Reviewerly/exHarmony huggingface dataset:
Sistem Informasi Geografis Pemetaan Rumah Sakit di Kota Pontianak Berbasis Web

The availability of information that is very limited to the location of hospitals in Pontianak City causes people to tend not to have accurate and relevant information so that they do not know which hospital location is close to where they live. This is very important because to anticipate things that are not desirable. The purpose of this study was to produce a web-based hospital geographic information mapping software system so that the availability of a clear geographical picture of the state and spread of hospitals in Pontianak City. The form of research used in this study is literature and survey studies, the authors' research variables are the distribution of hospitals in the city of Pontianak and the coordinates of the location of the hospital. The design method used is Rapid Application Development (RAD). For the description of the system modeling using use case, sequence, component and class diagram. While the development of the system uses the PHP programming language, MySQL as the database. The results of this software are in the form of a website that will display information on the location of the hospital on a digital map using Google Map API technology. This software is expected to help the community in finding information on the location of hospitals in Pontianak City
IMPROVING WRITING SKILL OF JUNIOR HIGH SCHOOL STUDENTS THROUGH PICTURE SERIES MEDIA

This research objective was to find out whether there was any significant difference in students’ writing skill before and after being taught using Picture Series media in learning recount text at Eighth grade students of SMP Negeri 8 Tarakan. The design of this research was Pre-Experimental research. The population in this research was all of the eighth grade students at SMP Negeri 8 Tarakan. The sample  in  this  research  was  30  students.  The  sample  was  chosen  by  using purposive sampling technique. Class for treatment was VIII-6. It consisted of 30 students. The steps in this research were pretest, treatment, and posttest. In the pretest, the students were asked to write the writing test. After giving the pretest, the researcher gave treatment. The treatment class was taught by using Picture Series media. After giving the treatment, students were asked to write the writing test in posttest. In analyzing the data, the researcher was used paired sample t-test in SPSS 24.0. The result of this research showed that there was different mean score in pretest and posttest. It was proven by the result of the students’ mean score from pretest was 36.27 and 43.20 in the posttest. It means that the improvement of the students’ mean score was 6.93. The result of Paired Sample t-test was 2.119 higher than t-table was 2.045. It means that the students’ writing skill in recount text have an improvement after giving the treatment. The result of sig (2 tailed). 0.000 is lower than 0.05, it means that the Picture Series media can give any contribution to the students’ writing skill. Based on the explanation above, it can be concluded that using Picture Series Media is effective to improve student’s writing skill in recount text.
A new method for Searching Optimal Differential and Linear Trails in ARX Ciphers.

In this paper, we propose an automatic tool to search for optimal differential and linear trails in ARX ciphers. It’s shown that a modulo addition can be divided into sequential small modulo additions with carry bit, which turns an ARX cipher into an S-box-like cipher. From this insight, we introduce the concepts of carry-bit-dependent difference distribution table (CDDT) and carry-bit-dependent linear approximation table (CLAT). Based on them, we give efficient methods to trace all possible output differences and linear masks of a big modulo addition, with returning their differential probabilities and linear correlations simultaneously. Then an adapted Matsui’s algorithm is introduced, which can find the optimal differential and linear trails in ARX ciphers. Besides, the superiority of our tool’s potency is also confirmed by experimental results for round-reduced versions of HIGHT and SPECK. More specifically, we find the optimal differential trails for up to 10 rounds of HIGHT, reported for the first time. We also find the optimal differential trails for 10, 12, 16, 8 and 8 rounds of SPECK32/48/64/96/128, and report the provably optimal differential trails for SPECK48 and SPECK64 for the first time. The optimal linear trails for up to 9 rounds of HIGHT are reported for the first time, and the optimal linear trails for 22, 13, 15, 9 and 9 rounds of SPECK32/48/64/96/128 are also found respectively. These results evaluate the security of HIGHT and SPECK against differential and linear cryptanalysis. Also, our tool is useful to estimate the security in the design of ARX ciphers.
Improving object recognition of CNNs with multiple queries and HMMs

In our paper we combine neural networks with Hidden Markov Models for multiview object recognition. While convolutional neural networks are very efficient in object recognition there is still need for improvements in many practical cases. For example if the training is not satisfactory or the object localization is not solved with the neural network then information fusion from several images and from inertial sensors can still help a lot to improve recognition rate. In our use case we are to recognize objects from several directions with the VGG16 network. We assume that no localization of objects is possible on the images due to the lack of bounding box annotations, we have to recognize the objects even if they occupy only about 25% of the field of view. To overcome this problem we propose to use a Hidden Markov Model approach where the consecutive queries, shots taken from different viewing directions, are first evaluated with VGG16 inference and then with the Viterbi algorithm. The role of the later is to estimate the most probable sequence of poses of candidates (from the predefined 8 horizontal views in our experiments), thus we can select the most probable object. The approach, as evaluated with different number of queries over a set of 40 objects from the COIL-100 dataset, can result in significant increase of hit rate compared to one shot recognition or to combining individual shots without the HMM model.
Next Frame Prediction Using Flow Fields

Next frame prediction is the challenging task in computer vision and video prediction. Despite the longtime studies in video processing, the next frame prediction problem is rarely investigated and it is at its beginning. In next frame prediction, the main goal is to design a model which automatically generates the next frame using a sequence of previous frames. In videos, in most cases, the large portion of the current frame is similar to the previous frames and only a small portion of the frame has a motion field. This leads us to utilize the optic flow field. To do so, Laplacian pyramid of convolutional networks and adversarial learning are used to predict simultaneously the optic flow and the gray content of the next frame. To evaluate the proposed approach, it is applied on UCF101 dataset. The obtained results show that our approach achieves a better performance.
A tutorial on ensembles and deep learning fusion with MNIST as guiding thread: A complex heterogeneous fusion scheme reaching 10 digits error.

Ensemble methods have been widely used for improving the results of the best single classification model. Indeed, a large body of works have achieved better results mainly by applying one specific ensemble method. However, very few works analyze complex fusion schemes using heterogeneous ensemble strategies. This paper is three-fold: 1) It provides a tutorial of the most popular ensemble methods, 2) analyzes the best ensembles using MNIST as guiding thread and 3) shows that complex fusion architectures based on heterogeneous ensembles can be considered as a mode of taking benefit from diversity. We introduce a complex fusion design that achieves a new record in MNIST with only 10 misclassified images.
Educational Multimedia for the learning of local archeology in the career degree in History at the University of Holguin

The objective of this research is to introduce an Educational Multimedia Software named Arqueologia en Holguin, whose purpose is to favor the teaching-learning process of topics related to archaeological research in students enrolled in the degree in History at the University of Holguin. Due to its social and patrimonial importance, the domain of this subject constitutes a necessity in the integral formation of the graduates of this specialty. With the use of methods at the theoretical and empirical levels, the teaching - learning process of this discipline was characterized and some of its main deficiencies were identified. Information and Communication Technologies offer a set of advantages and opportunities to introduce, socialize and learn about the scientific work in this profile and increase the archaeological culture, taking advantage of them as an element that motivates young people to a large extent. The main result of this research is the development and implementation of Educational Multimedia Software Arqueologia en Holguin, which was conceived for informative, educational and training purposes, constituting an updated bibliographic material. Some of the main features and functionalities of the proposed software are described and some methodological recommendations are offered to teachers who choose to use this resource. With the application of statistical methods and hypothesis testing, an initial assessment is made of the effectiveness of the resulting software
The benefits of synthetic data for action categorization

In this paper, we study the value of using synthetically produced videos as training data for neural networks used for action categorization. Motivated by the fact that texture and background of a video play little to no significant roles in optical flow, we generated simplified texture-less and background-less videos and utilized the synthetic data to train a Temporal Segment Network (TSN). The results demonstrated that augmenting TSN with simplified synthetic data improved the original network accuracy (68.5%), achieving 71.8% on HMDB-51 when adding 4,000 videos and 72.4% when adding 8,000 videos. Also, training using simplified synthetic videos alone on 25 classes of UCF-101 achieved 30.71% when trained on 2500 videos and 52.7% when trained on 5000 videos. Finally, results showed that when reducing the number of real videos of UCF-25 to 10% and combining them with synthetic videos, the accuracy drops to only 85.41%, compared to a drop to 77.4% when no synthetic data is added.
Sensing share space using Stereo Vision

With the increasing popularity of active modes (mainly pedestrians and bicycles), the spaces shared amongst these modes are also rising. Such spaces are often referred to as shared spaces and can often be seen in public areas near train stations, shopping streets and educational institutions. Such spaces are said to enhance safety and resolve spatial limitations of the space while the users are seen to exhibit interesting and complex behaviours as they freely interact with different modes approaching from various directions. This creates a need to collect data and understand the behaviour of people within such spaces. Many studies focusing on shared space interactions are limited by the current methods of data collection and data extraction. Other studies on people movement also face similar issues. Current data extraction approaches using cameras include repetitive and labour-intensive tasks which makes them costly and inefficient. Thus, this study focuses on automating the data extraction approach to obtain the ground-plane trajectories of people using the data recorded from a 3D-stereo vision camera. The data processing framework was divided into three main stages, (i) agent detection, (ii) ground-plane representation and (iii) agent tracking. The agent detection uses a neural-network-based detection model to detect people on the visual video which is then paired with the depth data to represent people on the ground plane. Each person is represented as a single point on the ground plane for every frame of the video. These points were then inputted into a tracking model to provides trajectories of people on the ground plane. Overall, this research integrates the recent state-of-the-art technologies into a single framework to automate the data extraction process and tests this framework in a real-world setting (behind the Amsterdam central station’s shared space area). For each stage, the advantages, challenge and recommendation for further improvements have been made. By automating the data processing of real-world datasets (including pedestrians and cyclists), This study reduces the cost and provides an easy way to collect and process data on real-world movements of pedestrians and cyclists. This will encourage urban planners to better understand people’s movement within their spaces and facilitate data-driven design approaches in the future.
Physical Training Evaluation Method for College Students Based on Analytic Hierarchy Process

This study introduces a physical training evaluation method based on the analytic hierarchy process to solve the difficulty of quantifying the evaluation of the physical training of college students. First, this method establishes an evaluation index system and constructs the corresponding evaluation index judgement matrix. Second, it normalises and calculates the index combination weight for constructing the basic evaluation model. Finally, this evaluation model is comprehensively utilised to evaluate the physical training of college students. The results denote that the method proposed in this study can effectively evaluate the physical training of college students. When compared with the traditional assessment method, the proposed method can better reflect the real physical condition and highlight the physical characteristics of the college students as well as conduct targeted training for the college students.
Research Guides: RefWorks: Create an Account

The University Libraries will support the Legacy RefWorks through June 2020. Starting July 2020, the libraries will only support the new version of RefWorks and cannot assure the continued access to or functionality of the Legacy version.
On Constructing Confidence Region for Model Parameters in Stochastic Gradient Descent Via Batch Means

We study an easy-to-implement algorithm to construct asymptotically valid confidence regions for model parameters in stochastic gradient descent. The main idea is to cancel out the covariance matrix which is hard/costly to estimate using the batch means method with a fixed number of batches. In developing the algorithm, we establish a process-level functional central limit theorem for Polyak-Ruppert averaging iterates. We also extend the batch means method to accommodate more general batch size specifications.
The Ethereal Library: Our Experience in Library Futures at the Kresge Library

Virtual presentation at the International Conference on Next Generation Libraries – 2019 - National Institute of Technology – Rourkela (Rourkela, Odisha, India)December 12-14, 2019
Boolean Functions with Multiplicative Complexity 3 and 4.

Multiplicative complexity (MC) is defined as the minimum number of AND gates required to implement a function with a circuit over the basis (AND, XOR, NOT). Boolean functions with MC 1 and 2 have been characterized in Fisher and Peralta (2002), and Find et al. (IJICoT 4(4), 222–236, 2017), respectively. In this work, we identify the affine equivalence classes for functions with MC 3 and 4. In order to achieve this, we utilize the notion of the dimension dim(f) of a Boolean function in relation to its linearity dimension, and provide a new lower bound suggesting that the multiplicative complexity of f is at least ⌈dim(f)/2⌉. For MC 3, this implies that there are no equivalence classes other than those 24 identified in Calik et al. (2018). Using the techniques from Calik et al. and the new relation between the dimension and MC, we identify all 1277 equivalence classes having MC 4. We also provide a closed formula for the number of n-variable functions with MC 3 and 4. These results allow us to construct AND-optimal circuits for Boolean functions that have MC 4 or less, independent of the number of variables they are defined on.
UTILITY OF DIRECT ANTIGLOBULIN TEST (DIRECT COOMBS TEST) - AN URBAN PUBLIC HOSPITAL EXPERIENCE

Introduction and Aims-The Direct Antiglobulin Test (DAT) is the test that detects immunoglobulin and/or complement on surface of red blood cells. Most of the laboratory use conventional tube technique but in 2-6% of cases of patients with clinical symptoms of hemolysis turn out coombs test negative on repeated testing. Hence we conducted this study to know more sensitive, simpler and cost effective technique of performing direct coombs test. Materials and Methods-A prospective study was performed over period of 18 months 500 cases of various indications were studied February 2018 to August 2019. Results-Sensitivity of gel technique was 100%, specificity was 96.12%, positive predictive value is 84.62% and negative predictive value was 100% in our study. There was 95% agreement between the results of gel card method and conventional tube method. Conclusion- In present study it was observed that Gel Technique was easier and quicker with better sensitivity than Conventional Tube Technique.
Proposal of Encoder and Decoder for Quantum Channel Compression

Recently, the quantum channel compression has been proposed. It is an encoding method, which reduces the channel resources (bits and qubits) used in a quantum secure communication protocol. The paper proposes a first-time practical implementation of this encoding process - encoder and decoder are designed. Thus, the practical feasibility of the quantum channel compression is demonstrated. The functional designs of the encoder and decoder are presented and verified by the software Quartus II v. 8.1, Web Edition. It was found that the implementation of quantum channel compression allows reducing not only the resources but also the duration of a quantum secure communication owing to a parallelism in the decoding part of the system.
Discretionary Denials of IPR Institution

On September 12, 2018, the PTAB in NHK Spring Co. v. Intri-Plex Techs., Inc., No. IPR2018-00752, Paper 8 (P.T.A.B. Sept. 12, 2018), exercised its 35 U.S.C. § 314(a) discretion to deny IPR institution, despite the IPR petition’s timely filing, due to a parallel district court trial scheduled six months away. On May 7, 2019, the PTAB designated NHK Spring as precedential, characterizing NHK Spring’s finding of the co-pending district court proceeding as “nearing completion.” The PTAB has even “recognized in cases such as NHK Spring that the fact that the court will resolve the same issues raised by the Petition, at an earlier date than the Board, gives rise to inefficiencies and duplication of effort between the tribunals.” Hormel Foods Corporation et al v. HIP, Inc., No. IPR2019-00469, Paper 9 (P.T.A.B. July 15, 2019). For instance, in May 2019, the PTAB in E-One, Inc. v. Oshkosh Corp., No. IPR2019-00161, Paper 16 (PTAB May 15, 2019), denied an IPR institution under § 314(a) due to a parallel district court trial scheduled eleven months away. This paper aims to illuminate what happened in NHK Spring and its progeny, both before and after the PTAB’s precedential designation, to inform PTAB readers of this interesting development on the PTAB’s exercise of § 314(a) discretionary denials, and to provide examples of what the PTAB’s term “nearing completion” means.
Development of The Scale of Earthquake Knowledge Level: Validity and Reliability Study

&lt;div&gt;The study group of this research, which aims to develop The Scale of Earthquake Knowledge Level, consists of students studying at Duzce University in the academic year 2018-2019. A total of 728 volunteers, 501 of whom were women and 227 were men, was included in the research group determined by random sampling method. As a result of the exploratory factor analysis, which was completed after testing the suitability of the data for analysis, the scale showed a three-dimensional structure consisting of 19 items. The factors that constitute the scale explain 61,744% of the variance. The sub-dimensions of the scale were named based on the knowledge about the earthquake. The suitability of the obtained model was 0.072 for RMSEA, 0.93 for NFI, 0,89 for GFI, 0.041 for RMR, and 0.86 for AGFI. As a result of the reliability analysis, the internal consistency coefficient (Cronbach alpha) of the scale was determined as 0.868. It is thought that this developed scale will provide support as a tool for educational purposes. It is recommended to carry out different researches that can help to investigate the level of knowledge about the earthquake with different variables.&lt;/div&gt;
Efficient Photometric Alignment for Around View Monitor System

Around view monitor system has become a typical advanced driver-assistance system. Nevertheless, due to the differences between the lenses and sensors, the output image of around view monitor system inevitably has the visible brightness difference at the overlapping area of the images, and there are still obvious seams in the image mosaic. Photometric alignment aims to match the brightness of images under different illumination conditions and can be used to eliminate seams in the stitching image. The existing photometric alignment methods are mainly based on the gain compensation of three RGB channels, which not only increase the computational complexity but also affect the quality of output image. This paper proposes a new photometric alignment algorithm based on brightness channel and image fusion technology. Experimental results demonstrate that the seams in the final bird's-eye view are smoothly compensated.
Diagnosis of Leadership Potential in High School Students with Special Needs in the Environment of an Inclusive Educational Institution

There is a need in Ukraine to create special conditions in higher educational institutions to serve the increasing number of people with special needs. Inclusive education involves the creation of an educational environment that meets the needs and capabilities of the child, regardless of the characteristics of his or her psychophysical development. Our work focuses on the study of the “leadership potential of the individual.” This is defined as a socio-psychological characteristic of the individual, reflecting the ability to influence the environment through one’s own personal resources.It has been found that a leader should have the maximum influence on the group’s life. A leader must represent the group values. Also, he or she should be able to take responsibility for the group and be focused on the common tasks. The task was to determine whether the level of leadership development depends on the availability of special needs for high school students. A set of diagnostic methods was used for the purpose of pedagogical diagnostics: the technique “Diagnosis of motivation for success and fears of failure,” the technique for determination of leadership potential and the method “Leadership Self-assessment.” The conducted diagnostic research made it possible to state that the students’ special needs are not significant obstacles for the development of their leadership qualities. The results showed that high and average levels of leadership potential prevail. We believe that if proper conditions in a general school for children with special needs are created, they can become active civic activists and charismatic leaders.