concern disease, Plasmodium vivax appeared with a peak in July (41.6%) and was not present in the month of January (0%). Gender wise malarial status revealed to be higher in Males (60.4%) and lowest in Females (46.5%).
The Students' Perception on The Use of Hello English

The researcher discovered that in UPB if there are students non English department that interest to learning English, but they limited by time and economic so that they choose to use Hello English application. So that the researcher interest to conduct Hello English application to find out whether the application can be effectively used for learning. This research aims at knowing (1) what are student’s perception on the use of Hello English? (2) what are the possible impacts of Hello English towards the student’s vocabulary in learning general English?.The researcher used descriptive qualitative research design. The technique of collecting data was interview. The population of this research was the students from 2019 generations that took from groups; 53, 99, and 111 in UPB of UIN Antasari Banjarmasin. The participants of this research were fifteen for interview and questionnaire for supporting data.The result of the research showed that student’s perceptions on the use of Hello English has advantages amount 80% and disadvantages amount 20%. Hello English also some impacts, that are easy to learn English vocabulary through game in Hello English, Hello English helps students to memorize the vocabulary, Hello English application makes them increasing vocabulary, Hello English helps students to know meaning of vocabulary, Hello English helps students to pronounce English correctly, Hello English makes motivation student to learn more English, and learn creatively in acquire new vocabularies.
DEVELOPING STUDENTS’ READING COMPREHENSION ON DESCRIPTIVE TEXT BY USING COMIC BOOKS (Classroom Action Research at the Second Grade of MTS Al-Rahmah Lebakwangi Serang)

Mushlih Adam Maulana. 122301324. Developing students reading comprehension of descriptive text by using comic books” (A Classroom Action Research at the second Gradeof MTSAl-Rahmah Lebakwangi). This final project was about the use of comic books as a strategy to develop students’ reading skill of descriptive text. The Aim of this research is to develop students’ reading skill of descriptive text by using comic books strategy at the second grade of MTS Al-Rahmah Lebakwangi. In this study, the writer used classroom action research design. The research was done through in two cycles. Each cycle consisted ofplanning, action, observation, and reflection. Technique of collecting the data used test, observation and interview. The researcher analyzed the data both qualitatively and quantitatively. The researcher gave test cycle 1 and test cycle 2 especially on descriptive text to measure students’ readingskill . The result of the test showed that: the mean score of the test cycle 1 is is 64,6 and in the test cycle 2 is 84,53. It showed that there were improvements of the students’ readingskill. It meant that there was significant difference in the students’ reading achievement between the cycle 1 and cycle 2. Thus, it was concluded that comic books strategy was effective to develop students’ reading skill on descriptive text. Key Words: reading ability, Descriptive text, comic books strategy.
Parallel A* search on a multi-core CPU

Multi-core central processing units (CPU) and the graphics processing unit (GPU) have become popular parallel computing platforms in recent years [1]. The GPU platform is commonly adopted in the research community as it has been to be superior to the traditional CPU. Straightforward implementations of Parallel algorithms on a GPU can easily achieve a speedup of ten times or more over the sequential algorithms. However, achieving significant speedup on a multi-core CPU (over the sequential algorithm) requires intelligently designed and well-optimized algorithms [3]. This paper discusses a parallel implementation of A* search which achieved 6.67x Speedup with a search space of 106 nodes, 3.14x speedup with 107 nodes, and 137.67x speedup with 108 nodes when run on the eight-core, 3.0 GHz Intel Core i7 processor. This paper also analyses different work partitioning strategies and how the performance of the parallel A* search algorithm scales.
A STUDY OF SOCIAL SKILLS AMONG THE STUDENTS AT ELEMENTARY LEVEL

The study explored the developed social skills among students at elementary level. A total of 772 Students were selected using multi stage cluster sampling in the district of Sialkot. Explored social skills included accepting criticism, showing respect, solving problems, accepting rights & responsibilities and tolerance of individual differences. A scale consisting of sixty nine items was developed and standardized through factor analysis. The instrument was checked and ensured for reliability measures using Cronbach’s Alpha (r = .75, p < .05) as well. Five factors were identified through exploratory factor analysis using principal component matrix measuring students’ level of social skills studying at elementary level. Results found students possessing the social skill of tolerance of individual difference being highest among all other types. Significant differences of social skills based on students’ gender were also observed. The study presents implications for policy makers and school authorities.
LibGuides: Multimedia Instructional Design: Home

This guide is for the NCU certificate Multimedia Instructional Design. It contains resources available in the NCU Library.
Identifying specialisation domains beyond taxonomies: mapping scientific and technological domains of specialisation via semantic analyses

This chapter focuses on new methods that can be used at the interface of science and policy for the identification of the localised domains of specialisation in science and technology. The authors explore semantic methodologies which, by analysing the textual content of science and innovation-related documents (such as policy and project descriptions, scientific publications, patents, clinical trials, and so on) go beyond classifications, allowing emergent topics and domains to be identified, as well as mapping and benchmarking the local capabilities in specific domains of interest.
LibGuides: Resources for Online Teaching and Learning: Agricultural & Food Sciences: Online Courses

This guide contains online teaching and learning materials for Agricultural and Food Sciences majors.
UMC Library: Online Learning: Campus Information

A research guide aimed at supporting online learning at the University of Minnesota, Crookston.
Software-related Inventions

On 29 November 1972, Atari Inc., a newly incorporated Californian firm, announced therelease of its first video arcade game: PONG.1 The game required the player to control a simulated table tennis paddle, moving it vertically across the screen to intercept and return a ball toan opponent (either one that is computer-controlled or another person). Although simplistic bytoday’s standards, it was a roaring success, arguably laying the foundations for a multibilliondollar gaming industry and catapulting Atari to massive (albeit shortlived) riches.2As a technical creation, the PONG arcade cabinet was fascinating. The soul of the machinewas held in the connection and arrangement of 66 chips of varying types.3 The components ofits experience – graphics, sounds and gameplay – were all a product of hardware: an exampleof transistor–transistor logic reliant upon the components’ relative configuration and thepower supplied to them. There was no software. No writing of code. No instructions issued tothe components other than by the machine’s physical controls. That an identical result can nowbe replicated in software – that a suitably programmed, off the shelf computer can emulate thisfeat of wiring and solder – is testament to the boundaries that computer programs can cross.It also highlights the core of the problem with the law’s understanding and treatment of thissubject matter within the confines of intellectual property: software possesses a unique duality.It is, as Nack explains, ‘both the text description of a machine and the “machine” itself . . .no special physical device is needed to implement the algorithm – a standard computer willsuffice’.4
Object Detection Using Synthetic Training Data

Annotating data for machine learning purposes can be very inefficient and time-consuming. In this paper we introduce a pipeline for generating a 3d scene from a simple image. We discuss and develop the first step which includes a 3d network being able to recognise any particular object. We focus on how synthetic data can be used to make the annotating process simpler. We use generated synthetic images and train two different networks (YOLO and DOPE) and study their performances in order to learn how to create better training data. Finally, we conclude that domain randomization is very useful for attaining good results and discuss the diculties when studying training data.