Reviewerly/exHarmony huggingface dataset:
THE IMPLEMENTATION OF KAKI READING TECHNIQUES WITH QUANTUM LEARNING STYLE IN READING COMPREHENSIVE LEARNING (PENERAPAN TEKNIK MEMBACA KAKI GAYA QUANTUM LEARNING DALAM PEMBELAJARAN MEMBACA KOMPREHENSIF)

Reading is an obligation for students, therefore, Indonesian Tadris students who will become educators should also be able to develop reading skills.Unfortunately, this is still far from expectations, thus it is necessary to apply the right and suitable method to increase student passion in the reading comprehensive subject.The purpose of this study was to describe the implementation, benefits, constraints, and solutions of the KaKi technique with quantum learning style in the Comprehensive Reading learning.This study used descriptive qualitative with a case study research approach.The data sources are obtained from places, events, informants, and documents.Places and events are the processes of implementing learning carried out in the classroom.The informants in this study were Indonesian Tadris Department students.The documents studied are related to the implementation of Comprehensive Reading learning.The data obtained were analyzed using an interactive analysis model which included data reduction, data presentation, and drawing conclusions or verification.The results showed that 1) the implementation of the KaKi technique with Quantum Learning Style was suitable with the RPS or Semester Learning Plan compiled by lecturers following curriculum standards.2) There are benefits in implementing the KaKi technique with Quantum Learning Style.3) There are constraints in implementing the KaKi technique with Quantum Learning Style.
Strategi Pengajaran Guru Dalam Mengatasi Kecemasan Berbicara Siswa

Abstract: This present research has specific aims they are:(1)To investigate the students’ speaking difficulties in English Intensive Program. (2) To investigate the speaking anxiety of students in English Intensive Program. (3) To analyze teachers’ teaching strategies in the English Intensive Program conducted in Al-Bahjah II Boarding School Cirebon. This study shows how the teacher’s teaching strategies to overcome the students’ speaking anxiety. This Research used Descriptive Qualitative as a method, in this research, the instrument of the research is the researcher herself. The researcher becomes the source of collecting the data. As the instrument of the research, the researcher took the data carefully and accurately by using two techniques of data collection, namely observation and interview. This research was conducted at Al-Bahjah II Boarding School Cirebon. The respondents are English Teacher and the students of Banat 3 in Al-Bahjah II Boarding School Cirebon. which chosen by strong consideration. The Finding of the research was shown that (1) The students faced some difficulties which comes from external and internal factors. From external factors students have incomprehensible learning input and being left behind by the fluent students in speaking. While, from the internal factors students are lack of vocabulary and grammar mastery. (2)  The students in English Intensive Program have two kinds of speaking anxiety namely State and Trait speaking anxiety. State speaking anxiety faced  by the students are afraid of being tested and nervous of being monitored by the teacher and afraid to speak in front of the class and being ridiculed by the peers. Besides, the trait speaking anxiety faced by the students are lack of confident and high tension of nervous. (3) There are five kinds of teaching strategies used by the teacher that considered to overcome the students’ speaking anxiety in English Intensive Program namely, drilling, role play, presentation, group work, show and tell.
History of chemical mineralogy in Russia (1740-1790)

Abstract Until the end of the XVIII century, mineralogy as an independent science did not exist. Mineralogy, in essence, was called the science of ore deposits in its modern sense. Then, there was no clear definition of the term "mineral." This concept included not only minerals in the proper sense of the word, but also ores, rocks, and fossils. Due to the low general level of knowledge by the middle of the XVIII century, there was no information on the chemical composition of minerals. Of all the chemical elements in the time of Lomonosov (until 1765), only 17 were known: carbon, phosphorus, sulfur, iron, nickel, cobalt, copper, zinc, arsenic, silver, tin, antimony, platinum, gold, mercury, lead and bismuth. Later, until 1790, 11 more chemical elements were discovered: nitrogen, oxygen, chlorine, manganese, barium, molybdenum, tungsten, tellurium, hydrogen, zirconium, uranium. Lomonosov laid the chemical study of minerals using qualitative and primitive quantitative analyzes. Along with chemical analyzes, physical experiments were carried out to study minerals. The scientist had the idea of synthesizing minerals, artificially obtaining salts, a number of ore and other minerals. Thanks to the efforts of Lomonosov, the first scientific chemical laboratory was built and opened in St. Petersburg. Scientists covered various issues of mineral formation, including deposition methods and sources of mineral matter, and paragenetic associations of minerals.
An Improvement in Branch and Bound Algorithm for Feature Selection

Branch and bound (BB) algorithm undergoes an exponential growth in feature selection as the number of features increases, which may require, in the worst cases, exploring the whole tree looking for an optimal solution. This paper presents an enhancement in the BB algorithm for feature selection using an approximate monotonic criteria function. The enhanced version of the sub-optimal BB algorithm seeking for the solution by cutting unpromising paths and deleting multiple features at each internal tree node based on a predefined tao variable. The experiment was applied to different datasets and compared to the original BB algorithm and numerous selection methods. The results show promising results in terms of accuracy, elapsed time, and tree size.
Describing a Smart Learner in Mastering the English Speaking via Text Message Interview

In a country of which English is considered as a foreign language, learners are lack of practicing in using the English language for real communication in their life.They prefer talking in their own languages.Their environment does not support them to have the emersion situation.The books they use are not printed in English.Their teachers do not use English for explaining their subjects.They never get a speaking test in their learning test.So they are not fluent in speaking the language.As the result they are not confident in communication.In the contrary, the problems are answered by a qualified student.How does the smart student becomes fluent in non English speaking country is explored in this research.It presents about the way how to be good a English speaker.She is interviewed via text-message interview to answer some questions about the activities how she becomes a good and fluent in Speaking English.As a part of qualitative research, her answers are used as the data that are employed to describe the activities that support her as a qualified English speaker.The findings are concluded that she becomes fluent in speaking because she makes herself as an english user in various activities.
RETRACTED: Research on Existing Problems and Innovation Strategies in Civil Engineering Construction Technology Based on Computer Technology

Abstract In recent years, the industry reform of Construction Engineering in our country has made great efforts based on computer technology. Under the background of computer market economy system, the construction industry has a broad development prospect. As an important part of it, the scale and quantity of civil engineering construction are also growing, and the building function is becoming more and more complex. This paper analyzes and discusses the problems and innovations in the construction technology of civil engineering, hoping to provide reference for relevant practitioners.
Evaluation of University Libraries in Turkey within the Context of Cloud Computing

Cloud computing is a service model that allows access to information resources such as computer networks, servers, databases and computer applications at any time and from anywhere.University libraries, like other libraries, already started to benefit from the cloud computing service model that provides benefits such as diversity, flexibility, continuity, scalability, and cost-effectiveness in their information services.In recent years, the increase in the number of universities has also increased the number of university libraries in Turkey.Cloud computing will enable university libraries, especially those with limited budgets, to provide information services more cost-effectively.In this study it is aimed to evaluate the position of university libraries in Turkey within the context of cloud computing.The structured interview technique was used in the research.SPSS program was used to evaluate the data.Percentage values, frequency and Chi-square statistic calculations were used to analyze the data.As a result of the research, the existing conditions and problems in the usage cloud service model in university libraries have been tried to be identified, a road map for solving these problems has been put into in this context.
Utilization of Digital Technology in Designing and Producing Zero Waste Clothes with Sustainability Approach

Consumerism is a new phenomenon created in the 21st century that can play a substantial role in the destruction of national resources of any country. Nowadays, concerning the ever-increasing improvement of fashion in the world, consumerism in the field of textiles and clothing is raised more than ever. Considering the wasteful consumption of products may bring about remarkable damages to the environment, presently certain methods such as no waste clothes production with a sustainability approach are under attention and survey. Researches accomplished in this regard resulted in the initiation of methods that are used by designers around the world as leading methods. Since this approach is an unprecedented opinion that is still in the route of extension and expansion, just a few studies have been conducted regarding the results obtained so far from designing zero-waste clothes and the experiences of consumers' awareness of this approach. The present research, regarding its objective, is of applied type based on descriptive-analytical method and procedure. Data collection is achieved by library method, relying on documents, written sources, and the internet. It challenges the discovery of the roots in this being formed field using the point of view proposed by Keith Fletcher. By explaining the experiences of this researcher in holding workshops related to this opinion, the out comings are surveyed. The obtained results confirm the application of various techniques such as digital printing patterns and the use of updated universal technology for the elimination of wastes.
Exploring the effects of linguistic labels on learned visual representations using convolutional neural networks

Deep convolutional neural networks (CNNs) trained on large numbers of images are now capable of human-level visual recognition in some domains (Rawat and Wang, 2017). Analyses of the visual representations learned by CNNs show some resemblance to human visual representations (Kriegeskorte and Douglas, 2018), suggesting that these networks may offer a good model of human object recognition. Here, we use CNNs as a model of visual recognition for the purpose of exploring the effects of different types of labels on learning of visual categories. To what extent are labels necessary to distinguish between different kinds of tools, animals, and foods? One idea is that certain visual categories are so distinct that no guidance from labels is necessary. Alternatively, labels may help or even be necessary to discover certain types of categories. This question is difﬁcult to answer in human learners because we cannot control their prior visual and semantic experience. We trained multiple CNNs on the same set of images while manipulating the labels they receive: none, basic-level labels (dog, hummingbird, hammer, van), superordinate labels (mammal, bird, tool, vehicle), or various combinations. We then correlated the model’s choices on a triad task (given three images, select the one that is most different) with people’s choices. The performance of unsupervised models was strongly dependent on low-level visual differences, highlighting the importance of labels to the training process. More surprisingly, the best performance was achieved by models trained using the coarser-grained superordinate labels (vehicle, tool, etc.) rather than basic-level labels, even when predicting triads where all three objects came from the same or from different superordinate categories (e.g., banana, a bee, and a screwdriver). The beneﬁts of training with superordinate-level labels will be further discussed in the context of representational efﬁciency and generalizability.
Virtual Reality and Tourism: Visiting Machu Picchu

In COVID-19 times, the mobilization of people has become a latent danger due to the possible contagion, consequently people are deprived of visiting archaeological sites in person. Thus, virtual reality emerges as an alternative solution. Individuals can immerse themselves within virtual environments to explore monuments, museums, and other cultural heritage sites. The purpose of this article is to present a system to make virtual visits to the Citadel of Machu Picchu. The UP4VED methodology was used the system construction. The tests of the 3D model were carried out with hotel guests, who showed their satisfaction with the immersive virtual visit to the citadel, considering it an easy-to-use technology that facilitates interaction.
Analysis and Application of the Factors Affecting Missile Storage Management Failure

In the process of missile's life-cycle management, it is because that missiles are in a storage state for a relatively long time and are affected by storage environment and time, the deterioration of the performance of the internal parts of the missile will inevitably occur and lead to failure or invalidation. Aiming at this problem, by collecting the storage management data of a certain type of missile for more than ten years combined with the analysis method of logical regression, this paper analyzes the main influencing factors of different types of failures during the storage management of this type of missile. Then, the improvement measures are put forward for the storage management mode based on the analysis results and an analysis model is used to predict the failure frequency after taking measures. Besides, the effectiveness of the improvement measures is verified by comparing with the failure frequency in the statistical data.
Research on Construction of Connected Curriculum System in Middle and Higher Vocation School

This paper points out the existing problems in china’s middle and higher vocational education and suggests the construction of connected curriculum system in this sector. Based on the experience from australia’s vocational education system, this paper promotes optimizing talent training program and constructing productive training bases in schools to train talent in an cooperative way between schools and enterprises. What’s more, diversified studying and module courses being used in curriculum are also keys to address the problem in china’s middle and higher vocational education.
Bayesian model of human visual search in natural images

The ability to efficiently find objects in the visual field is essential for almost any everyday visual activities. In the last decades, there was a large development of models that accurately predict the most likely fixation locations (saliency maps), although it seems to have reached a plateau. Today, one of the biggest challenges in the field is to go beyond saliency maps to predict a sequence of fixations related to multiple visual tasks. Particularly, in visual search task, Bayesian observers have been proposed to model the visual search behavior as an active sampling process. In this process, during each fixation, humans incorporate new information and update the probability of finding a target at every location. Here, we combine these approaches for visual search in natural images and proposed a model to predict the whole scanpath. Our Bayesian Searcher (BS) uses a saliency map as prior and computes the most likely next location given all the previous fixations, considering visual properties of the target and the scene. We collected eye-movement visual search data (N=57) in 134 natural indoor scenes and compare different variants of the model and its parameters. First, considering only the third fixation of each scanpath, we compared different state-of-the-art saliency maps on our dataset, reaching similar AUC performances as in other datasets. But, after the third fixation, all performances diminished to almost chance level. This suggests that saliency maps alone are not enough when top-down task’s information is critical. Second and more strikingly, when comparing BS models, their behavior was indistinguishable from humans for all fixations, both in the percentage of target found as a function of the fixation rank and the scanpath similarity, reproducing the entire sequence of eye movements.
President's Page

I am honored and eager to serve as the 90 th SEG president. As I undertake this great responsibility, I am fully aware that I am standing on the shoulders of those presidents who served before me — all of them the visionaries, entrepreneurs, and intellectual foundations of the applied-geophysics industry. Alan Kay, credited as the father of mobile computing, is often quoted as saying, “The best way to predict the future is to invent it.” As 2020–2021 SEG president, I commit to proactively support the difficult decisions necessary to maintain SEG’s legacy of excellence in applied geophysics and to invent an even more dynamic and relevant SEG for the future. Clearly, these times call for us all to be brave and proactive.
RETRACTED: Research on the Construction and Characteristic Development of College English Teachers Based on Big Data Analysis

Abstract With the urgent need for applied talents in foreign-related languages in China, the importance of English is also increasing. The construction and development of English teachers in colleges and universities is related to their English teaching level. Therefore, colleges and universities should actively solve the problem of the construction and development of teachers’ team based on big data analysis. The construction of teachers’ specialization is the foundation for the survival of higher education. The work of colleges and universities should closely focus on the construction of teachers’ specialization and actively explore and think about the effective connotative development model based on big data analysis. Therefore, on the basis of deeply exploring and exploring the characteristics of teachers’ team construction in private colleges and universities, exploring the connotative development mode of teachers’ team construction is conducive to the survival of colleges and universities, the overall improvement of teachers’ quality and the level and quality of personnel training.
Reliable Smart Contracts

The rise of smart contracts executed on blockchain and other distributed ledger technologies enabled trustless yet decentralised computation. Various applications take advantage of this computational model, including enforced financial contracts, self-sovereign identity and voting. But smart contracts are nothing but software running on a blockchain, with risks of malfunction due to bugs in the code. Compared to traditional systems, there is an additional risk in that erroneous computation or transactions triggered by a smart contract cannot be easily rolled back due to the immutability of the underlying execution model. This ISoLA track brings together a number of experts in the field of smart contract reliability and verification to discuss the state-of-the-art in smart contract dependability and discuss research challenges and future directions.
Hashish Addiction at Higher Education Institutions: Factors and Remedies

Hashish is considered to be the most widely and commonly used drug (UNODC, 2013, p-31). Hashish looks to be in usage of university students as well. A significant number of students have been reported with the usage of hashish regularly during their studies at universities. The usage of hashish is badly affecting the psychological and physical health of the students. The addict students have been found in street crimes as well. Therefore, this paper identifies the parental and societal factors of hashish addiction in universities students. To provide the remedies to overcome the usage of hashish in students, unstructured interviews were used as a tool of research. Purposive sampling was used in the selection of participants. The study is an empirical addition in the knowledge for the comprehension of hashish addiction in the students. The findings revealed a need for school wide consistency to address the usage of hashish in the students. It was concluded that students learned the usage of hashish from their parents as well. Parental illiteracy and poverty were found major factors of hashish addiction in the students. Students adopted the usage of hashish from senior students at university climate. The study can assist the school administration to evaluate their current efforts to overcome usage of hashish in students. The recommendations of the study are supportive in launching prevention programs for the hashish addiction in the students.
Brief Announcement: Distributed Quantum Proofs for Replicated Data

This paper tackles the issue of checking that all copies of a large data set replicated at several nodes of a network are identical. The fact that the replicas may be located at distant nodes prevents the system from verifying their equality locally, i.e., by having each node consult only nodes in its vicinity. On the other hand, it remains possible to assign certificates to the nodes, so that verifying the consistency of the replicas can be achieved locally. However, we show that, as the replicated data is large, classical certification mechanisms, including distributed Merlin-Arthur protocols, cannot guarantee good completeness and soundness simultaneously, unless they use very large certificates. The main result of this paper is a distributed quantum Merlin-Arthur protocol enabling the nodes to collectively check the consistency of the replicas, based on small certificates, and in a single round of message exchange between neighbors, with short messages. In particular, the certificate-size is logarithmic in the size of the data set, which gives an exponential advantage over classical certification mechanisms.