Reviewerly/exHarmony huggingface dataset:
Pose Estimation of 3C Components Based on Monocular 2D Camera

In order to accurately and effectively estimate the pose of 3C product components in the manufacturing process and meet the needs of intelligent production, this paper proposes a complete 3C component pose estimation technology scheme based on the Perspective n-Points algorithm, and also analyzes and verifies the impact of errors in theoretical derivation and experiment. Showing in the framework, firstly, we compared common monocular camera pose estimation algorithms to choose the suitable one, identified and analyzed the factors affecting the accuracy of pose estimation, then the whole design of marker points is discussed and the corresponding image detection and localization algorithm is optimized. After completing the above theoretical analysis and realization, an accomplished technical work-flow is formed. Through 3D software simulation and actual experiment, the effectiveness and accuracy of the pose estimation scheme in monocular camera case are verified, and the theoretical basis for realizing the higher precision in multi-camera case is also provided.
Bringing Shape to Textual Data – A Feasible Demonstration

The Internet has revolutionized the communication paradigm. This has led towards immense amount of unstructured data (i.e. textual data), which is a major source to get useful knowledge about people in several application domains. TM (Text Mining) extracts high quality information to discover knowledge by drawing patterns and relationships in textual data. This field has taken great attention of the research community. As a result, several attempts have been made to propose, introduce and refine techniques applied for uncovering knowledge from text data. This study aims at: (1) presenting existing TM techniques in the scientific literature, (2) reporting challenges/issues and gaps that still need attention, and (3) proposing a framework to bring shape to textual data. A prototype has been developed to demonstrate the effectiveness and potential worth of proposed approach to display how unstructured data (i.e. news articles in this study) has been brought to a shape representing interesting knowledge. The proposed framework implements basic NLP (Natural Language Processing) functions in combination of AYLIEN API (Application Programming Interface) functions. The results reveal the fact that how events, celebrities and popular news-items have been covered in the electronic media, and it also represents subjectivity of topical news events. The news coverage trends highlight the significance of daily news events, which may assist in getting insight about the media groups.
An Approach to Supervised Learning: Dynamic Multi-Hyperplane Partitioning

Supervised learning has tremendous applications in cancer prediction, patient treatment, business, and engineering. Datasets for supervised learning are often corrupted by noise and non-biological effects, leading to model-overfitting and performance degradation in current methods of binary classification. In this research, we develop a new classification method that fully exploits unique characteristics, such as persistent outliers, anomalies from a batch effect, and hidden relationships between features and their classes in the datasets, hence improving classification performance of current methods. The proposed method, called dynamic multi-hyperplane partitioning (DMP), learns the model by using subclassifiers, which are random in number and each of which uses multiple hyperplanes for decision boundaries. We also develop a method to transform samples to improve classification performance of DMP. We prove that, under a mild condition, accuracy of DMP is as good as or supersedes that of support vector machine (SVM). We test DMP on comprehensive datasets, which span diverse fields of applications, and compare accuracy, sensitivity, specificity, F-measure, and the receiver operating characteristic of DMP to those of competitive baselines, including SVM, random forest, Bayes classifier, gradient boosting tree, and deep-belief nets and neural nets. From the comparison, the proposed method is most accurate in nine out of eleven datasets, when using the mean values alone for comparison. DMP achieves 100% accuracy, 100% sensitivity, and 100% specificity in three datasets. As a generalization, we perform statistical test of difference, at significance levels of 0.05, 0.01 and 0.001. From statistical tests, DMP is the most accurate or one of the most accurate classifiers in nine out of eleven benchmark datasets., and is not the most accurate classifier in the remaining two datasets. The DMP learning method is accurate, simple to implement, and does not require fine-tuning of parameters, making it attractive for binary classification. This research has practical applications and leads to a timely and accurate approach to binary classification in diverse fields.
A research of security in website account binding

More and more websites have allowed users to bind a third-party account, mobile phone or email address. Users can log in to different websites through the bound third-party account or mobile phone, or recover password via the bound email address. So security issues in the binding process should be highly valued. In this article, we investigated the security in the account binding process. We designed three attack models for different account binding methods, which are OAuth based third-party account binding, Quick Response Code (QR code) based third-party account binding, and mobile phone/email address binding. We assessed the risk of these three attacks on 43 selected websites. According to our assessment results, 11 websites have vulnerabilities in third-party account binding, 4 websites have vulnerabilities in mobile phone or email address binding. To alleviate the possible hazards, we provided defensive measures for each stage of account binding.
A Fault Analysis and Prediction of Aircraft Based on Association Rules and Weibull Distribution

In this paper, a fault analysis and prediction of aircraft equipment is proposed via the construction of association rules and the analysis of Weibull Distribution. Firstly, for the recorded data in the airborne detection system, the prefix path graph is introduced to improve the Apriori algorithm to further mine the association rules between the fault equipments with low and high supports. Then, the first failure time of the equipment with high support is recorded, and the reliability analysis model of the equipment is established according to the Weibull distribution. Finally, the results of reliability analysis model obtained from the association rules provide the theoretical basis for the maintenance program of aircraft. The experiments in aircraft airborne detection system verifies the effectiveness and practicability of the proposed method.
Analysis of the Curriculum Reform Method Based on the Combination of Computational Thinking and Engineering Thinking

The software design pattern is an important core course for software engineering. However, the traditional classroom teaching method only focuses on the teaching of technical knowledge, but ignores the importance of thinking ability. In order to develop students' "computational thinking" and "engineering thinking" ability to combine the Exploration curriculum reform teaching methods paper from the main body, teaching content, teaching methods and evaluation of the four aspects of the course, presents a concrete and feasible teaching development program that combines "computational thinking" with "engineering thinking".
Gamifying Balinese Local Story: Facilitating Gen Z in Learning English

Working with nowadays children, technology cannot be neglected to be involved in their learning.Gamification in education becomes very popular as one of the most effective methods in facilitating students' learning.Inserting gamification elements in Balinese Local Stories was the purpose of this R&D research.In order to develop a gamified Balinese local story, the ADDIE model was used.As a result, 5 stories had been developed in the form of application with the insertion of gamification elements, like points, badges, levels, and leaderboards.The products had been judged by ICT media expert and educational material expert.Based on the result of expert judgment rubrics, the products were categorized as excellent application.As an implication, these media can be used to facilitate students in learning English.
DEVELOPMENT OF REFLECTION AS A COMPONENT OF PROFESSIONAL SUBJECTIVITY IN THE PROCESS OF TEACHING FUTURE TEACHERS

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Making Large Ensemble of Convolutional Neural Networks via Bootstrap Re-sampling

The ensemble of Convolutional Neural Networks (CNNs) is known to be more accurate and robust than the component CNNs models. Along with the development of a fast training method, current research has managed to make an effective ensemble of several CNNs models and require no additional training cost. However, when the ensemble size of CNNs is further increased, it is hard to observe a corresponding performance enhancement. According to the generalization capability analysis of CNNs, this phenomenon can be explained by the oversaturation of model capacity and the close correlation among the component CNNs, especially when the CNNs are trained within the same dataset. To address this problem, we propose to train CNNs on re-sampled bootstrap datasets. Extensive experiments demonstrate the bootstrap re-sampling is effective for a large ensemble size (up to 80). Besides, benefiting from the usage of the bootstrap re-sampling technique, we can also have an unbiased estimate of the standard deviation of the ensemble output.
Manajemen proyek Sistem Informasi Penggajian Berbasis Web

Project management is a strategy that needs to be done in achieving the efficiency and effectiveness of a company. Developments in the era of technology in this period are in line with the development of SMEs engaged in the field of karawo craft services, such as Rumah Karawo. The project planning can be prepared using Work Breakdown Structure (WBS). Project management can also be used to estimate the project acceleration (crasing) at Karawo House. With the preparation of a good project management, it can be estimated the time and cost needed to run the project, so as to minimize cost losses due to the possibility of project overturning. The development of a project management plan carried out using a waterfall.
Klustering Jumlah Penumpang pada Halte Bus Rapid Transit Kota Tangerang

Bus Rapid Transit (BRT) Trans Tangerang is a local public transportation system developed in the main corridor of the Tangerang City area as well as a feeder for Transjabodetabek and rail transport. BRT Trans Tangerang is one part of the Bus Rapid Transit program which is implemented and launched by Department of Transportation. The BRT Trans Tangerang system began operating at the beginning of December 2016. Some problems faced by Trans Tangerang Bus Rapid Transit such as the number of passengers that need to be increased to reduce congestion in the city of Tangerang and the placement of the right bus stops to attract passengers. Therefore, to overcome this problem, data and information about BRT Trans Tangerang are needed to find patterns of passenger distribution. The process of finding this information can be done by using data mining method. Within this method, there is a clustering technique which is useful to clustering all data in groups which have similar data. The algorithm used to classify the data is called simple k-means algorithm. In this study, all the data will be clustered into five cluster. The clustering results have almost the same nature between the data in one cluster, namely the total number of passengers per month, so that by performing clustering characteristics, knowledge of the busy schedule of passengers in one day can help related parties to anticipate the density of passengers on certain days.
Design of Lightweight AES Algorithm Based on Masked Lookup Table

With the development of information and communication technology, block cipher algorithm represented by AES algorithm has been used more and more widely. This design optimizes the hardware implementation of AES algorithm, mainly including: using T lookup table to realize multiple operations in round unit, ameliorating the T lookup table by using fixed value masking to improve the safety, designing a structure of inner-round loop structure and completely expanded structure, and using ISE to synthesize the AES algorithm module on Virtex-6 platform. As a result of experiment, the inner-round loop structure takes up 410slices+136BRAM, and the completely expanded structure takes up 2492slices+732 BRAM. The consumption of slices increases by only 7%-10%, and can achieve 51.2Gbps throughput under 400MHz clock. Finally, the security analysis and DPA experiments show that the fixed value masking scheme in this design improved the security of AES algorithm, and can resist SODPA.
Two Useful Discrete Distributions to Model Overdispersed Count Data

The methods to obtain discrete analogues of continuous distributions have been widely considered in recent years. In general, the discretization process provides probability mass functions that can be competitive with the traditional model used in the analysis of count data, the Poisson distribution. The discretization procedure also avoids the use of continuous distribution in the analysis of strictly discrete data. In this paper, we seek to introduce two discrete analogues for the Shanker distribution using the method of the infinite series and the method based on the survival function as alternatives to model overdispersed datasets. Despite the difference between discretization methods, the resulting distributions are interchangeable. However, the distribution generated by the method of infinite series method has simpler mathematical expressions for the shape, the generating functions and the central moments. The maximum likelihood theory is considered for estimation and asymptotic inference concerns. A simulation study is carried out in order to evaluate some frequentist properties of the developed methodology. The usefulness of the proposed models is evaluated using real datasets provided by the literature.
GOOGLE SLIDE DAN QUIZIZZ DALAM PENGEMBANGAN BUKU AJAR ‎ELEKTRONIK INTERAKTIF (BAEI) MATEMATIKA

This study aims to determine the attractiveness and feasibility and effectiveness of learning implemented using interactive electronic textbooks (BAEI) assisted by Google slides and quizizz on the matrix material. This research method is research and development (R&amp;D) with the Borg and Gall development model. There are 10 stages in this development namely 1) Potential and problems, 2) Data collection, 3) Product design, 4) Design validation, 5) Design revision, 6) Product trial, 7) Product revision, 8) Trial usage. 9) Product revision, 10) Mass production. Data collection instruments used were questionnaires given to material experts and media experts to determine product viability, and were given to students to find out the attractiveness of products that had been developed as well as pretest and posttest test instruments. The results of data analysis obtained from material experts and media experts stated that teaching materials developed were feasible to be used by obtaining "Valid" criteria with an average score of material experts of 3.76 and media experts of 3.48. Then the students' response to the electronic textbook (BAEI) in small group trials and large group trials (field) obtained the criteria of "Very Attractive" with the average score on the small group trial of 3.28 and the average results the score of large groups (field) is 3.49. The results of the effectiveness test analysis using effect sizes on the pretest and posttest obtained an average score of 0.72 and included in the medium category.
Penerapan Metode Filter Gabor Untuk Analisis Fitur Tekstur Citra Pada Kain Songket

Songket is a traditional Malay and Minangkabau woven fabric in Indonesia, Malaysia and Brunei. Songket is classified in the brocade woven family. Songket is hand woven with gold and silver threads generally worn at official occasions. The purpose of this study is to analyze the texture of songket fabric by using gabor filters. The results of the study stated that the texture output that appeared was strongly influenced by the magnitude of the frequency parameter values and the orientation of the image degrees. The greater the frequency value given, the results of the test use look brighter and blurry. Therefore the frequency value on the middle scale (f = 0.176) is considered the most appropriate for texture analysis. In addition to the frequency of orientation parameters are also able to show a tendency towards the texture in a certain direction. From the appearance of this fabric texture, the area suspected of having a good texture on the songket cloth.
Mitigation for Hawser‘s Short Fatigue Life on The Study of The Fatigue Life Prediction of Hawser in Single Point Mooring (SPM) at Tuban Fuel Terminal

One of the vital components of SPM System is Mooring Hawser. Mooring Hawser is mooring lines that used to anchor the tanker ship that are berthed at Single Point Mooring (SPM) fuel terminal to loading or offloading the fuel oil. The incident of broken hawser unexpectedly due to short fatigue life that occurs on hawser when tanker ship that is anchored at SPM 150.000 DWT at Tuban Seas, East Java, Indonesia is the basis of this study for mitigation and replace of new hawser. This study calculates fatigue life of the hawser by using numerical simulation approach and Palmgren-Miner Methods. the hawser variation that conducted is only at the size of the outside diameter, namely: 0.144 m, 0.152 m, and 0.160 m. The material properties of the hawser in this study are Nylon Polyamide PA66. Numerical simulation consist of two steps: Hydrodynamics diffraction numerical simulation is used to obtain response (RAO) of tanker ship and SPM, and hydrodynamics time response numerical simulation is used to obtain effective hawser tension time history in 3600 second time simulation. By using the S-N Curve of Nylon Polyamide PA66 that is obtained from Jernej Klemenc, Andrej Wagner, and Matija Fadjiga (2011) as the basis to calculate fatigue life prediction of three variations in the outside diameter of the hawserwith Palmgren-Miner methods. The calculation result of new hawser fatigue life = 57.40536 Months or 4.718249 Years of Effective Berthing Time. The new hawser use outside diameter variation = 0.152 m to replace the previous hawser.
Experimental pairwise entanglement estimation for an N-qubit system

Designing and implementing algorithms for medium- and large-scale quantum computers is not easy. In the previous work, we have suggested, and developed, the idea of using machine learning techniques to train a quantum system such that the desired process is “learned,” thus obviating the algorithm design difficulty. This works quite well for small systems. But the goal is macroscopic physical computation. Here, we implement our learned pairwise entanglement witness on Microsoft’s Q#, one of the commercially available gate model quantum computer simulators; we perform statistical analysis to determine reliability and reproducibility; and we show that after training the system in stages for an incrementing number of qubits (2, 3, 4, ...) we can infer the pattern for mesoscopic N from simulation results for three-, four-, five-, six-, and seven-qubit systems. Our results suggest a fruitful pathway for general quantum computer algorithm design and for practical computation on noisy intermediate-scale quantum devices.
Building Smart Classroom of Combinatorial Mathematics Based on PBL Teaching Model

With the prevalence of artificial intelligence and the continuous development of information-based teaching, the emergence of smart classrooms has provided a new teaching environment for classroom teaching. As a new and efficient teaching mode, smart classroom has entered schools. Based on the classical PBL teaching method, this paper attempts to construct the question-driven smart classroom of combinatorial mathematics, and shares some teaching experience and experience from the aspects of teaching preparation, teaching implementation and teaching evaluation.
Research on Relevance Analysis and Clustering Algorithms in College Students' Academic Performance

Aiming at the problems of contemporary college students' academic achievements, the K-means clustering analysis algorithm is used to analyze the correlation between library learning behavior and academic achievement GPA. The experimental results show that students' academic performance evaluation should be based on many factors and put forward Suggestions for improving college students' academic performance.
Pronominal Participles with Dependent Words: The Codified Standard and Uncertainties Surrounding It

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DAPS: A Decentralized Anonymous Payment Scheme with Supervision

With the emergence of blockchain-based multi-party trading scenarios, such as finance, government work, and supply chain management. Information on the blockchain poses a serious threat to users’ privacy, and anonymous transactions become the most urgent need. At present, solutions to the realization of anonymous transactions can only achieve a certain degree of trader identity privacy and transaction content privacy, so we introduce zero knowledge proof to achieve complete privacy. At the same time, unconditional privacy provides conditions for cybercrime. Due to the great application potential of the blockchain in many fields, supporting privacy protection and supervision simultaneously in the blockchain is a bottleneck, and existing works can not solve the problem of coexistence of privacy protection and supervision.
EUROPEAN FOREIGN LANGUAGE TEACHING POLICY WITH THE USE OF TECHNOLOGY

Abstract&#x0D; For the past few decades the use of technology has become essential to every kind of activity in everyday life for everyone all over the world. Consequently, today the use of technology is an indispensable part of the educational practices both inside and outside of the classroom settings. Specifically, it is an effective asset in the foreign language teaching process providing learners with various opportunities to improve their language skills. This study focuses on strengthening the European policy of teaching a foreign language through the use of technology both inside and outside the classroom context for teachers in service, and training them to clarify and receive current trends and developments in the use of technology for their professional purposes. The method of the study was qualitative via the document analysis. The result of the study indicated that the European policy of teaching a foreign language promotes the use of technology to achieve the desired goals.&#x0D; Keywords: European foreign language teaching policy, promote, information and communication technology, classroom context