Reviewerly/exHarmony huggingface dataset:
Research on 3D Path Planning of Quadrotor Based on Improved A* Algorithm

Considering the complexity of the three-dimensional environment and the flexibility of the quadrotor aircraft, using the traditional A* algorithm for global path planning has the disadvantages of less search direction, more expanded nodes, and a longer planning path. Therefore, an improved A* algorithm is proposed, which is improved from two aspects. Firstly, a two-layer extended neighborhood strategy is proposed, which can increase the search direction and make better use of the flexibility of the aircraft. Secondly, the heuristic function is improved to make the heuristic function value closer to the actual planning path distance, which can reduce the expansion nodes and optimize the planning path. Finally, the path planning simulation of the improved A* algorithm is carried out and the results show that the path planned by the improved algorithm is shorter and the expanded nodes are fewer, which can guide the quadrotor to reach the destination better.
Making EMS fit for the future

Over the next few issues, the RCVS will provide more details of forthcoming changes to its policies on extramural studies. In this first article, RCVS director of education Linda Prescott-Clements sets out the case for reform and how the overall student experience should be improved by it.
Try Dam: Digital Checkers Game Application Based on Machine Learning

A traditional game like checker or dam is often played by people in the past during their free time.Despite their leisurely and compelling activities, the games stimulate the cognitive, social and emotional well-being of players, to plan the right strategy to win the game.However, moving along with the difference in time, traditional games that used to be often played by all sections of society are increasingly being marginalized by the younger generation.Due to the development of technology, the younger generation appears to be more inclined to play mobile games than traditional ones.The proposed solution to this problem is to create a traditional game in digital form; and this paper aims to develop a digital checkers game application using machine learning and to test the functionality and effectiveness of the game.The development of this digital checkers game applies agile model, combined with game design strategy.The Alpha-Beta Pruning algorithm will be used to produce a computer capable of playing checkers.Based on the game competition result, the player's winning rate decreases along with the chosen difficulty level.Once the difficulty level increase, players need to demonstrate their mastery to play against computer.The computer has gained increased information to defeat the opponent using various strategies using "alpha-beta pruning" technique.This digital checkers game is expected to increase awareness and passion among generation young towards the local traditional games.Expected game play experience from the application include entertainment and easy access especially using smart telephone device.
Penerapan project based learning untuk meningkatkan hasil belajar teks prosedur siswa SMP

Writing is the most advanced language skill. It must be honed frequently in order to become skilled in writing. This study used the Classroom Action Research (PTK) method. PTK was conducted in 2 cycles and each cycle consisted of planning, implementation, observation, and reflection activities. The sample in this study was class VII C SMPN 35 Bandar Lampung as many as 27 people. The results of the increase in grades and the number of students passing above KKM in the pre-cycle process were 13 students (48.1%) completed the learning, in cycle I 18 students (67%) completed the learning and cycle II as many as 24 students (89%) completed the learning. Keywords: PTK, PBL, Prosedur Text
Autonomous Robot Navigation Using Fuzzy Inference Based Dynamic Window Approach

The autonomous navigation of a mobile robot in an unknown environment depends on the robot’s ability to perceive and adapt to that environment. The dynamic window approach (DWA) is a local planning algorithm for obstacle avoidance that considers the motion dynamics of the robot while steering to avoid collisions. The DWA generates a window with all the velocities that are reachable in a time interval and then evaluates all the velocities with an objective function to select the best velocity. In this paper, a novel hybrid algorithm is proposed based on DWA, fuzzy inference system (FIS) and Kalman filter. The proposed work discusses the implementation of DWA algorithm along with FIS to tune the weights of the DWA objective function. Also, the algorithm is extended to incorporate a Kalman filter for state estimation of dynamic obstacles in the environment.
Qualitative and Artificial Intelligence-based Sentiment Analyses of Anti-LGBTI+ Hate Speech on Twitter in Turkey

The aim of this study was to evaluate hate speech in Turkish LGBTI+-related tweets during a one-month period of artificial intelligence-based sentiment analyses. Turkish tweets related to LGBTI+, were retrieved using Python library Tweepy and were evaluated by sentiment analysis. The researchers then performed a qualitative analysis of the most frequently liked and retweeted tweets (n = 556). Sentiment analysis revealed that 69.5% of tweets were negative, 23.3% were neutral, and 7.2% were positive. The qualitative analysis was grouped under seven themes: LGBTI+ Club; Terrorism and Terrorist Organization Membership; Perversion, Illness, Immorality; Presence in History; Religious References; Insults; and Humiliation. The results of this study show that anti-LGBTI+ hate speech in Turkey is significant in terms of both quality and quantity. As LGBTI+ individuals are at risk for excess mental distress and disorders, it is important to understand the risks and other factors that ameliorate stress and contribute to mental health in social media.
Some aspects of artificial personality architecture

This paper examines the possibility of artificial personality as a form of strong AI and as a model of the human psyche. It is argued that connectionism is not relevant for creating an artificial personality – brain is a hybrid system, which, in addition to self-learning circuits, contains algorithmic procedures. A hypothesis of the functional role of the awareness of self-consciousness property as a reflexive rank, since genuine intelligence arise, is proposed. AI as a model can be built as a hybrid multi-agent system. Some circuits may be analog, others – digital; some systems may be self-learning, others may operate under algorithmic rules and mathematical functions. The success of perceptronical inclines to idea that sensation modeling can be self-learning. The level of emotions can be realized as primary representations in the analog form. The later may be abstracted in judgments treated as secondary representations. The level of self-consciousness or meta-psychological states implies certain possibility of learning to self-learning (as an analogue of awareness of self-awareness) using secondary representations at the input.
Multi-Agent Task Assignment and Sequencing using Monte Carlo Tree Search and Process Algebra

In this article we explore the advantages, and disadvantages, of solving multi-agent to task assignment problems by searching state-space trees using Monte Carlo Tree Search (MCTS) and Process Algebra (PA). State-Space trees have been used for many years to assign tasks to agents. Since these trees exhibit exponential growth as the problem size increases, optimal solutions can be hard to find. Over the years we have used Depth First Branch and Bound (DFBnB), and Genetic Algorithms (GA) to find solutions, but each of these methods have drawbacks. Introduction of MCTS has the potential to alleviate these drawbacks while improving solution quality. Furtermore, the integration of Process Algebra with MCTS allows for richer problem formulations by making it possible to define relationships between generic tasks.
Supplemental Material: Pyroxenite melting at subduction zones

&lt;p&gt;Data filtering methods, crustal thickness calculations, spatial averaging methods, error calculations, sample locations, Zn/Fe versus Al2O3 for subarc peridotites, Zn/Fe-crustal thickness correlation for samples with MgO &gt;10 wt%, Dy/Yb, Ba/Nb, and Th/Nb ratios as a function of crustal thickness, copper contents of peridotite- versus pyroxenite-derived melts, the filtered and spatially averaged global geochemical compilation created and used in this study, and the compilation of experimental melts of silica-deficient pyroxenites. &lt;/p&gt;
Enhancing Students’ Skill in Writing an Argument through Brainwriting

The target of class is second grade students of Gunung Kaler 2 Junior High school in Tangerang Regency, the subjects of this study were conducted toward students of class VII A which contains of 32 students in the class. The purpose of this study was to enhance students' writing skill in argument throughbrainwriting. It is a qualitative research that using a classroom action research method. In this research consist 3 cycles, where each cycle consists of 4 steps namely planning, acting, observation, and reflecting. The data collected through observation, writing test, and interview. The result of the research showed that students’ writing skill in argument could enhance significantly after applied brainwriting to them. For KKM score is 75, it could seemed from the percentage in cycle one was 61. Then in cycle two percentage became 86, the percentage became 100% Based on the data collected that implementing braiinwriting could enhance students’ writing skill in argument. Because through brainwriting makes students could be understand deeply related text types accordance of the context use and students could create the text well. Based on the explanation above, it could be conclude that enhancing students’ writing in argumenttive through brainwriting was effective way in teaching learning process especially in learning writing in argument.
FAIR digital objects, persistent identifiers and machine actionability

Based on the work of the Research Data Alliance and FAIR Digital Objects Forum, and examples from three different domains, this article highlights the importance and effectiveness of PID level metadata for FAIR implementation and machine actionability.
Acknowledgment to the Reviewers of Minerals in 2022

High-quality academic publishing is built on rigorous peer review [...]
Research on the Algorithm of Situational Element Extraction of Internet of Vehicles Security based on Optimized-FOA-PNN

The scale of the intelligent networked vehicle market is expanding rapidly, and network security issues also follow. A Situational Awareness (SA) system can detect, identify, and respond to security risks from a global perspective. In view of the discrete and weak correlation characteristics of perceptual data, this paper uses the Fly Optimization Algorithm (FOA) based on dynamic adjustment of the optimization step size to improve the convergence speed, and optimizes the extraction model of security situation element of the Internet of Vehicles (IoV), based on Probabilistic Neural Network (PNN), to improve the accuracy of element extraction. Through the comparison of experimental algorithms, it is verified that the algorithm has fast convergence speed, high precision and good stability.
A Study Into the Alteration of Physical and Chemical Characteristics of Activated Carbon Surface for Purifying Water

The most common applications of activated carbon in today’s world are process water treatment, commercial and industrial wastewater treatment, and air/odour abatement. When transformed to activated carbons, carbonaceous source materials have the potential to efficiently cleanse and eliminate a wide range of pollutants from water and wastewater streams. With over 1,000 recognized uses, activated carbon’s potential is limitless. AC may be tailored to satisfy a wide range of unique purposes, from gold mining to water purification, and food manufacturing. Non-polar adsorbents like activated carbon work well. It may be used with a range of substances to adsorb diverse qualities of wastewater due to its large specific surface area and micropore, high adsorption performance, and recycling. This research aimed to look into the influence of chemical surface features on activated carbons’ application in water purification.
DESIGN OF TRAFFIC ACCIDENT PREDICTION MODEL IN TOLL ROAD USING A DECISION TREE ALGORITHM

A toll road is a road that the users are obligated to pay, which is held to improve efficient transportation services. Although toll roads have relatively more ideal conditions than highway roads, many traffic accidents still occur on the road. Toll road managers collect operational data on toll roads, including daily traffic, weather, and accident data. One of the solutions to increase the level of toll road safety is to design an accident prediction model through data mining. In this paper, the prediction model was made using attributes according to the framework consisting of day, type of road surface, weather conditions, road surface conditions, time of occurrence, driver sex, and type of vehicle. The prediction model was built to predict certain areas' probability and severity of accidents. The prediction model is built using the decision tree algorithm. The results show that the attributes used can predict the severity of accidents with 39.73% accuracy. The most vulnerable area is in section B on 9 to 10 km, with a total number of accidents of 13.17% of total accidents.
Physical-Chemical Properties and Spatial Distribution of Heavy Metals in Agriculture Soil in Al-Qadisiyah City by using ArcGIS and Multivariate Analysis

Al-Qadisiyah governorate is one of the most important agricultural areas in Iraq, and the study was conducted in different areas of the governorate, including seven areas for sampling. The physical-chemical properties and heavy metals of agricultural soils were examined. The results showed that highest value was Ni (189.9 mg/kg) followed by Cr (124.5 mg/kg), Zn (50.8 mg/kg), Cu (36.9 mg/kg), Pb (35.2 mg/kg) and Cd (1.17 mg/kg). Moreover, Ni and Cr concentration levels were higher than Canadian soil guidelines. Geostatistical analysis was applied to know the sources of heavy metals in agricultural soil and results were revealed that Zn, Cu, Ni, and Cr were the same pollution sources and Cd and Pb also were the same pollution sources indicating these elements impacted by anthropogenic activities. The Pearson correlation coefficients found some physical-chemical properties role in increasing heavy metals in the soil such as EC and Cu, and also TOC, OM and Cr. Therefore, these results are considered useful for the competent authorities in order to reduce and control these pollutants in agricultural soils.
Signature Verification Using Python

Abstract: Each individual has a distinctive signature that is primarily used for personal identification and the confirmation of significant papers orlegal transactions. Static (offline) and dynamic signature verification come in two flavours (online). After a signature has been made, it can be verified using a methodknown as static verification. For a lot of documents, off line signature verification is ineffective and slow. Online biometric personal verification, such as fingerprints, eye scans, etc., has increased in recent years as a way to get over the limitations of offline signature verification. Convolution neural network (CNN)-based offline signature verification is proposed inthis study. We can extract more accurate representations of the image content using a neural network model called CNN. In order to improve categorization, CNN starts with the raw pixel datafrom the image, trains the model, and then automatically extracts the features. CNN's key advantage over its forerunners is that it automatically identifies significant features without human supervision and that it predicts images with the highest degree of accuracy of any algorithm.
Sentiment Analysis Using Machine Learning

Abstract: Sentiment analysis falls within the category of analytics research. This can make sense by reading raw data using computational methods. This is what analysis is. Written expressions that are neutral, unfavourable, or indifferent can be assessed using sentiment analysis. People use a variety of social media platforms, including Facebook and Twitter, which is a useful tool for gauging public sentiment. This uses a variety of machine learning techniques. We have considered a variety of sentiment analysis techniques in this study. Using machine learning classifiers, sentiment analysis has been carried out. Users' tweets are categorised as having "positive" or "negative" sentiment using polarity-based sentiment analysis and deep learning models. Sentiment Analysis, one of the branches of computer science that is now gaining the most ground.
Studi Pustaka: Konsep Bilingualisme dan Pengaruhnya terhadap Perkembangan Bahasa Anak

This research aims to discuss qualitative research with the literature study method. The method used is the literature study method, data collection by finding sources and constructing from various sources such as books, journals, and pre-existing research. Therefore, qualitative research is carried out with a research design whose findings are not obtained through procedures or in the form of calculating numbers, but describe holistic-contextual phenomena by collecting data from researchers and various sources and making them as instrumental keys. Qualitative research has a descriptive nature and is more likely to use inductive approach analysis, so that processes and meanings based on the subject's perspective are more prominent in this qualitative research. Based on the results of this literature study research, it can be concluded that bilingualism is a phenomenon of the use of two or more languages by a person. Bilingualism can occur due to internal as well as external factors. The internal factor for the occurrence of the phenomenon of bilingualism is the existence of intermarriage between two people which causes the offspring to have more than one language. The external factor is the presence of additional language learning as a second language. The phenomenon of bilingualism also has an impact on children's language development. Bilingualism is not a bad phenomenon for a child's language development. Children affected by the phenomenon of bilingualism tend to be considered more intelligent than monolingualism. So many educational institutions equip children with other languages even from an early age.
Pengaruh Media Audiovisual terhadap Prestasi Belajar Siswa dalam Mata Pelajaran Ipa Kelas VI SD Negeri Perdopo 02 Gunungwungkal

The purpose of this study was to find out descriptively the learning success of class VI students at SDN Perdopo 02 who studied with audiovisual media and did not learn with audiovisual media. Based on this comparison, the aim is to find out the science learning outcomes of class VI students at SDN Perdopo 02 in odd semesters between being taught with and without audio-visual media. The results showed that students in grade VI at SDN Perdopo 02 had a very high learning rate with an average of 23,500 audio-visual media and studied without audio-visual media. audiovisual media in the high category, an average of 18,500. The t-test gives tcount = 3.999 and p = 0.001 if p &lt;0.01, so that comparing the results of the t-test it is concluded that a very significant value makes a difference in achievement in science learning from class VI SDN Perdopo 02 for students with audiovisual media and without audiovisual media.
Peran Pajak dalam Meningkatkan Pembangunan Pendidikan di SMKN 7 Tangerang

This study aims to analyze the role of taxes in increasing educational development at SMKN 7 Tangerang. The method used in this research is qualitative descriptive analysis. The approach taken is by analyzing the results of the interviews that have been conducted and then describing them. Qualitative research is research that produces descriptive data in the form of written or spoken words. The data taken was obtained from a question and answer session with resource persons, relevant sources, as well as direct visits to SMKN 7 Tangerang. The data analysis technique used in this research is qualitative content analysis. The results of this study indicate that taxes play an important role in improving educational development such as facilities, teaching staff, and developing the potential of students at SMKN 7 Tangerang. Taxes play a role in providing assistance in the form of physical and non-physical. Taxes play a role in improving school facilities. Taxes play a role in managing funds provided by the government. Based on the results of this study, it was concluded that public schools receive subsidized assistance from the government, the assistance provided is obtained from public awareness in paying taxes.
Renewable Energy Utilization and Environmental Pollution Control in the New City Area Mamminasata Metropolitan, Indonesia

The dynamics of the development of the Mamminasata Metropolitan new city area has an impact on environmental quality degradation. The increase in development activities causes land use conversion and contributes to an increase in energy demand. This study aims to analyze: the allocation of work space utilization as a determinant of environmental quality degradation in the Mamminasata new city area, the effect of controlling space utilization, renewable energy utilization, and transportation management on improving the environmental quality of the Mamminasata new city area; and formulate a model for the use of renewable energy and the sustainable development of the Mamminasata Metropolitan new city area. This study uses an explanatory suqiental approach. Data were obtained through observation, surveys, in-depth interviews, and documentation. The results of the study indicate that the allocation of land for the development needs of socio-economic activities in the new city area has an impact on increasing the burden of pollution on soil, water, and air as well as the complexity of the transportation system in the direction of decreasing environmental quality. Control of space utilization, renewable energy utilization, and transportation management simultaneously have an effect on improving the environmental quality of the Mamminasata new city area with a coefficient of determination of 94.84%. This study recommends the use of renewable energy in supporting socio-economic activities towards the sustainability of the Mamminasata Metropolitan new city area development.
The Effectiveness of Using Blindfold Games to Improve Students’ Vocabulary

The main aim of the study is to examine the effectiveness of blindfold game to improve the students’ vocabulary mastery. The writer used random sampling technique to take the samples and total number of the sample were 20 students. The instrument of the study was vocabulary test. The result of the study reveals that there is a significant different between the students’ vocabulary mastery before and after using blindfold game. In the pre-test, there are 2 or 10% students get very poor, 7 or 35% students get poor, 8 or 55% students get fair and also 3 or 55% students get average classification. While in the post test, there are 8 or 40% students get average score, 11 or 55% students get good score, and only 1 or 15% students who get very good classification. The means score of the post-test is greater that pre-test ((56.25 &lt; 75. 90).). The standard deviation of pre - test is 15. 18 and post-test is 9. 19. While P- Value = 0,000, (α)= 0,05. It means that the t - test is smaller than (α).