Reviewerly/exHarmony huggingface dataset:
PERAMALAN INDEKS HARGA SAHAM MENGGUNAKAN ENSEMBLE EMPIRICAL MODE DECOMPOSITION (EEMD)

Stock price fluctuations make investors tend to hesitate to invest in stock markets because of an uncertain situation in the future. One method that can solve these problems is to use forecasting about the stock prices in the future. Generally, the huge size of data non linear and non stationary, and it is difficult to be interpreted in concrete. This problem can be solved by performing the decomposition process. One of decomposition method in time series data is Ensemble Empirical Mode Decomposition (EEMD). EEMD is process decomposition data into several Intrinsic Mode Function (IMF) and the IMF residue. In this research, this concept applied to data Stock Price Index in Property, Real Estate, and Construction from July 1, 2019 to July 30, 2020 as many as 272 data. Based on the results of data processing, as many as 6 IMF and IMF remaining were used as IMF forecasting and the IMF remaining in the future. The forecast was performed by choosing the best model of each IMF component and IMF remaining, used ARIMA and polynomial trend. Keywords: Time Series Data, Stock Price Index, EEMD, ARIMA, Polynomial Trend.
A Comparison of the Lehmann and GLM ROC Models

Recently, several regression methods have been developed to model the receiver operating characteristic curve (ROC), as a measure of accuracy for potential biomarker use in diagnostic testing and disease detection.In this paper, we investigate the Lehmann ROC regression model and compare it to more commonly used ROC regression methods that are found in the literature.The comparative performance of the methods are evaluated using simulated data from the normal, extreme value, and the Weibull distributions.Theory suggests that the Lehmann method should only work well when using the Weibull distribution.Our simulation results suggest that the performance of these methods is more complicated than the theory might suggest.The methods were demonstrated using data from a study concerning the clinical effectiveness of leukocyte elastase determination in the diagnosis of coronary artery disease (CAD).
THE DEVELOPMENT OF INTEGRATED THEMATIC TEXTBOOK WITH THEME MY IDEALS AND SUB-THEME ME AND MY IDEALS BASED ON CURRICULUM 2013

This study aimed to develop a textbook for fourth grade elementary school students. This research applied research-and-development model adapted from Borg &amp; Gall. The developmentinvolved the following steps (1) initial research and information gathering, (2) textbook planning, (3) product validation testing, (4) product revision, (5) product testing. The research data was obtained through documentation, interviews, questionnaires, validation sheets and learning achievement tests after a product trial had been carried out with 2 classes, namely the experimental class and the control class. The data were then analyzed using the t-test technique and the relative effectiveness test. The results of the independent t-test obtained t value -5.551 and showed significant differencewith p 0.000. The significance value was smaller than Î± value (0.05). This means that there is an average difference between the control class and the experimental class. The calculation of the relative effectiveness obtained a value of 57.24%, so it can be concluded that the textbook developed have a relative effectiveness level of 57.24% compared to the previous textbook.
Software HIDROKSI Development to Detect and Reduce Misconceptions Using Conceptual Change Text Strategy on Salt Hydrolysis

This research aims to determine the feasibility of software HIDROKSI to detect and reduce students' misconceptions using a conceptual change text strategy on salt hydrolysis. This research used the Research &amp; Development (R&amp;D) method with 3rd grade SMAN 1 Krian’s student as a subject. The instruments used are student response questionnaires and student activity observations. Software HIDROKSI was developed using the Adobe Flash CS6 Action Script 3.0. The results analyzed using the quantitative descriptive method are as follows: (1) Software HIDROKSI isvalid with an average percentage of content validation is 86.67% and construct validation is 86.22% (2) The practicability of software HIDROKSI is very practical with an average percentage of student response questionnaire results is 96.61% (3) The effectiveness of software HIDROKSI in detecting and reducing student’s misconceptions is very effective with an average percentage of students' shift in conceptions from misconceptions to knowing concepts is 86.34%.
AN EARTHQUAKE MODEL IN DAVAO REGION USING SYMBOLIC REGRESSION VIA GENETIC PROGRAMMING: A TOPOLOGICAL DYNAMICAL SYSTEM APROACH

The study proposes a new approach to genetic programming (GP) based on symbolic regression (SR) on a statistical search which is a topological dynamical system identification technique that uses a stochastic process for finding the earthquake models from the space (phase or state space) and the law of evolution of such functions or models in a dynamical system. It is an evolutionary algorithm aimed to recapitulate a set of measures in an n- dimensional space, used to determine the relationship of measurable functions or model (sets of functions or distributions) and parameters simultaneously unlike in traditional regression analysis only the parameters are determined while the model is defined in advanced. Since earthquake occurrences cannot be predict, this study introduce an earthquake model of Davao Region.
A novel approach to improve Chat Bot accuracy using Natural Language Processing

Chat bots are finding increasing usage these days in applications ranging from simple automated FAQ’s to sophisticated e-commerce buying recommendations. The technology powering these bots has undergone tremendous improvements thanks to new age sciences such as Machine Learning, AI and Natural Language Processing. Although chat bots have come quite far in effectiveness and imitating real humans, there’s still lapses and areas where they can be improved in order to make them much more powerful and closer to human interaction. This is the main aim of the proposed work where one such limitation has been considered and attempt to address it by utilizing Natural Language Processing.
Design Of Remote Electronic Fire Monitoring System Based On K-Means Clustering Algorithm

In order to overcome the problem of poor real-time response and accuracy of remote electronic fire monitoring system, a remote electronic fire monitoring system based on K-means clustering algorithm is proposed and designed. The hardware of the system includes communication module, smoke sensor, temperature sensor and image collector. In the design of system software, firstly, the database is constructed, the information collected by system hardware is collected into the database, the fire characteristics are extracted, and the smoke, temperature and image data in the database are clustered by K-means clustering algorithm. The fused fuzzy reasoning is carried out to determine whether the fire occurs or not, so as to realise remote electronic fire monitoring. The experimental results show that the response delay of the system is always under 1.5 μs, the response delay is short, the response accuracy is always above 95%, the monitoring accuracy is high, and it is practical.
Research and Design of Intelligent Teaching Mode Based on Artificial Intelligence Technology

The emergence of smart classroom represents the continuous pursuit of the traditional teaching method for the height under the blessing of modern technology. The integration and development of advanced technology is an important basis for classroom and teaching reform to improve the quality of teaching. Integrating AI technology into the teaching process and creating an efficient and intelligent classroom has become the future development trend. In practice, feedback analysis based on big data combined with artificial intelligence technology is an effective way to build a modern smart classroom, which can gradually achieve the classroom learning analysis goal of cooperation between computer and people, range and optimization.
Tradução multinível de poesia e a solução de um problema situado e mal definido

The notions of “multilevel”, “level of description and organization” are quite familiar for the studies of complex systems. Examples include physico-chemical, biological, computational, socio-economic, historical, and cultural systems. Poems are complex phenomena and can be described as multilevel hierarchical systems. Different levels of description of a poem correspond to different sets of components, structures and processes (e.g., context, lexicon, syntax, prosody, rhythm, typography) that asymmetrically restrict each others. We suggest the notion of “multilevel translation” to characterize an operation whose focus is a solution of a situated problem. The operation involves selection and re-creation of a hierarchical, multilevel system of constraints. This perspective allows us to approach the translation of a poem as the solution of a multilevel, situated and ill-defined problem. We describe the steps of this operation, and we exemplify it by the translation of the poem “The Expiration”, by Augusto de Campos.
Nekray

In recent years, the demand of kiosk devices has increased significantly for relaying information in organizations, institutions, or any other service centers. They have become a better alternative for traditional human assistance or reception desks. However, there are no dynamic operating systems or user interfaces available for kiosk devices. This paper represents a development of an operating system for kiosk devices called ‘Nekray', which was built on Linux Kernel environment. It was designed to be dynamic, fast, user-friendly, and user interactive. The developed operating system avails the option to change the data of its features as per requirement. It also supports plug and play feature and can be installed in any low-cost hardware board. Furthermore, built-in AI is also a part of the developed system that performs its features through image processing. The system maintains the privacy and interactive transition of data to its users on kiosk devices.
PENINGKATAN KETERAMPILAN MEMBACA PEMAHAMAN DENGAN METODE SCRAMBLE PADA SISWA KELAS IV SD NEGERI NUSA HARAPAN PERMAI MAKASSAR

Type of this research was Classroom Ation Research which based on several steps, such as planning, action implementation observation, evaluation, and reflection. Subject of the research were IV class students SD Nusa Harapan Permai Makassar as many as 23 students. Data collection used observation and the next test analyzed by descriptive method. The result of the research showed that the application of Scramble Method for Increasing of Comprehension Reading Skill students could improve learnig result of students in IV class SD Nusa Harapan Permai Makassar. In this case based on the improvement average value of learning result from 69.13% in cycle I became 78.26% in cycle II and the increase of average value is eleven percent. So, this research is considered successful.
Novel Maintainability Model for Object-Oriented Software System with Oom Metrics

The maintainability parameter plays prominent role in improvement of quality in any type of software system. In Object-Oriented software system, Unified Modeling Language (UML) based class diagrams utilized in effective way to estimate the maintainability of the system..The researchers measured the Maintainability parameter model by using Understandability and Modifiability factors. In the proposed model development the utilized Understandability and modifiability metrics are developed based on the class inheritance which is the major property of the Object Oriented  software systems. The main aim of this research is to estimate more improved maintainability model based on the OOM metric values of understandability and modifiability factors. The resultant maintainability estimation model mostly useful for the future researchers to improve the Object Oriented software quality in better and identifiable manner.
Using Photographs to Develop Writing Ability of the First Grade Students of SMA Negeri 10 Makassar

This thesis aims at finding out whether or not the use of photographs can develop the writing ability of the first grade students of SMA Negeri I0 Makassar.The method applied in this research was pre-experimental with one group pretest and posttest. The research population was the first grade students of SMAN I0 Makassar in academic 2009/2010. The sample was the first grade students that consisted of 32 students were taken using cluster sampling technique. The data here analyzed using t- test.The result of this research showed that the first grade students of SMAN I0 Makassar, in pretest and posttest were different significantly. It was proven by value of the  t-test 6.47 which was greater than the value of t-table 2.042 with the level of significance (p) 0.05 and degree of freedom (n-1)= 31.  It can be concluded that using photographs can develop the writing ability of the students Key words: Photographs, Writing Ability
Accelerating Smith Waterman Algorithm for Optimizing Gene Sequences Alignment Using Parallel Residue Number System Arithmetic Based Architecture

The understanding of evolutionary relationships among biological entities enabled computer scientist’s researchers to developing various arithmetic number bases systems with remarkable genetic sequence alignment technique, where weaker analyses in homologous sequence are acceleratory detected and implemented. Using SWA for continuous improvement in the sensitivity of genes and proteins regulatory sequence alignment, three moduli sets are presented for DNA sequence alignment with residue of each modulus independently of each other, concurrently by parallel ALUs without carry propagation among them. Finally, we developed a reconfigurable RNS-SWA based arithmetic architecture with design support tool characterized in addition (ADD), subtraction (SUB), multiplication (MUX) using RNS conversion technique properties on a multi ALU system which provide structural VHDL simulation descriptions summary for the RNS-SWA Based DNA sequences; improving low Power, high speed linear processing acceleration required in genetic sequences computing. Our proposed design work when implemented in PLD-RNS-SWA based high profile acceleration comparator, exhibits a greater significant percentage speed when compare with the non RNS state of art profiler in real time processing design supporting a very high speed integrated Circuits.
Early History of Archaeology Graphs

The earliest archaeological spindle graph was published in 1883 by natural historian and avocational archaeologist Charles C. Abbott. Evidence that he obtained the idea from paleontology, which first published spindle graphs in the 1830s and 1840s, is circumstantial at best, and differences in graph styles weigh against such borrowing. Several spindle graphs published in the 1890s and early 1900s by archaeologist William Henry Holmes either depict his views on inevitable progressive evolution—a theory rapidly falling from anthropological favor—or were so speculative as to likely have had little influence on the discipline. During the first couple decades of the twentieth century, physicist/geographer/anthropologist Franz Boas (often referred to as the father of anthropology) published numerous line graphs of quantitative data. He influenced archaeologists Leslie Spier and Manual Gamio who used line graphs to display temporally varying frequencies of artifacts. About the same time, the wife and husband team of Madeleine Kidder and Alfred V. Kidder published several line graphs of relative frequencies of pottery types against stratigraphic provenience, seemingly largely as a result of Madeleine’s influence because Alfred never again published such a graph and instead favored phyletic seriation graphs of a type reminiscent of Sir William Flinders Petrie’s sequence dating graphs from the turn of the century.
DANCE: Enhancing saliency maps using decoys

Saliency methods can make deep neural network predictions more interpretable by identifying a set of critical features in an input sample, such as pixels that contribute most strongly to a prediction made by an image classifier. Unfortunately, recent evidence suggests that many saliency methods poorly perform, especially in situations where gradients are saturated, inputs contain adversarial perturbations, or predictions rely upon inter-feature dependence. To address these issues, we propose a framework that improves the robustness of saliency methods by following a two-step procedure. First, we introduce a perturbation mechanism that subtly varies the input sample without changing its intermediate representations. Using this approach, we can gather a corpus of perturbed data samples while ensuring that the perturbed and original input samples follow the same distribution. Second, we compute saliency maps for the perturbed samples and propose a new method to aggregate saliency maps. With this design, we offset the gradient saturation influence upon interpretation. From a theoretical perspective, we show the aggregated saliency map could not only capture inter-feature dependence but, more importantly, robustify interpretation against previously described adversarial perturbation methods. Following our theoretical analysis, we present experimental results suggesting that, both qualitatively and quantitatively, our saliency method outperforms existing methods.
Focusing on Software Development Outcomes Instead of Outputs

Imagine landscaping your yard is your hobby, and you would like to have a small storage building to keep all of your garden and yard tools organized and stored. You want to be the envy of your neighbors, so you take the opportunity to create something that will stand out. You spend an hour or two drawing something that demonstrates the style of the garden shed and its dimensions. Maybe something like the plans shown in Figure 1-1.
Let’s Install Python!

In this chapter, we will take a deeper look into what programming is and how it is used to control various gadgets. We will also look at installing Python in our system. Let us get started!
METHODOLOGICAL APPARATUS FOR FORMING STUDENTS' FAMILY AND MORAL VALUES

The article describes that the methodological apparatus for the formation of family and moral values of students provides the main categories of methodology, methodological approaches to the formation of family and moral values. Theoretical analysis defines four groups of representations of scientific methodology in the works of scientists. The main categories of scientific methodology are analyzed: correlation of the concepts «approach» and «principle». Methodological approaches to the formation of students' family and moral values: axiological, socio-humanistic, system-structural, activity-based, cultural approaches. Analyzing the functional activity of each methodological approach, the attributes of the formation of family and moral values will be analyzed. The work was carried out to diagnose the basics of the methodological apparatus for the formation of family and moral values of students. On the experimental site of students, the method m was carried out. Rokicha «Definition of value orientation», analyzed the percentage and quantitative indicators of research results.
Python and Files

In the previous chapter, we learned how to create real-world objects in Python using classes. We learned how everything was an object in Python. Then, we learned how to create classes in Python and use those classes to create similar objects without writing too many lines of code.
Tamper Proof Embedded Hardware for Secured Applications

An embedded hardware designed for critical application like defence, health and industry application requires to be secured. The system may be subjected to masquerading, eavesdropping and denial of service. This can be done in several ways. One of the common modes is by tampering the hardware through physical access or memory corruption through external attack. In order to mitigate this, it is necessary to design a tamper proof hardware. Whereby, in case of intrusion the same can be communicated to the owner and preventive actions can be taken. This can be done by adding sensors to the box to monitor its physical status and then the status can further be transferred through IOT
GRU, AdaGrad, RMSprop, Adam Implementation of GRU and Adam Optimization Method For Stock Price Prediction

In terms of their potential, stocks are one of the most profitable investment options today. If done well and right, stocks can be a very profitable investment. However, volatile stock prices make it necessary to predict stock prices to make a profit. Gated Recurrent Unit (GRU) is a method for predicting time series data such as stock prices. The Optimization method is needed to get accurate prediction results. The weight renewal optimization method such as Adam is implemented to obtain the best weight in the Gated Recurrent Unit (GRU) and to find out the best loss function value generated by the Adam optimization method. The GRU-Adam implementation is carried out on two stock data, namely ICBP and YULE. The results of this research are that the ICBP data yields the respective loss function values, namely train loss 0.0016 and validation loss 0.0007. Whereas the YULE data resulted in a train loss value of 0.0051 and a validation loss of 0.0031. The MAPE generated in the ICBP stock data is 0.97%. While the YULE data is 3.00%.
Decentralized Riemannian Gradient Descent on the Stiefel Manifold

We consider a distributed non-convex optimization where a network of agents aims at minimizing a global function over the Stiefel manifold. The global function is represented as a finite sum of smooth local functions, where each local function is associated with one agent and agents communicate with each other over an undirected connected graph. The problem is non-convex as local functions are possibly non-convex (but smooth) and the Steifel manifold is a non-convex set. We present a decentralized Riemannian stochastic gradient method (DRSGD) with the convergence rate of $\mathcal{O}(1/\sqrt{K})$ to a stationary point. To have exact convergence with constant stepsize, we also propose a decentralized Riemannian gradient tracking algorithm (DRGTA) with the convergence rate of $\mathcal{O}(1/K)$ to a stationary point. We use multi-step consensus to preserve the iteration in the local (consensus) region. DRGTA is the first decentralized algorithm with exact convergence for distributed optimization on Stiefel manifold.
The Prevention of Electronic Crimes Act 2016 And Shrinking Space for Online Expression in Pakistan

Freedom of expression is one of the most cherished fundamental rights. It also imperative in all fields including cyber or digital space. The Prevention of Electronic Crime Act (PECA-2016) was enacted in 2016 to regulate cyber or digital space in the country. This study critically comprehends PECA-2016 with regard to online expression in Pakistan.Doctrinal as well as non-doctrinal(socio-legal) research method are adopted in present study. Under nondoctrinal(socio-legal) methods, unstructured interviews with three legal experts were conducted. This study finds out that there are several provisions in the PECA-2016 which adversely affect online freedom of expression in the country. It is concluded that some of the provisions of the PECA-2016 should be improved or repealed to bring it in conformity with freedom of expression principles.