Reviewerly/exHarmony huggingface dataset:
Active Covering

We analyze the problem of active covering, where the learner is given anunlabeled dataset and can sequentially label query examples. The objective isto label query all of the positive examples in the fewest number of total labelqueries. We show under standard non-parametric assumptions that a classicalsupport estimator can be repurposed as an offline algorithm attaining an excessquery cost of $\widetilde{\Theta}(n^{D/(D+1)})$ compared to the optimallearner, where $n$ is the number of datapoints and $D$ is the dimension. Wethen provide a simple active learning method that attains an improved excessquery cost of $\widetilde{O}(n^{(D-1)/D})$. Furthermore, the proposedalgorithms only require access to the positive labeled examples, which incertain settings provides additional computational and privacy benefits.Finally, we show that the active learning method consistently outperformsoffline methods as well as a variety of baselines on a wide range of benchmarkimage-based datasets.
Similarity Check Result Implementation of Gabor Filter for Carassius Auratus’s Identification

Abstract— Carassius auratus (goldfish) is a freshwater ornamental fish that is widely kept in both ponds and swimming pools. This fish has various types, colors, and shapes. Several species have similar anatomy so that it is challenging to distinguish manually, including the type of Fantail, Ranchu, Oranda. This study aims to create a system that can identify these species. The identification process uses a feature extraction method, namely the Gabor Filter. Gabor filter consists of several steps including parameter initialization, Gabor kernels, Gabor convolution, feature point. The parameters used were frequency, orientation, and kernel’s size. Gabor kernel was formed based on initialized parameters. The addition of pixels for the goldfish image and Gabor's kernel produces a convolution process. The results of the convolution process were normalized to produce a feature vector matrix. The goldfish image classification uses the Probabilitas Neural Network method. The dataset in this research used 216 images of goldfish consisting of the Fantail, Oranda, and Manchu species. The combination of values of each parameter can affect the level of accuracy. Optimal parameters are obtained at kernel size (5.5), frequency (3), orientation (5), and downsample (16.16). The higher the parameter value, the more variation of the feature vector is obtained. The more variations of the feature vector, the higher the data redundancy so that the classification process becomes inefficient. The average accuracy of using a Gabor filter for image identification of goldfish reaches 80.86%.
SiNext: The next generation sign language

In today’s smart world people are using smart assistants that made their life easier than ever before. The only principle in this technology is the human voice which plays a key role in this. If the voice is the future of computing what about those who cannot hear or speak? The hearing and speaking impairment society aren’t able to communicate with it. They can only communicate via sign language.The aim is to create a model that can speak up on behalf of the user to the smart assistants so that they can also communicate with them and they can also take advantage of modern technology like home automation.The model uses 'deeplearn-knn-image-classifier' to classify the images and 'knn.predictClass' to predict the signs. Model accuracy during the testing was 90.25%.
Comparision of RBC size and mean corpuscular volume in automated peripheral smear system

Introduction:The MCV procedure is used to determine the average size of red blood cells as well as any anomalies.It is part of a routine check-up to detect any anomalies.Haematocrit values and RBC count are used to measure MCV.Despite the fact that the MCV is a predictor of RBC scale, the estimate relied solely on the PCV and RBC count.The aim of this research is to determine the relationship between MCV and RBC scale.Materials and Methods: A total of 80 patients' blood samples were randomly obtained from an academic laboratory.To save the blood from clotting, anticoagulants are used.The RBC size is determined using a regular formula from the collected sample's peripheral smear.The automatic hemology analyser is used to extract MCV from the laboratory.The data were statistically analyzed. Results and Conclusion:According to the analysis, a pathologist will evaluate macrocytic or microcytic RBCs without using an automatic analyzer and without scanning for and comparing the size of small lymphocytes by using the peripheral smear alone and comparing the MCV values.There is a need for a scale (in-built Vernier caliper) in the microscope, which is useful for RBC size measurement and also saves time.According to the findings, there is a statistically significant linear association between RBC size and MCV.
3D Medical Image Augmentation for Improving Deep Neural Networks

This paper proposes a 3D image augmentation method for improving the generalization performance of deep neural networks. It allows us to enrich the diversity of training data samples that is essential in medical image segmentation tasks, thus reducing the data overfitting problem caused by the fact the scale of medical image dataset is typically smaller. It also enables us to predict medical segmentation surfaces in Euclidean space without additional labeled datasets. This method includes image transformation functions, which are comprised of a spatial deformation and image intensity change, enabling the synthesis of complex effects such as variations in anatomy and image acquisition procedures. Our numerical experiments demonstrate that the proposed approach provides significant improvements over state-of-the-art methods for 3D medical image segmentation.
Automatic Test Pattern Generation using Grover’s Algorithm

Quantum computing is an exciting new field in the intersection of computer science, physics and mathematics. It refines the central concepts from Quantum mechanics into its least difficult structures, peeling away the complications from the physical world. Any combinational circuit that has only one stuck at fault can be tested by applying a set of inputs that drive the circuit to verify the output response. The outputs of that circuit will be different from the one desired if the faults exist. This project describes a method of generating test patterns using the Boolean satisfaction method. First, the Boolean formula is constructed to express the Boolean difference between a fault-free circuit and a faulty circuit. Second, the Boolean satisfaction algorithm is applied to the formula in the previous step. The Grover algorithm is used to solve the Boolean satisfaction problem. The Boolean Satisfiability problem for Automatic Test Pattern Generation(ATPG) is implemented on IBM Quantum Experience. The Python program initially generates the boolean expression from the file and converts it into Conjunctive Normal Form(CNF) which is passed on to Grover Oracle and runs on IBM simulator and produces excellent results on combinational circuits for test pattern generation with a quadratic speedup. Grover’s Algorithm on this problem has a run time of O(√N).
Exclusive Mining of blockchain transactions

After creating a new blockchain transaction, the next step usually is to make miners aware of it by having it propagated through the blockchain’s peer-to-peer network. We study an unintended alternative to peer-to-peer propagation: Exclusive mining. Exclusive mining is a type of collusion between a transaction initiator and a single miner (or mining pool). The initiator sends transactions through a private channel directly to the miner instead of propagating them through the peerto-peer network. Other blockchain users only become aware of these transactions once they have been included in a block by the miner. We identify three possible motivations for engaging in exclusive mining: (i) reducing transaction cost volatility (“confirmation as a service”), (ii) hiding unconfirmed transactions from the network to prevent frontrunning and (iii) camouflaging wealth transfers as transaction costs to evade taxes or launder money. We further outline why exclusive mining is difficult to prevent and introduce metrics which can be used to identify mining pools engaging in exclusive mining activity.
Weighted Model Counting with Conditional Weights for Bayesian Networks

Weighted model counting (WMC) has emerged as the unifying inference mechanism across many (probabilistic) domains. Encoding an inference problem as an instance of WMC typically necessitates adding extra literals and clauses. This is partly so because the predominant definition of WMC assigns weights to models based on weights on literals, and this severely restricts what probability distributions can be represented. We develop a measure-theoretic perspective on WMC and propose a way to encode conditional weights on literals analogously to conditional probabilities. This representation can be as succinct as standard WMC with weights on literals but can also expand as needed to represent probability distributions with less structure. To demonstrate the performance benefits of conditional weights over the addition of extra literals, we develop a new WMC encoding for Bayesian networks and adapt a state-of-the-art WMC algorithm ADDMC to the new format. Our experiments show that the new encoding significantly improves the performance of the algorithm on most benchmark instances.
Relative Effectiveness of Computer Simulation Instructional Package and Four Mode Application Technique in Teaching Difficult Chemistry Concepts in Secondary Schools in Nigeria

The study identified the concept-Electrolysis in Ordinary Level West African School Certificate (WASC) chemistry syllabus as a topic that was not usually well taught by Chemistry Teachers due to either lack of competence or inappropriate pedagogical skills by the Chemistry Teachers. Hence the study examines the relative effectiveness of Computer Simulation Instructional Package (CSI), Four Mode Application Technique (4MAT) and Lecture Method (LM) in improving studentsâ performance in chemistry. The study adopted a pretest post-test experimental design with lecture method as the control group. The sample consisted of 180 participants selected from three Senior Secondary School II (SSS II) Chemistry Students in Akure North Local Government Area of Ondo State. The sample was classified into two experimental groups (CSI 60), (4MAT 60) and a control group (LM 60). A 15 item instrument tagged Electrolysis Chemistry Achievement Test (ECAT) was developed by the researcher and ascertained for reliability (r 0.78, p(2,177) 7.121. Furthermore, CSI was found to be more effective (X 11.88) than 4MAT (X 11.03) . The study concluded that CSI is an effective method in teaching electrolysis in secondary schools in Nigeria.
Trustworthy Machine Learning: Past, Present, and Future

Fueled by massive amounts of data, models produced by machine-learning (ML) algorithms, especially deep neural networks (DNNs), are being used in diverse domains where trustworthiness is a concern, including automotive systems, finance, healthcare, natural language processing, and malware detection. Of particular concern is the use of ML algorithms in cyber-physical systems (CPS), such as self-driving cars and aviation, where an adversary can cause serious consequences. Interest in this area of research has simply exploded. In this work, we will cover the state-of-the-art in trustworthy machine learning, and then cover some interesting future trends.
Image Segmentation Using A Neoteric-Adaptive Fusion Of Fuzzy C-Means Clustering Model And Fuzzy Svm

Image Clustering processes have effectively remained as an alphanumeric method of image separation method in many arenas and applications. A clustering algorithm screens records that are keen on numerous groups in such a way that the resemblance inside a group is enhanced than between groups.  On the other hand, those grouping procedures are merely relevant for explicit images like medicinal images, atomic pictures, etc. In this paper, we extant a novel grouping procedure grounded on A Neoteric-Adaptive Fusion of Fuzzy C-Means (NAF-FCM) for image separation which might be useful on broad images and exact images like medicinal and atomic images, seized using communal digital cameras and Charged-Couple Device cameras. The procedure involves the notions of fuzziness and belongingness to offer an improved and further adaptive grouping process as matched to numerous conventional grouping procedures. Both high quality and quantifiable investigates favor the projected grouping procedure in terms of furnishing an improved segmentation enactment for several numbers of segmented regions.  This work incorporates image segmentation using a fusion of fuzzy c-means clustering model with fuzzy SVM classification to identify the changed areas using remote sensing images.   The proposed algorithm is concentrated on fast and exact clustering. Grounded on the consequences assimilated, the projected system contributes an enhanced visual quality and its performance is compared with the conventional K-means clustering procedure. The result acquired from the proposed Neoteric Adaptive clustering process is far better than the conventional K-mean procedure.
Using Nursery Rhymes to Enhance Vocabulary Among Young English Learners in Indonesia

This research is being conducted to examine and explain the results of using nursery rhymes in improving vocabulary skills among young English learners in Indonesia. This study focuses on whether the use of nursery rhymes in English teaching will significantly improve vocabulary mastery among Indonesian elementary learners. Two English teachers and eighty students from two elementary schools in Depok-Sleman, Yogyakarta, Indonesia who are in third grade and aged between eight and nine years participated in this report. The theoretical basis of this current study is based on the concrete theory of learning by Ausubel, the theory of social constructivism by Vygotsky and the theory of second-language acquisition by Krashen. This research employs the quasi-experimental approach, the experimental group was taught English using nursery rhymes and the control group was taught over a span of eight weeks using traditional method. Pre-test and post-test instruments were used to collect data for the analysis. The results suggest that the use of nursery rhymes substantially improved average vocabulary scores for the students. Students from the experimental group also performed significantly better in matching the vocabulary with the correct image, matching the English vocabulary with its synonyms in Bahasa Indonesia and filling in the blanks with the right choice of English vocabulary compared to their counterparts in the control group. This study asserts that the use of nursery rhymes can significantly enhance the awareness of vocabulary among students. This research also has significant pedagogical implications and developments on the use of nursery rhymes to teach English vocabulary. Hopefully the Indonesian Ministry of Education and Teacher Education Division will train teachers to use nursery rhymes to develop English vocabulary for young learners.
Rancang Bangun Sistem Informasi E-Archives di Dinas PU Bina Marga dan Tata Ruang Provinsi Sumatera Selatan Berbasis Web

Archives are a very important source of information in an office, but archive management is often neglected and inefficient, this can cause various problems from damage to archives to loss of archive data. The purpose of this study was to determine the archive management procedure at the Public Works Office of Bina Marga and Spatial Planning of South Sumatra Province. Methods in collecting research data used are observation, interviews and documentation. Based on the results of observations on the management of archives at the Office of PU, Bina Marga and Spatial Planning, South Sumatra Province, including recording incoming and outgoing letters done manually, poor archive storage and maintenance, poorly maintained archive storage and difficult to search for archives. So it is necessary to have an information system for archive management, an archive information system built using the PHP programming language and the web-based CodeIgniter framework. The results of this design are in the form of a web-based archive information system that can manage the recording of incoming mail, outgoing mail, mail search, and digital archive storage.
Using Monolingual in Educational Subject for English Lecturers

The research is a case study which aim at finding out 1) Whether lecturers use monolingual or bilingual in teaching educational subjects and How the English language lecturers verbally transform teaching material in educational subjects to English language education students. The subjects were lecturers who taught the subject (3 lectures). The technique of data collection was done through deep interview and field note. The analysis technique refers to Craswell's theory includes categorization, direct interpretation, forming patterns, and naturalistic generalizations. The results show: 1) In general they use monolingual (Indonesian language) in transforming educational subject teaching materials to their students, while the use of English is only at the brainstorming stage. The portion of Indonesian is more dominant than foreign language. It because of teaching materials for education courses have complex and general material content so that in the material delivery process, monolingual is considered more effective than bilingual both, lecturers to students and students to students in their core activities; 2). In the 3rd teaching processes in the class, it was revealed that in the pre-activity, the lecturer explained or introduced brainstorming material in Indonesian, but there were also lecturers who used English. In the activities phase generally applied discussion classes, there are lecturers who apply English by means of student paper assignments made in English and Indonesian-language presentations, some are the opposite, and there are also full Indonesian-language activities. In the post activity stage, the activity concludes the learning process activities of the lecturers generally used monolingual.
Project: Paint App with Tkinter

In the previous chapter, we learned how to create a Tic Tac Toe app with Tkinter. We also learned all about events and how to use them to make our app respond to external events (mouse click, keyboard key press, etc.).
Information Seeking and Usage Behavior of @rlthingy’s Twitter Followers for Satisfying Their Information Needs

Social media became an information source. That situation made people rely more upon their information needs from social media despite its credibility. Its users also used Twitter to seek information, which is increasingly becoming more popular with a Twitter feature called Mention Confess (Menfess), developed by the Twitter account @biolbe. A Twitter account that provided Mention Confess services with the most followers in Indonesia is @rlthingy. @rlthingy aimed to satisfy the information needs of its followers' personal lives. Information Seeking Theory with qualitative methods and Netnography research design used in this research. This study showed the follower's interaction in seeking and using the information on @rlthingy's Twitter account. The results showed many personal motivations that made followers do the information-seeking on @rlthingy. Those were like the anonymous feature offered, comprehending people's opinions on a problem to add insight and provide entertainment. The anonymous feature was viral for @rlthingy's followers because they could ask questions without thinking about the stereotypes that would attach to them. The study also showed how followers would always be synergistic about seeking and using information simultaneously. That situation happened because they felt responsible for the information and co-existence with other followers' problems. Information behavior made by @rlthingy followers also made by liking Mention Confess, which were considered necessary. The results also showed information processing behavior done. Information procession depended on the nature of the Public Significance of the urgency of information. If the answer had a high Public Significance and being in an urgent situation for @rlthingy followers, they would immediately believe in the information and vice versa.
STRUCTURAL-PHOTOMETRIC IMAGES AS REFLECTION OF THE TIEN SHAN INTEGRAL TECTONIC SEGMENTATION

The article discusses (first) the possibility of the structural-photometric images application for the Tian Shan intracontinental orogen segmentation. With the help of the Photoshop Pro program, the geological map into a system of graphic images was transformed. This technique allowed to identify the integral structural and morphological heterogeneity of the Kyrgyz Tian Shan upper crust and to create a scheme of the region's morphostructural segmentation.
CRITICS (CRITICISM) OF EXISTING APPROACHES TO DETERMINING THE CONTENT OF INFORMATION

The article provides critical remarks on the application of some of the existing approaches to the study of the «content of information» as a separate phenomenon. It is shown that neither a word, nor, moreover, a «number» or «sign» («symbol»), can be taken as a unit of information content. Moreover, they cannot be taken as a basis for searching for units of information content.
Bit-Parallel ECC Coprocessor resistant to Differential Power Analysis Attacks in GF(2m)

Elliptic curve cryptography (ECC) is one of the most popular public key systems in recent years due to its both high security and low resource consumption. Thus, ECC is more appropriate for Internet applications of Things, which are mainly involved with limited resources. However, non-invasive side channel attacks (SCAs) are considered as a major threat to ECC systems. In this paper, we design a processor for the ECC in the binary field, resistant to differential power attacks (DPA). The main operations in this architecture are randomized Montgomery multiplication and division units, which make it impossible to create DPAs by involving a random number in the calculation process. The goal is to accelerate the operation by opening the loops in the Montgomery randomized multiplication/division units, and accordingly, bit-parallel design instead of bit serial design. The results show that, despite the complexity of the logic in the two/three-bit processing versions, the speed is significantly improved by accepting a slight increasing in the area resource. Further, our design is flexible where in the top-level module, depending on the area-speed trade-off, a variety of multiplier and divisor units can be selected. The FPGA evaluations show that in terms of Time×Slice metric, the 2-bit divider/3-bit multiplier version of our architecture leads to 40% improvement over the best previous work. Further, by duplicating the divider and multiplier modules along the bit-parallel architecture this gain can reach to 50%. In terms of operation speed, our design versions are faster than previous work by a factor of 1.87 and 3.29. Furthermore, ASIC evaluations in term of Time×Area metric, indicate that deploying 2-bit multiplier leads to 19% gain relative to previous well-known work. Moreover, duplication of modules along with bit-paralleling amplifies the overall gain up to 36%.