Reviewerly/exHarmony huggingface dataset:
On the optimality of the Kitanidis filter for state estimation rejecting unknown inputs

As a natural extension of the Kalman filter to systems subject to arbitrary unknown inputs, the Kitanidis filter has been designed by one-step minimization of the trace of the state estimation error covariance matrix. In this technical communiqué, it is shown that the Kitanidis filter is also optimal for the whole gain sequence in the sense of matrix positive definiteness, which notably implies that the Kitanidis filter minimizes not only the trace criterion, but also the matrix spectral norm criterion.
HUMAN IDENTIFICATION USING HISTOGRAM OF ORIENTED GRADIENTS (HOG) AND NON-MAXIMUM SUPPRESSION (NMS) FOR ATM VIDEO SURVEILLANCE

Today video surveillance is the scorching topic in the research field of Computer Vision.Around 400 million surveillance cameras are used in various sectors which merely act as blind and record videos for postincident analysis.With the increase in crimes around the world, video surveillance plays a key role in identifying anomaly activities in a day to day application.One such application is a robbery in Automated Teller Machine (ATM).Identifying and tracking unlawful human activities is a challenging task in the ATM video surveillance system.Thus, an effective Human detection method using computer vision and image processing is proposed to create phenomenal results.The proposed approach, incorporate the most acclaimed Histogram of Oriented Gradient (HOG)-Support Vector Machine (SVM) with a combination of Adaptive Background Generation Model and Non-Maximum Suppression (NMS) algorithm to detect human with appropriate results in a video sequence.The experimentation result of the proposed method is applied on ATM Video Surveillance, real-time dataset.The performance analysis is evaluated by considering the average value of metrics such as the number of an input frames, ground truth elements and frames with human identified which acquired 97% of accuracy.
Implementation of Wireless Sensor Network in Earthquake Warning Simulation Using SW-420 Sensor

The wireless sensor network is a network consisting of sensor devices that detect nearby symptoms and then send information about the obtained results. Earthquakes are natural phenomena that can come at any time. So we need a tool that works automatically to give a warning as soon as possible when a WSN-based earthquake occurs to anticipate community rescue and reduce the number of casualties. This earthquake simulation alert will provide two notifications. Visual notifications displayed on the LCD and from the web. The sound notification issued by the buzzer will be different depending on the vibration received by the SW-420 sensor. Parameter earthquake used is MMI (modified mercalli intensity) using a visual assessment, international earthquake parameters. SIG (earthquake intensity scale) which already has a PGA (Peak Ground Acceleration) unit and includes MMI in it which is made by BMKG. After an excessive vibration is detected and it exceeds a predetermined limit, the MCU node will send an analog signal to the buzzer to provide a notification that has been set. For each appear notification, it aims to direct the public as soon as possible to assembly point that has been set in each building. Each detected vibration will be stored in WEB database. The vibration results detected by the sensor are a value of 0 (low) and 1 (high). These results will be sampled and produce an output in the form of Earthquake Intensity Scale.
A Method to Prevent SQL Injection Attack using an Improved Parameterized Stored Procedure

Structured Query Language (SQL) injection is one of the critical threats to database security.The effects of SQL injection attacks cause the data contained in the database to be at risk of being exploited by irresponsible parties, compromising data integrity, disrupting server operations and in return affecting the organization's image.Although SQL injection is an attack performed at the application level, SQL injection prevention requires security controls at all levels, namely application level, database level and network level.The absence of SQL injection prevention measures at the application level makes the database vulnerable to attack.Reviews indicate that the current approaches still not sufficient in addressing these three issues, which are i) improper use of dynamic SQL, ii) lack of input validation process and iii) inconsistent error handling.Currently, program and database code security is based solely on basic security measures that are focused at the network level such as network firewalls, database access control and web server request filtering.Unfortunately, these measures are still inadequate and not sufficient to safe guard the program code and databases from the attack.To overcome this shortcoming as addressed by these three issues, a new comprehensive method is proposed using an improved parameterized stored procedure to enhance database security.Experimental results prove that the proposed method is able to prevent SQL injection from occurring and able to shorten the processing time when compared with existing methods, hence able to improve database security.
Convolutional Neural Network Approach to Predict Tumor Samples Using Gene Expression Data

Cancer is threatening millions of people each year and its early diagnosis is still a challenging task.Early diagnosis is one of the major ways to tackle the disease and lower the mortality rate.Advancements in deep learning approaches and the availability of biological data offer applications that can facilitate the diagnosis and characterization of cancer.Here, we aimed to provide a new perspective of cancer diagnosis using a deep learning approach on gene expression data.In this study, RNA-Seq data of approximately 30 different types of cancer patients the Cancer Genome Atlas (TCGA) study, and normal tissue RNA-Seq data from GTEx were used.The input data for the training was transformed to RGB format and the training was carried out with a Convolutional Neural Network (CNN).The trained algorithm is able to predict cancer with 97% accuracy, using gene expression data.In conclusion, our study shows that the deep learning approach and biological data have a huge potential in the diagnosis and identification of tumor samples.
Software quality measures and their relationship with the states of the software system alpha

Semat (Software Engineering Method and Theory) is an initiative developed for refounding software engineering by defining a theoretical basis, best practices, and a set of widely-agreed elements. ISO/IEC 25000 (System and Software Quality Requirements and Evaluation-SQuaRE) is an international standard, that evaluates software product quality. ISO 25000 replaces ISO/IEC 9126 and ISO/IEC 14598 standards. Some authors describe the relationship between quality measures of ISO/IEC 9126 and the requirements and software system states of the Semat Essence kernel. Also, they redefine the completion criteria of the activity spaces related to these alphas. Other proposals include a schematic relationship between ISO/ IEC 9126 quality measures and the alpha states, but they avoid their correlation and some criteria for evaluating the product quality. Other proposals based on the ISO/IEC 25000 comprise other frameworks than Semat. Our proposal is focused on the selecting the appropriate measures of the software system states to structure the relationships between them, validate them by using a case study, and develop a model for product quality measurement. The results are promising since we can use them to establish a coherent and structural model for evaluating the software system alpha's health and progress.
Semiautomatic Generation of Code Ontology Using ifcOWL in Compliance Checking

Code compliance checking is a very important step in engineering construction, but most of code compliance checking relies on manual review at present. With the development of semantic web technology, ontology can be used to represent code information and check the code automatically. However, code ontology is established manually by researchers who have sufficient domain knowledge, in which it is easy to cause poor hierarchical structure of classes. It is also possible for code ontology not being suitable for compliance check. This paper proposes a semiautomatic construction method of railway code ontology based on ifcOWL. The railway code ontology is developed by converting ifcOWL which extends semantic information of railway code. This method can ensure the completeness of the hierarchical relationship of the classes in code ontology with good scalability, which makes use of taxonomy in ifcOWL. The establishment of ontology is divided into two processes with low coupling, namely, extension and conversion, which reduces the domain knowledge requirements of the researchers. Finally, a practical specification is selected to generate a code ontology that achieves some clauses checking.
An Analysis on Clock Speeds in Raspberry Pi Pico and Arduino Uno Microcontrollers

Choosing an application-centric microcontroller development board undisputedly increases the efficiency of the system.It impedes on-field failures and improves the quality of research.This paper analyses the Clock speeds of Arduino Uno and Raspberry Pi Pico microcontrollers to test their computation speeds using Mandelbrot Set, a familiar self-recurring fractal object.Arduino Uno is one of the popularly-used microcontrollers in the field of development.Pi Pico is the first and latest Microcontroller from Raspberry Pi family.Though the boards are economic, the latter tends to be very powerful.Hence these microcontrollers are chosen for analysis.The Mandelbrot Set is formed by the microcontrollers on an OLED display using Escape Time (ET) Algorithm.ET Algorithm takes a position (x, y) and recursively calculates the pixels that have to be turned on to render the Mandelbrot set on the display.Initially the boards are tested at their standard clock speeds.Further they are decelerated to under-rated levels to find the deviation in the rate of change of computation with the raise in their core frequencies.The Arduino Uno requires complex on-board hardware modifications with an intensive monitoring setup to work at overclocked frequencies.Hence this board is not tested at overdriven clock speeds.But Pi Pico effortlessly adjusts its core frequency to work at desired computation speeds using its phase-controlled loop.With this parameter, benchmarks and results, one of the two boards is regarded ideal for applications requiring cumulative calculations.
The Effect of Problem Based Learning Model on Creative and Critical Thinking Skills in Static Fluid Topics

Creative and critical thinking skills are one of the demands of new skills needed by students in the current era. One of the learning models that can sharpen creative and critical thinking skills is Problem based learning (PBL). Heretofore, research related to creative and critical thinking skills with PBL in understanding static fluid material is still minimal. Therefore, this research explored it. This study aimed to analyze the effect of PBL on students' creative and critical thinking skills. This type of research is experimental with a total of 58 students, both experimental class and control class in 10th-grade science class Christian Senior High School YPKPM Ambon. The research procedure in the form of creative and critical thinking skills tests carried out during the research process and data analysis used was the independent sample t-test. The results showed that the average value of the experimental class students' learning achievement related to students' creative and critical thinking skills was higher than the conventional class. This implies that PBL facilitates in improving students' creative and critical thinking skills on static fluid.
LexSubCon: Integrating Knowledge from Lexical Resources into Contextual Embeddings for Lexical Substitution

Lexical substitution is the task of generating meaningful substitutes for a word in a given textual context.Contextual word embedding models have achieved state-of-the-art results in the lexical substitution task by relying on contextual information extracted from the replaced word within the sentence.However, such models do not take into account structured knowledge that exists in external lexical databases.We introduce LexSubCon, an end-to-end lexical substitution framework based on contextual embedding models that can identify highly-accurate substitute candidates.This is achieved by combining contextual information with knowledge from structured lexical resources.Our approach involves: (i) introducing a novel mix-up embedding strategy to the target word's embedding through linearly interpolating the pair of the target input embedding and the average embedding of its probable synonyms; (ii) considering the similarity of the sentence-definition embeddings of the target word and its proposed candidates; and, (iii) calculating the effect of each substitution on the semantics of the sentence through a fine-tuned sentence similarity model.Our experiments show that LexSubCon outperforms previous state-of-the-art methods by at least 2% over all the official lexical substitution metrics on LS07 and CoInCo benchmark datasets that are widely used for lexical substitution tasks.
Chromosomal Aberration for Diagnosis and Prognosis of Acute Myeloid Leukemia Iraqi Patients

Background: Acute myeloid leukemia (AML) is a hematopoietic disorder in which there are too many immature blood-forming cells accumulating in the bone marrow and interfering with the production of normal blood cells. It has long been recognized that AML is a clinically heterogeneous disease characterized by a multitude of chromosomal abnormalities and gene mutations, which translate to marked differences in responses and survival following chemotherapy. This study aimed to clarify the chromosomal aberrations in early diagnosed and relapsed cases of AML. Materials and methods: Chromosomal changes were studied in thirty Iraqi patient samples diagnosed with acute myeloid leukemia were divided into 9 newly diagnosed and 13 received chemotherapy who were incomplete remission and 8 relapsed subjects. Results: Analysis of all chromosomal aberrations showed complex karyotype for most cells of relapsed AML patients compared with newly diagnosed patients. Conclusions: Chromosomal abnormalities are linked to AML development and high complexity of karyotyping for relapsed group.
Natural synthesis of productive forms from structured descriptions of sign language

Natural animation of sign language directly from linguistic descriptions continues to be a challenge especially in cases where the forms involved are more productive, such as geometric depictions. Prior work laid the foundation for natural sign language synthesis with the Paula animation system directly from AZee linguistic descriptions. This paper considers more elaborate discourse, composed of several clauses linked together by the overall meaning and involving largely productive signing. We make the case that one of the keys to natural animation of such discourse lies also in the segments between the typically annotated signs, in other words on the segments traditionally termed “transitions”. By studying an example discourse video and the corresponding motion capture, we progressively build an efficient linguistic description of it and specify how to animate it naturally.
Physical Modeling of the Ancient Greek Wind Musical Instrument Aulos: A Double-Reed Exciter Linked to an Acoustic Resonator

We present a simulation method for the auralization of the ancient Greek double-reed wind instrument Aulos.The implementation is based on Digital Signal Processing and physical modeling techniques for the instrument's two parts: the excitation mechanism and the acoustic resonator with toneholes.Single-reeded instruments are in-depth studied firstly because their excitation mechanism is the one used in a great amount of modern wind-reed instruments and secondly because the physics governing the phenomena is less complicated than the double-reeded instruments.We here provide a detailed model of a system comprised of a double-reed linked to an acoustic resonator with toneholes to sonify Aulos.We validate our results by comparing our method's synthesized signal with recordings from a replica of Aulos of Poseidonia built in our lab.The comparison showed that the fundamental frequencies and the first three odd harmonics of the signals differ 6, 5, 3, and 2 cents on average, respectively, which is below the Just Noticeable Difference threshold.
Steganography using dual tree complex wavelet transform with LSB indicator technique

Image steganography is undoubtedly significant in the branch of multimedia communication security.The undetectability and large payload capacity are two of the important characteristics of any form of steganography.In this paper, the level of image security is improved by combining the steganography and cryptography techniques in order to produce the secured image.The proposed method depends on using LSBs as an indicator for hiding encrypted bits in dual tree complex wavelet coefficient DT-CWT.The cover image is split into non-overlapping blocks of size (3*3).After that, a Key is produced by extracting the center pixel (pc) from each block to encrypt each character in the secret text.The cover image is converted using DT-CWT, then the produced key is used to determine the starting pixel in each block for hiding and the direction of hiding (clockwise or anticlockwise).The proposed method is applied on many images with different embedding rate, and many metrics are used to evaluate the performance of the proposed method, namely: Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), correlation factor (CF) and Structural Similarity Index Measure (SSIM).It achieves in average 52.225 dB of PSNR, 0.3215 of MSE, 0.9952 of SSIM and 0.9997 of CF with embedding rate 1.5.
The Effectiveness of Educational Games on Post-Pandemic Learning

Learning through interactive media gives additional value to the educational world because it enables learners to represent themselves. Game-based learning promotes learners’ creativity, critical thinking and cognitive skills related to technology use. Previous research discovered that game-based learning has a positive effect on learners. Therefore, in this research, an applied study was conducted on the use of the E-CrowdWar educational game with high school students. The purpose of this study was to determine the effectiveness of using games in learning to improve student learning outcomes. The study was conducted with 100 high school students in Blitar and 100 in Kediri. E-CrowdWar was used during the classroom activities along with in-class learning. An independent sample t-test was used to measure the effectiveness of game-based learning. The integration of games into online learning had a significantly positive effect on student learning outcomes. The pre-test results showed that the average student learning outcome score in both cities was the same, namely 65 points. After implementing game-based learning, student learning outcomes in Kediri increased to 90.74 points and in Blitar to 86.95 points. The study discovered that game-based learning through E-CrowdWar was effective in promoting the students’ academic outcomes, although there were differences in the mean score. Based on the results, game-based learning provides tremendous improvements in learning outcomes and so should be applied, especially in the economic field.&#x0D; Keywords: Gamification, Education, Learning Result
Waking Up In the Morning (WUIM): A Smart Learning Environment for Students with Learning Difficulties

Effectiveness, efficiency, scalability, autonomy, engagement, flexibility, adaptiveness, personalization, conversationality, reflectiveness, innovation, and self-organization are some of the fundamental features of smart environments. Smart environments are considered a good learning practice for formal and informal education; however, it is important to point out the pedagogical approaches on which they are based. Smart learning environments (SLEs) underline the flexibility of eclectic pedagogy that places students at the center of any educational process and takes into account the diversity in classrooms. Thus, SLEs incorporate pedagogical principles derived from (1) traditional learning theories, e.g., behaviorism and constructivism, (2) contemporary pedagogical philosophy, e.g., differentiated teaching and universal design for learning, (3) theories that provide specific instructions for educational design, e.g., cognitive theory of multimedia learning and gamification of learning. The innovative concept of transmedia learning is an eclectic pedagogical approach, which in addition to learning principles, blends all available media so far. WUIM is a transmedia program for training independent living skills aimed primarily at children with learning disabilities, which emerged from the composition of pedagogical theories, traditional educational materials and cutting-edge technologies such as augmented and virtual reality, and art-based production methodologies. This paper outlines the development of WUIM, from the prototyping presented at the 4th International Conference in Creative Writing (2019) to the Alpha and Beta stages, including user and expert evaluations.
An Optimised Flow for Futures: From Theory to Practice

A future is an entity representing the result of an ongoing computation. A synchronisation with a "get" operation blocks the caller until the computation is over, to return the corresponding value. When a computation in charge of fulfilling a future delegates part of its processing to another task, mainstream languages return nested futures, and several "get" operations are needed to retrieve the computed value (we call such futures "control-flow futures"). Several approaches were proposed to tackle this issues: the "forward" construct, that allows the programmer to make delegation explicit and avoid nested futures, and "data-flow explicit futures" which natively collapse nested futures into plain futures. This paper supports the claim that data-flow explicit futures form a powerful set of language primitives, on top of which other approaches can be built. We prove the equivalence, in the context of data-flow explicit futures, between the "forward" construct and classical "return" from functions. The proof relies on a branching bisimulation between a program using "forward" and its "return" counterpart. This result allows language designers to consider "forward" as an optimisation directive rather than as a language primitive. Following the principles of the Godot system, we provide a library implementation of control-flow futures, based on data-flow explicit futures implemented in the compiler. This small library supports the claim that the implementation of classical futures based on data-flow ones is easier than the opposite. Our benchmarks show the viability of the approach from a performance point of view.
Providing the minds of the out-of-the-box digitalization as the basic component of the information culture of the teacher

Article is devoted to questions of formation and development of the higher vocational school of the information competence defined as a basic component of information culture. The author of the provisions which account in student teaching will promote realization of an effective technique of system application of information and communication technologies and achievement of the objectives of high school education locate.