Reviewerly/exHarmony huggingface dataset:
The Regional Extents of Local Thrust Systems in Jabbari and Rupper Town, South East of Hazara Pakistan

Geological traverse between the town of Jabbri and Rupper, southeast Hazara delineates the stratigraphic and structural element of the area presented by high resolution geological map and cross section of the area. Oldest rocks in this section is Precambrian Hazara formation which is disconformably overlain by a Jurassic to Eocene sequence including Samana Suk, Chichali, Lumshiwal, Kawagarh, Hangu, Lockhart, Patala, Margalla-hill-limestone, Chorgali and Kuldana formations. Located in Lesser Himalayas, under the influence of main boundary thrust (MBT), this area developed several thrust systems from north to south including Hazara thrust, Haro thrust, Sangoda thrust, Rupper thrust. The main regional Hazara thrust has Precambrian rock in its hanging wall thrusted over the Jurassic Samna Suk formation. In lower detachment, there are several local thrust systems within Jurassic-Eocene strata.These thrusts trends in NE-SW direction indicating NW-SE compressional regime with the hanging wall Drag folds showing southward vergence. The stereographic plot of mesoscopic scale folds shows at least three folding events and varying plunging directions between the range of 240° and 290°. Most of the folds are plunging towards west and this is yet another indicator of east-west compressional forces. These folds orientations suggest transpressional deformation rather than pure compression. The balanced restore section shows that there is about 2.5 km shortening along 15 km restored section which makes about 16% shortening along the section.&#x0D; &#x0D;
The Deviant Behavior of The Investigators in Using of Forced Efforts as Learned and Maintained Behavior

The author conducts research especially on the use and abuse of forced effort by investigators.This research was done qualitatively for twelve years through respondents, Polri officials, both of those who were still in service or not, those who had dealt with Polri investigators as suspects in a criminal case, and University students from the Faculty of Law in Semarang.The use of forced efforts and even the abuse can run continuously because the investigators have studied it and defended it.This can occur due to several reasons, including lack of professionalism of investigators and infrastructure and funds to carry out investigations in criminal cases; in using the investigator forced efforts without paying any attention to the consequences or the negative side of the use of it for others and also in the end for themselves; they are also no longer able to control the consequences of their actions which can be harmful and unpleasant; what they have done before, in the form of this deviant behavior, has also been strengthened to be done again through the ease of their work activities and the various benefits that can be obtained through the use and abused of such forced efforts.This is following the Differential Enforcement theory submitted by Burgess and Akers.The essence of the basic understanding of this theory can be said to continue the essence of Sutherland's basic understanding of the theory of Differential Association regarding learning about crime.
Indian Railway Tweet Monitoring System

Abstract: In today’s fast paced and competitive world, India is home to one of the world’s largest railway networks. According to statistical facts, approximately 22 million passengers travel via trains every day. A majority of them are on various social networking site including Twitter, adding to this, more than 200 million users are active daily on this application, tweeting more than 500 million tweets every day, out of them, at least 600 are based on the sole topic of complaining about railways, about 5% are suggestions and etc. To help out the Indian Railway Ministry to quickly classify and/or clarify the tweets as soon as possible and in a much more efficient manner, we would provide a solution by helping them classify the types of posts such as if it is a complaint, or just feedback, or some other type. Since almost everyone on this planet wishes to get a swift and quick response for any query they have, this application would allow the whole team behind the scenes to efficiently handle all the tweets, give a response to the posts, and allows them enough time to get working on an issue.
Institute Recommendation System Based on Online Review Comments and Machine Learning

Abstract: Recommendation system has become a necessity in real world. In recommendation system, we are searching any product based on the reviews, if any product shows the best ratings, then we can select that product. Recommendation system has been used in wide range of application like, amazon, Netflix, Flipkart, Facebook etc. Now institution also become a part of recommendation system. In institution recommendation system, we select those colleges which is having a best reviews, which meets our eligibility criteria and our branch also. Recommendation system helps the user to discover the information and settle on a right choices where they do not have the required learning to judge a specific item. Only Naves Bayes algorithm is best algorithm in this system that we can easily check, and recommends them. This system has been used in education. Keywords: Artificial Intelligence, Machine Learning, Artificial Immune System, Naives Bayes, Decision Tree, Collaborative Filtering, Content Filtering, Hybrid Filtering
Prediction of Electricity Usage with Back-propagation Neural Network

The use of electricity has become a need that is increasing day by day. So it is not surprising that the problem of using electricity has attracted the attention of many researchers to research it. Electricity users make various efforts and ways to save on the use of electrical energy. One of them is saving electricity usage by electricity users using electrical energy-efficient equipment. That is why the previous research confirms the need for interventions to reduce the use of electrical energy. Therefore, this study aims to predict electricity use and measure the performance of the anticipated results of electricity use. This study uses the back-propagation method in predicting the use of electricity. This study concluded that the backpropagation architectural model with better performance is the six hidden layer architecture, 0.4 learning rate, and the Root Means Square Error (RMSE) value of 0.203424. Meanwhile, the training data test results get the best architectural model on hidden layer 8 with a learning rate of 0.3 with an RMSE performance value of 0.035811. The prediction results show that the prediction of electricity consumption is close to the actual data of actual electricity consumption.
Intelligence System for Multi-Language Recognition

Language classification systems are used to classify spoken language from a particular phoneme sample and are usually the first step of many spoken language processing tasks, such as automatic speech recognition (ASR) systems Without automatic language detection, spoken speech cannot be properly analyzed and grammar rules cannot be applied, causing failures Subsequent speech recognition steps.We propose a language classification system that solves the problem in the image field, rather than the sound field.This research identified and implemented several low-level features using Mel Frequency Cepstral Coefficients, which extract traits from speech files of four languages (Arabic, English, French, Kurdish) from the database (M2L_Dataset) as the data source used in this research.A Convolutional Neuron Network is used to operate on spectrogram images of the available audio snippets.In extensive experiments, we showed that our model is applicable to a range of noisy scenarios and can easily be extended to previously unknown languages, while maintaining classification accuracy.We released our own code and extensive training package for language classification systems for the community.CNN algorithm was applied in this research to classify and the result was perfect, as the classification accuracy reached 97% between two languages if the sample length was only one second, but if the sample length was two seconds, the classification accuracy reached 98%.While the classification among three languages, the classification accuracy reached 95% if the sample length was only one second, but if the sample length was two seconds, the classification accuracy reached 96%.
Carrying Out The Instructive-Educational Activities For Optimal Integration Of Preschoolers

The golden age of childhood brings a number of important changes in a child's life.Play is the most important source of learning for children and their main concern at preschool age.Kindergarten is a space for play and social experimentation, where the child plays, establishes emotional relationships with adults and children, learns to live in the community and respect the individuality of others, to be tolerant of differences.Thus, the kindergarten meets the need for community and socialization of the child.Positive interactions with colleagues lead to the building-up of friendships, the development of cooperation skills and conflict resolution.However, not all children can easily establish friendships.The purpose of our research aims to highlight the importance of stories, exercise games and role-playing games in order to optimally integrate preschoolers in the mixed group in kindergarten.The research took place over a period of 18 weeks.The methods used in the research were observation and psycho-pedagogical experiment.To test the hypothesis, we used as a research tool an observation grid.The study was attended by 20 preschoolers aged 2-6, from one preschool education unit in Cluj-Napoca town, Romania.
Data Collection Improvement: Daily Self-Enumeration Accommodation Survey

Until now, BPS - Statistics Indonesia has conducted monthly accommodation surveys both for the star and non-star accommodation categories to provide information on commercial accommodation activities at the national and regional levels. Both star and non-star accommodation categories are done by complete enumeration in each region. Statistics include guest night and room capacity to obtain the occupancy rate of a hotel room. The data contains daily accommodation information that is collected every month, so then it will be entered completely in each region following the observation month. Due to the timeliness requirements for monthly press releases, BPS has implemented online data entry since 2017. It may seem obvious, regions that have more interest will have an impact on a bigger number of accommodations, which also affects the number of enumerators and may lead to such problems especially in response burden. Unfortunately, the same problem is also not easily avoided by regions with less accommodation, mostly due to the distance issues to the accommodation area and its spread in the region. Therefore, a new data collection strategy is required to provide respondents with convenience in order to increase response rates, as well as to reduce the workload of enumerators which also leads to the lower cost. The outbreak of COVID-19 has posed unprecedented problems for National Statistical Offices (NSOs) around the world, including BPS – Statistics Indonesia. This crisis has led us to think in new ways and make decisions that will change our statistical operations in order to meet ongoing data needs even throughout the epidemic. The purpose of this paper is to discuss the evolution of accommodation surveys, which are designed to not only solve problems but also achieve objectives. Currently, there are nearly 180 active users of this self-enumeration accommodation survey for about 142 distinct accommodations across Indonesia. Moreover, this addition has proven to have succeeded in increasing the response rate average from 57.17% in 2020 to 68,35% in 2021.
An Analysis of EFL Students’ Difficulties in Listening Comprehension at STKIP Muhammadiyah Bogor

The purpose of this study is to find out the difficulties or problems and the factor encounter by students in listening comprehension aimed to prepare teacher to help Student difficulties and solve the problems during teaching. This research used qualitative descriptive method. The procedure data employ the questionnaire in collecting data. 61 EFL Students of STKIP Muhammadiyah Bogor as participants. Ther resultd revealed that there were some factors affected to EFL learner in listening comprehension such as listening material, listener attitude and background knowledge, speaker and physical setting, but the most difficulites faced students in this case were lengt speech its about 60%, and unfamiliar words its about 80% in listening material variable. Meanwhile, for the listener attitude and background knowledge at the least there were two items the most difficulties faced such as catching linking word its about 54% and catching proper word its about 44%. The last and the most significant difficulties faced was the speaker and physical setting such as in unclear recorder resulting from poor CD or casset its is about 93%, and poor of recording quality and poor of equipment both of them approximate 90%.
Multi-Level Fusion Model for Person Re-Identification by Attribute Awareness

Existing person re-recognition (Re-ID) methods usually suffer from poor generalization capability and over-fitting problems caused by insufficient training samples. We find that high-level attributes, semantic information, and part-based local information alignment are useful for person Re-ID networks. In this study, we propose a person re-recognition network with part-based attribute-enhanced features. The model includes a multi-task learning module, local information alignment module, and global information learning module. The ResNet based on non-local and instance batch normalization (IBN) learns more discriminative feature representations. The multi-task module, local module, and global module are used in parallel for feature extraction. To better prevent over-fitting, the local information alignment module transforms pedestrian attitude alignment into local information alignment to assist in attribute recognition. Extensive experiments are carried out on the Market-1501 and DukeMTMC-reID datasets, whose results demonstrate that the effectiveness of the method is superior to most current algorithms.
Copyright Protection of Literary Works Based on Data Mining Algorithms

In order to improve the copyright protection effect of literary works and improve the healthy dissemination of digitized literary works, this paper combines data mining technology to conduct research on the copyright protection of literary works and constructs a literary copyright protection system. In digital literary works, watermarking algorithms can be used to watermark the characteristics of literary works to obtain digital literary works that have been watermarked. After that, this paper can combine data mining algorithms to perform text feature recognition and feature classification and improve the copyright protection effect of literary works. The experimental research results verify that the effect of the copyright protection system of literary works based on data mining algorithms is very good.
Web based Library Resources and Services Library and Information Science

With the emergence of the internet and associated technologies, in particular the World Wide Web has opened up an entirely new medium for providing improved information services and resources for the users.Library services provided by using web technology are referred as web based library services.The present paper mainly discusses that what are the web based library services, their features, advantages and disadvantages.Different web based services i.e.
Simulation Research on Automatic Navigation of Indoor Wheelchair

A new auto-navigation wheelchair based on ROS system is proposed to deal with the global aging and the low behavioral ability of the elderly.Lidar is used to locate and map the active area using gmapping algorithm.Real-time map information is transmitted to the processor by the camera and lidar working together.Automatic navigation is completed by A* algorithm calculation.Important information points are marked by QR code and precisely positioned by camera recognition, which enables wheelchair to have automatic navigation function.It can help older people move safer and more freely at home; It can also be applied to nursing homes to reduce the pressure of nurses and centralize management of the elder.
Online active classification via margin-based and feature-based label queries

In the paradigm of online active classification, the learner not only has to predict the label of each incoming instance, but also must decide whether the true label of that instance should be supplied, or not. The overall goal is to minimize the number of prediction mistakes with few label queries. In this paper, we focus on a novel framework for online active learning, with the aim of handling high dimensional classification problems. The key component of our framework is to exploit both the margin-based predictive uncertainty and the feature-based discriminative information of the current instance, in order to determine whether it should be labeled. Based on this labeling strategy, we propose several online active learning algorithms, for both binary classification tasks and multiclass ones. For these algorithms, which use adaptive subgradient methods for updating their linear model, expected mistake bounds are provided. Experiments on high-dimensional (binary and multiclass) classification datasets reveal the benefit of our label query strategy, and show the superiority of our algorithms over the existing ones.
PARTNERSHIP OF UNIVERSITY AND SCHOOL AS A FACTOR IN THE DEVELOPMENT OF PERSONAL POTENTIAL OF STUDENTS: EXPERIENCE OF THE ORGANISATION

The problem of increasing the personal potential of school students in accordance with the new educational paradigm is now more and more urgent for the education system. The modern development of the economy, science, culture, and the social and spiritual sphere of life requires that people be endowed with the qualities of a creatively gifted person. Such personality is characterised by non-standard thinking, the ability to generate original, unusual ideas. The concept of "personal potential" means a person's ability to multiply his inner capabilities, first - the ability to develop, this is the ability to live a rich inner life and effectively interact with the environment, be productive, grow and develop successfully.In modern conditions, the school and teacher are no longer the only and main sources of education. The school student turns into an active participant - a subject of educational activity: not only a consumer, but also a producer of information. This situation requires a continuous search for new forms of interaction and pedagogical support of students. And in this context, various forms of partnership between the university and school have been successfully developing for a long time. Universities actively cooperate with schools, are organisers of a set of activities for working with children involved in the system of pre-university training and continuing university education.The results of the study, based on the study and analysis of experience in organising partnerships between leading universities, including the Kazan Federal University, and schools of the Russian Federation, provide data on the most effective types of their interaction, contributing to the development of the personal potential of school students.In a systematic form, the authors compare the structural components of the personal potential of students, highlighting their main target characteristics and the corresponding forms of partnership between the university and school.The authors have developed and presented a model of interaction between the university and school, which contributes to the development of key components of the structure of personal potential of a school student: intellectual, communicative, creative, emotional-volitional, motivational-value.The paper formulates recommendations to improve the effectiveness of partnerships between the university and school in the direction of developing the personal potential of school students.
Implementation of Flood and Drought Control for Economic Growth of the Cisadane River Flow in Banten

The current growth of water conservation in Indonesia is still not optimally utilized by the community. The government has an important role in flood and drought disaster control to improve the welfare of its population. According to Indonesian Law No. 11 of 1974, water is a basic necessity for humans. However, human activities in agriculture, industry, and household activities can cause pollution, where the necessity for water increases yet its quality decreases. The water resource network in the watershed area of Banten Province, especially in Cisadane, is an old water resource facility and infrastructure, so there is some large and small scale damage, which certainly has an impact on the services to the water users. Related to flood control, the lake has a very important role as a water storage area and in reducing the amount of water runoff/water retention. The decline in the condition of the flow of rivers, lakes, reservoirs and swamps is inseparable from physical predicaments such as land conversion, and non-physical ones such as natural disasters. Therefore, the government’s role is important to provide information on flood and drought disaster control management systems so that the community can support their economic stability and be properly maintained.&#x0D; Keywords: implementation program, optimization, conservation of water resources, flood and drought disasters
A machine learning method for seismic signal monitoring: A contribution to the detection of the potential volcanic hazard on Etna, Italy

&amp;lt;p&amp;gt;The dynamics driving an eruption play a crucial role in the impact volcanic activity has on the community at large. The interpretation of geophysical and geochemical changes heralding a volcanic unrest is a fundamental key to forecasting upcoming phenomena. However, the style and intensity of the eruption are difficult to predict, even in open-conduit volcanoes where eruptions can be relatively frequent. This is the case of Etna, in Italy, one of the most active basaltic volcanoes in the world. In 2021, fifty-two lava fountains arose from its Southeast Crater accompanied by lava emissions and ash fallout, which disrupted air and road traffic in numerous Sicilian municipalities. Lava fountains are just one of the typical eruptive styles of Etna. Strombolian activity and lava flows are also relatively frequent here, each with its own characteristics in terms of intensity and social impact.&amp;lt;br&amp;gt;We developed a machine learning (ML) method for the analysis of the seismic data continuously acquired by the local stations of the Etna permanent seismic network, exploiting the spectral characteristics of the signal. Its design started from: i) the need to detect the volcanic hazard, and ii) provide timely and indicative information on possible eruptive scenarios to the Civil Protection and the Authorities. Besides the identification of anomalies in the data, which flag enhanced volcano dynamics in its early stages, we investigate on clues concerning the potential intensity level of eruptive phenomena. The method works in near real time and can effectively contribute to the multidisciplinary analysis of volcanic hazard.&amp;lt;/p&amp;gt;