Reviewerly/exHarmony huggingface dataset:
Function Point Analysis On Software Effort Estimation Using Artificial Intelligence

Understanding the size and effort taken for a programming project in the beginning phases is pivotal yet difficult. Over the years several researchers and experts worked for this cause and developed various methods. As said above, several methods exist for the purpose of estimating effort but the accuracy is still unsatisfying. After abundant research, in this paper, we propose a method which is simpler and accurate i.e., Function Point Analysis (FPA). The Function point investigation technique was created by A. J. Albrecht (1979) to help measure the size of an automated business data framework. These sizes are utilized as a part for the estimation of profitability in framework improvement and support exercises, and as a segment for assessing the exertion required for such exercises. Close assessment of the technique shows certain shortcomings, and the creator proposes a halfway other option. A depiction is given of the standards of this Mark II methodology. The outcomes are introduced of certain estimations of real frameworks to adjust the Mark II methodology, and ends are drawn on the legitimacy and relevance of capacity point investigation by and large.
Dynamic Latent Scale GAN

Generator of generative adversarial networks (GAN) maps latent random variable into data random variable. GAN inversion is mapping data random variable to latent random variable by inverting the generator of GAN. When training the encoder for generator inversion, using the mean squared error causes the encoder to not converge because there is information loss on the latent random variable in the generator. In other words, it is impossible to train an encoder that inverts the generator as it, because the generator may ignore some information of the latent random variable. This paper introduces a dynamic latent scale GAN, a method for training a generator that does not lose information from the latent random variable, and an encoder that inverts the generator. When the latent random variable is a normal i.i.d. (independent and identically distributed) random variable, dynamic latent scale GAN dynamically scales each element of the latent random variable during GAN training to adjust the entropy of the latent random variable. As training progresses, the entropy of the latent random variable decreases until there is no information loss on the latent random variable in the generator. If there is no information loss on the latent random variable in the generator, the encoder can converge to invert the generator. The scale of the latent random variable depends on the amount of information that the encoder can recover. It can be calculated from the element-wise variance of the predicted latent random variable from the encoder. Since the scale of latent random variable changes dynamically in dynamic latent scale GAN, the encoder should be trained with a generator during GAN training. The encoder can be integrated with the discriminator, and the loss for the encoder is added to the generator loss for fast training.
Motion capture in humanoid model with Unity engine using Kinect V2

Animation is a technique to create illusion of motion, which is created by displaying a series of motionless pictures in sequence or using a spine/bones to create motion that looks real. All this time, the process of creating an animation still using traditional technique which requires special skills and take some time to finish a complicated animation which is used in movies or video games. Motion capture is an animation-making technique by tracking every part of body in order to find position and rotation of human’s joints which is generated by the image from the sensor. Motion capture has lots of method, such as marker base technique which use mark to track any motions. Motion capture markerless method that can capture or track motions without using any marks. Motion capture with markerless technique can be done by using RGB-Depth’s camera censor, which is by using Microsoft Kinect V2 with Kinect V2 SDK in order to make Kinect connected with computer, and using Unity Engine, a game engine that has already provided animation timeline and supports any 3D format which contains animation file that can be used in mostly other models which is using humanoid. In order to obtain motion data  which will be changed into skeleton joint data, we will use connector OpenNI and 3D Collada model with (.dae) format because Collada is 3D format Open Source which is built using XML-based so that it can easily read and written back into 3D file as an output.
Representation Memorization for Fast Learning New Knowledge without Forgetting

The ability to quickly learn new knowledge (e.g. new classes or data distributions) is a big step towards human-level intelligence. In this paper, we consider scenarios that require learning new classes or data distributions quickly and incrementally over time, as it often occurs in real-world dynamic environments. We propose "Memory-based Hebbian Parameter Adaptation" (Hebb) to tackle the two major challenges (i.e., catastrophic forgetting and sample efficiency) towards this goal in a unified framework. To mitigate catastrophic forgetting, Hebb augments a regular neural classifier with a continuously updated memory module to store representations of previous data. To improve sample efficiency, we propose a parameter adaptation method based on the well-known Hebbian theory, which directly "wires" the output network's parameters with similar representations retrieved from the memory. We empirically verify the superior performance of Hebb through extensive experiments on a wide range of learning tasks (image classification, language model) and learning scenarios (continual, incremental, online). We demonstrate that Hebb effectively mitigates catastrophic forgetting, and it indeed learns new knowledge better and faster than the current state-of-the-art.
Sistem Pakar dalam Menganalisis Alergi Kulit Manusia dengan Metode Certainty Factor

The skin is human’s outer sense, which servers as protection from bacteria, viruses, and solar flares, and as a sense. Skin may suffer from a variety of factors, one of which is allergies. Human skin allergies result from a pressurized immune system that humans normally react to certain substances, such as food, animal hair, or medicine. In addition to the three factors, a current of society giveslittle attention to skin allergies and lack of care or awareness is a trigger factor. Thus, the aim of this research is to analyze human skin allergies using the Certainty Factor method. By conducting interviews and observations on Rahmatan Lil ‘Alamin Clinic, Padang City, found 10 skin allergic kinds, 27 skin allergic symptoms, and 50 patients data. Those data are treated using the Certainty Factor method with stages to decisive symptom and allergic code, set the rule, set the weight, and calculate Certainty Factor score. In this research, it obtained test results at a percentage of a large 92% and the most allergic diagnosed is allergic dermatitis. By the test results inferable that expert system designed can be used to determine the diagnosis of human skin allergies.
Robust Privacy-Preserving Motion Detection and Object Tracking in Encrypted Streaming Video

Video privacy leakage is becoming an increasingly severe public problem, especially in cloud-based video surveillance systems. It leads to the new need for secure cloud-based video applications, where the video is encrypted for privacy protection. Despite some methods that have been proposed for encrypted video moving object detection and tracking, none has robust performance against complex and dynamic scenes. In this paper, we propose an efficient and robust privacy-preserving motion detection and multiple object tracking scheme for encrypted surveillance video bitstreams. By analyzing the properties of the video codec and format-compliant encryption schemes, we propose a new compressed-domain feature to capture motion information in complex surveillance scenarios. Based on this feature, we design an adaptive clustering algorithm for moving object segmentation with an accuracy of 4x4 pixels. We then propose a multiple object tracking scheme that uses Kalman filter estimation and adaptive measurement refinement. The proposed scheme does not require video decryption or full decompression and has a very low computation load. The experimental results demonstrate that our scheme achieves the best detection and tracking performance compared with existing works in the encrypted and compressed domain. Our scheme can be effectively used in complex surveillance scenarios with different challenges, such as camera movement/jitter, dynamic background, and shadows.
3D Scene Reconstruction with Multi-layer Depth and Epipolar Transformers

We tackle the problem of automatically reconstructing a complete 3D model of a scene from a single RGB image. This challenging task requires inferring the shape of both visible and occluded surfaces. Our approach utilizes viewer-centered, multi-layer representation of scene geometry adapted from recent methods for single object shape completion. To improve the accuracy of view-centered representations for complex scenes, we introduce a novel "Epipolar Feature Transformer" that transfers convolutional network features from an input view to other virtual camera viewpoints, and thus better covers the 3D scene geometry. Unlike existing approaches that first detect and localize objects in 3D, and then infer object shape using category-specific models, our approach is fully convolutional, end-to-end differentiable, and avoids the resolution and memory limitations of voxel representations. We demonstrate the advantages of multi-layer depth representations and epipolar feature transformers on the reconstruction of a large database of indoor scenes.
Upslices, Downslices, and Secret-Sharing with Complexity of $1.5^n$.

A secret-sharing scheme allows to distribute a secret s among n parties such that only some predefined “authorized” sets of parties can reconstruct the secret, and all other “unauthorized” sets learn nothing about s. The collection of authorized/unauthorized sets can be captured by a monotone function \(f:\{0,1\}^n\rightarrow \{0,1\}\). In this paper, we focus on monotone functions that all their min-terms are sets of size a, and on their duals – monotone functions whose max-terms are of size b. We refer to these classes as (a, n)-upslices and (b, n)-downslices, and note that these natural families correspond to monotone a-regular DNFs and monotone \((n-b)\)-regular CNFs. We derive the following results.
Design of College Students’ Career Planning Guidance System Based On B/S Three-Tier Architecture

At present, the guidance mode of college students’ career planning guidance system is imperfect, resulting in too long submission time. A college students’ career planning guidance system based on B/S three-tier architecture is designed. Hardware part: on the basis of obtaining the sensor dynamic compensation filter, expand 6 static memory; Software part: obtain the influencing factors of College Students’ career planning, combined with the external environment, use the B/S three-tier architecture to set the guidance mode, formulate the links of career planning, adopt the hierarchical management mode, and design the role authority management function of the system. Experimental results: the average submission time of the college students’ career planning guidance system designed this time and the other two systems is 11.277s, 16.253s and 15.554s, which proves that the college students’ career planning guidance system integrating the B/S three-tier architecture has a better effect.
What Is Happening With Education?

This paperwork aims to emphasize the utility of principles in defining new models of education, to outline the main traits of educational communities regarding mentorship relations, informational sources and intergenerational interaction. In the process of underlining how crucial it is to include principles and values in future educational models, the author raises the question “Why do we educate?”. The article shows great use for understanding the importance of updating the teaching methodologies, in order to better interact with new generations to come.
Multi Anchor Point Shrinkage for the Sample Covariance Matrix (Extended Version)

Portfolio managers faced with limited sample sizes must use factor models to estimate the covariance matrix of a high-dimensional returns vector. For the simplest one-factor market model, success rests on the quality of the estimated leading eigenvector "beta". When only the returns themselves are observed, the practitioner has available the "PCA" estimate equal to the leading eigenvector of the sample covariance matrix. This estimator performs poorly in various ways. To address this problem in the high-dimension, limited sample size asymptotic regime and in the context of estimating the minimum variance portfolio, Goldberg, Papanicolau, and Shkolnik developed a shrinkage method (the "GPS estimator") that improves the PCA estimator of beta by shrinking it toward a constant target unit vector. In this paper we continue their work to develop a more general framework of shrinkage targets that allows the practitioner to make use of further information to improve the estimator. Examples include sector separation of stock betas, and recent information from prior estimates. We prove some precise statements and illustrate the resulting improvements over the GPS estimator with some numerical experiments.
The Relationship between Perceived Corruption and FDI: A Longitudinal Study in the Context of Egypt

This paper investigates the dynamic relationship between perceived corruption and foreign direct investment (FDI) in Egypt during the period 1970–2019. Using a novel back-casting methodology, it extrapolates perceived corruption time series between 1970 and 1980. The results of the Johansen cointegration technique and the multivariate vector error correction model show a positive relationship between perceived corruption and FDI, supporting the “greasing the wheels” effect of corruption. This positive association can be explained by several factors, such as the cross-interdependence of rent-generating assets with perceived corruption and FDI, and the use of FDI data based on the balance of payments that has growing financial-flows and phantom-FDI components. The findings of this paper have important policy implications. Improving the fundamental governance structure in Egypt should be accompanied by a comprehensive investment facilitation strategy to compensate for the removal of “grease” from the “wheels”.
Quality Enhancement through Incorporating Studentcentered Learning Methods in Higher Education Institutions (HEIs)

One of the main tasks of higher education institutions is to attract their customers with its quality education. To improve education practices and to meet the challenges of an ever-changing environment, it is vital to introduce a paradigm shift in education. Hence, what we teach to our students is not enough, the way we teach them is what matters the most. There are several factors, which can serve as indicators of quality education. The demands, needs, expectations of the learners have changed. Accordingly, the primary goal of education is to provide the quality that ensures contemporary students not only with subject knowledge but also with the key skills needed for the 21st century world. Although the concept of student-centeredness is not new, challenges still exist concerning incorporating all characteristics and elements of the student-centered learning approach in Higher Education Institutions in Georgia. According to the previous studies, it is noticeable that the lack of resources and staff training are some of the hindering factors to create and maintain student-centeredness in HEIs (Tvalchrelidze &amp; Alkesidze, 2019). The paper sheds light on the significance of making the classroom environment student-centered, as it can boost and maintain the quality of education for all students (Harris, Spina, Ehrich &amp; Smeed, 2013; Vavrus, Thomas, Bartlett, 2011). The primary objective of this paper is to identify teachers’ perceptions of student-centered learning, along with the current instructional practices and challenges in the case of Higher Education Institutions in Georgia. Hence, it examines the level of integration of studentcentered strategies in the classrooms. For this reason, the quantitative paradigm was applied, as the methodology for the research. The research was carried out among lecturers from three different universities. The results depict that there is still a gap between the practical application of the student-centered learning methods and the perception of the concept, which can have an impact on ensuring quality education. Based on the gained data, it could be seen that less than 40% of lecturers from three different universities fully integrate student-centered learning methods. Furthermore, the research reveals some barriers that hinder the process of promoting the student-centered learning environment. Consequently, based on the findings the conclusions and recommendations were made. To deal with the hindering factors that were identified through this research, it is vital to modify and enhance institutionallevel approaches.
Intelligent Motion Planning for a Cost-effective Object Follower Mobile Robotic System with Obstacle Avoidance

There are few industries which use manually controlled robots for carrying material and this cannot be used all the time in all the places. So, it is very tranquil to have robots which can follow a specific human by following the unique coloured object held by that person. So, we propose a robotic system which uses robot vision and deep learning to get the required linear and angular velocities which are ν and ω, respectively. Which in turn makes the robot to avoid obstacles when following the unique coloured object held by the human. The novel methodology that we are proposing is accurate in detecting the position of the unique coloured object in any kind of lighting and tells us the horizontal pixel value where the robot is present and also tells if the object is close to or far from the robot. Moreover, the artificial neural networks that we have used in this problem gave us a meagre error in linear and angular velocity prediction and the PI controller which was used to control the linear and angular velocities, which in turn controls the position of the robot gave us impressive results and this methodology outperforms all other methodologies.
Las tutorías de acompañamiento durante el período de excepcionalidad: resultados en la carrera de Educación Inicial de la UMET

In the present work, elements of extraordinary importance are addressed regarding the accompaniment tutorials at the Metropolitan University of Ecuador under exceptional conditions. A pedagogical model of this activity is provided. The objective of this work is to propose a pedagogical model of the work of the accompaniment tutor in the current university, based on the experiences of the work of the tutors in the conditions of virtuality in the Initial Education career.
PENGEMBANGAN E-HANDOUT MESIN BUBUT KELAS XI DI SMK NEGERI 2 BITUNG

DEVELOPMENT OF CLASS XI LATHE E-HANDOUT&#x0D; IN SMK NEGERI 2 BITUNG&#x0D; &#x0D; By:&#x0D; RONALDO KRESMITO PITOY&#x0D; 14212084&#x0D; &#x0D; Supervisor :&#x0D; &#x0D; Dr. H. Dj. Liow, ST, M.Eng&#x0D; Ir. D. J. I. Manongko, M.Eng&#x0D; &#x0D; &#x0D; ABSTRACT&#x0D; This research is motivated by the limited or incomplete handouts in school in terms of material explanation and the number of handouts, the lack of handouts available in schools causes students to be unable to learn independently. The purpose of this research is to produce lathe handout products for class XI. This research is a development research (Research and Development) using the ADDIE (Branch 2009) research model, namely (A) analysis, (D) esign, (D) development, (I) implementation, and (E) valuation. The sample taken was 5 people for the small group test. The data analysis technique was carried out descriptively. Students are given a questionnaire to see student responses to the lathe e-handout, the student responses are more in the 4.5 range and are in very good qualifications. Based on the results of the study, it can be concluded that the e-handout product for class XI has been produced with the appropriate qualifications for use.&#x0D; &#x0D; Keywords: E-Handout, Research and Development, Lathe.
Natural Language Interfaces to Databases for English vs. Hindi: The Research Gap

Accessing a database requires the knowledge of Structured Query Language (SQL). It is not easy for end users to learn SQL. A Natural Language Interface to Database (NLIDB) allows the end users to access databases in a natural language. Some NLIDB systems have been developed for Hindi. But there exists the research gap in the development of those systems as compared to the systems developed for English. Very limited research has been done to develop NLIDB systems for Hindi as compared to English. This paper analyses the systems developed for both these languages. It compares the existing systems and explores the challenges to NLIDB development for Indian languages including Hindi. The paper discusses the future research directions to fulfill the research gap in the development of NLIDB systems for Hindi and other Indian languages.
An Analysis of Cybersecurity in Dutch Annual Reports of Listed Companies

In this paper we study the disclosure of cybersecurity information in annual reports, such as cybersecurity measures and cyber incidents, from a financial law and economics perspective. We start our discussion with an analysis of the requirements in financial law to disclose cybersecurity information in annual reports. Hereafter, we discuss the incentives for the board regarding disclosing cybersecurity related information and its effect on stakeholders and shareholders. We draft hypotheses regarding the actual disclosure of cybersecurity information and propose a research design of an exploring empirical study. The results of our study show that although there is no strict legal obligation to do so, 87% of the companies mention cybersecurity or similar words in their annual report in 2018. However, only 4 out of 75 companies disclosed more than six specific cybersecurity measures, while openness would generate the highest surplus for society from a social welfare perspective. Some major Dutch banks and employment agencies did not disclose any specific information with regard to their cybersecurity strategy, while those companies are highly vulnerable for cybersecurity incidents. This hampers the protection of creditors, investors and other stakeholders. Our analysis aims to propel the debate on stimulation of self-regulation or possible obligations in financial law concerning cybersecurity in annual reports.