Reviewerly/exHarmony huggingface dataset:
ALGORITMA BACKPROPAGATION DALAM MEMPREDIKSI JUMLAH KENDARAAN BERMOTOR YANG MEMBAYAR PAJAK MENURUT JENIS KENDARAAN DI KABUPATEN BATUBARA

Tax is a source of funds for the state to overcome various problems such as social problems, improving welfare, prosperity of its people. In the Batubara district itself, the number of receipts of Motor Vehicle Taxes and the development of the number of motorized vehicles have increased but not offset by awareness of taxpayers, this is reflected in the amount of arrears and considerable fines at the Coal Samsat Office. Looking at these problems, a method that is effective in estimating the number of vehicles paying taxes in the Batubara district is needed. The data used is data from the Regency Statistics Agency. Coal through the website www.batubarakab.bps.go.id. The data is the number of motorized vehicles that pay taxes in the Coal district in the period of 2012 to 2017. The algorithm used in this study is Artificial Neural Networks with the Backpropagation method. Input variables used are 2012 data (X1), 2013 data (X2), 2014 data (X3), 2015 data (X4), 2016 data (X5) and 2017 data as targets with models training and testing architecture of 4 architectures namely 4-4-1, 4-8-1, 4-16-1, 4-32-1. The resulting output is the best pattern of ANN architecture. The best architectural model is 4-8-1 with epoch 3681, MSE 0.009744 and 100% accuracy. So that the prediction of the number of motorized vehicles that pay taxes is obtained in Batubara district.
The Establishment of a Modern Vocational Education System

The development level of higher vocational education reflects the industrialization level of a country. Vocational education in China originated from the career education model of the Westernization Movement. After the foundation of New China (in 1949), Chinese vocational education, influenced by the Soviet Union, focused on training professional and technical talents. With the increased demand for talents, a pluralistic pattern of government leading but relying on enterprises, including a dynamic role for industry and the active participation of social forces, has been put forward, forming a “dual-track and overpass” style modern vocational education system.
Reasoning About Cognitive Attitudes in a Qualitative Setting

We present a general logical framework for reasoning about agents’ cognitive attitudes of both epistemic type and motivational type. We provide a sound and complete axiomatization for our logic and we show that it allows us to express a variety of relevant concepts for qualitative decision theory including the concepts of knowledge, belief, strong belief, conditional belief, desire, strong desire, comparative desirability and choice.
Application of Adobe® Photoshop® CC 2018 for Identifying the Source of HP® Color Laser Printouts

In today’s digital world, printer forensics is one of themost important disciplines to reveal the authenticity of printeddocuments and track criminals. Digital steganographyis an advanced approach to secure color laser printing processes,but it cannot be applied to monochrome laser printers.Therefore, the identity of the machine used to print colorquestioned documents provides a valuable means for detectingforgery crimes in digital forensic labs and law enforcementagencies. Based on this, we introduced a new forensicmethod that unveils the steganography (hidden information)embedded in color laser printouts via an adopted preset inAdobe® Photoshop® CC 2018. This forensic tool can be appliedas a nondestructive and indirect tool for image processing.In the present work, printing, scanning, extraction, andmeasurements for the embedded tracking dots of candidatecolor laser printouts were conducted.Thirty-five HP® color laser printers were selected withdifferent and same models with different serial numbers andused to print a hundred color laser printouts.The defined coded dots matrix patterns that characterizedthe color laser machines of the HP® brand could clearly bedetermined.Therefore, this procedure could successfully be appliedto distinguish between various color laser printouts printedby HP® printers with a variant serial number in digital forensiclabs with a conclusive accuracy ratio attained to onehundred percent.
Impact of New Technologies in the Digital Libraries

The Digital library aims to provide access to information ‘on demand’ regardless of the location of the computer, where it is stored. The role of digital libraries in the present day information environment and new challenges and promises for library services especially in the India. A Digital Library is to be an electronic collection of real or virtual resources, which may also be available elsewhere. These resources must be whole works with which human can have a complete cognitive effective engagement. A Digital library may allow either online or offline access to the elements it organizes and houses, and may include multimedia as well as multilingual data. Although accessible online, a digital library is not identical to a website or a portal however while portals, specialized websites and search engines cover a wide range of subject areas, digital libraries are more narrowly focused around one or a specific group of disciplines. Digital libraries, moreover attach content specific and highly descriptive metadata such as, descriptors or keywords to describe each item in the collection. Therefore, searches in a digital library can produce more useful results, save time and effort in searching , and in the best of cases browsers may directly access the text or multimedia content for which they executive their search. Keywords: Digital Library, Quick Access, Digital Information collection, Multimedia data, High Speed Networks and Hypermedia. Cite this Article Nagu N. Bansode, Manohar Ganapati Shinde. Impact of New Technologies in the Digital Libraries. Journal of Advancements in Library Sciences. 2019; 6(Special Issue 1): 279s–283s.
Can We Trust Smart Cameras?

Technological advances have changed our conception of cameras as boxes that capture images into the notion of networked, smart devices that analyze their environment and trigger decisions. Since smart cameras have become key enabling components for cyberphysical systems, trust in these devices is gaining importance.
A New Constraint Satisfaction Perspective on Multi-Agent Path Finding: Preliminary Results

In this paper, we adopt a new perspective on the Multi-Agent Path Finding (MAPF) problem and view it as a Constraint Satisfaction Problem (CSP). A variable corresponds to an agent, its domain is the set of all paths from the start vertex to the goal vertex of the agent, and the constraints allow only conflict-free paths for each pair of agents. Although the domains and constraints are only implicitly defined, this new CSP perspective allows us to use successful techniques from CSP search. With the concomitant idea of using matrix computations for calculating the size of the reduced domain of an uninstantiated variable, we apply Dynamic Variable Ordering and Rapid Random Restarts to the MAPF problem. In our experiments, the resulting simple polynomial-time MAPF solver, called Matrix MAPF solver, either outperforms or matches the performance of many state-of-the-art solvers for the MAPF problem and its variants.
The Impact of Task Type and Scorer Factor on Writing Scoring in Chinese Writing Test

At present, international Chinese teaching has entered a new stage of connotative development. Improving the reliability and validity of Chinese proficiency test in listening, speaking, reading, and writing is one of the issues worthy of further discussion. This study investigates the impact of task types on writing score errors, and explores the most suitable task types and number of scorers for evaluating foreign students` Chinese writing ability. By using the analysis method of Generalizability Theory (GT) model and SPSS 22.0 UNINOVA program, the research group completed the G study. The results show that the writing ability of the subjects is the main factor affecting the writing score, and the scoring error caused by the scorer factor is greater than the task type. The D study shows that argumentative writing test is easier to achieve higher reliability, while narrative test has the lowest reliability. In addition, when the number of raters was 3, the generalizability coefficients of these 4 task types reached the ideal level of 0.7. In the end, this paper points out that argumentation should be the first choice for writing tasks of Chinese proficiency test above the intermediate level, and raters should be at least 3 in a group. Meanwhile, effective rater training should be carried out.
Improvement of Walking Motivation by Vibratory Display Powered by an Ankle-Worn Generation Device

We propose an ankle-worn power generation device that supplies power to a vibration speaker to improve walking motivation. With the walking motion of the user, the vibration speaker is driven. In this paper, we propose an interface of a wearable generator that obtains electric power from ankle movement during walking by means of attaching a device with power generation functions to the ankle, and we report the performance evaluation result of the ankle-worn power generation device. In addition, as a part of investigating factors that improve walking motivation, we also describe the results of a questionnaire on walking and its considerations, and the approach to the design-oriented aspects assuming scenarios for future use.
THE TASKS FOR THE OPEN REGIONAL ROBOTICS CHALLENGE “FAIRYTALE TOURNAMENT”

The article presents some tasks to be done by a participant while taking part in a robotics challenge. The tasks can be used while teaching robotics at school. Schoolchildren may have different levels of training. The tasks are divided in three categories due to their difficulty: Beginner, Amateur and Master. The tasks have been successfully tested while the open regional robotics challenge “Fairytale Tournament” being held. The challenge was held in 2018 by the Shadrinsk State Pedagogical University.
An Evaluation Framework for Virtual Articulatory Movements Based on Medical Video

An important aspect of a Speech tutoring aimed talking-head system (STTS) is the accuracy of produced articulatory movements. Little work has been done for the Articulatory movements' accuracy (AMA) evaluation in STTSs. Although subjective evaluation is reliable, it is time consuming and inconvenient. The traditional objective evaluation is comparing the motion of several points on the surface of the synthetic articulator to the Electromagnetic articulography (EMA) data which describes the motion of corresponding points on the articulatory surface of a speaker. The EMA information is too limited to describe the whole shape changing of deformable articulators for a speech process. To solve this problem, we propose a substantially different objective evaluation method based on a separately recorded medical video. The synthetic articulatory shapes in a speech process are compared to the corresponding shapes tracked from the medical video. This method is translation, rotation, and scaling invariant which allows the comparison of the shapes from the synthetic tongue and the medical images. The time difference problem of synthesis results and medical video is solved by introducing Dynamic time warping (DTW) to the proposed method. Experimental results demonstrate that our method has the ability to evaluate the deformation shape accuracy from an entire articulation process. The comparison results suggest that our method is more accurate than the traditional method especially for deformable articulators.
The GDPR and Its Application in IoT and Connected Cars Opportunities for Business and Competitivity

The General Data Protection Regulation (GDPR) is in force since May 25 2018. This has an important impact on the design and development of new technologies based on exploitation of data, in particular private data. Not complying with the requirements can have high financial consequences up to 4% of the worldwide turnover of a company as a fine. At first glance, GDPR seems to be a constraint. However the, this regulation offers also the opportunity to develop new services based on big data processing and become competitive in a domain, which is considered being the petroleum of the 21st century. The paper describes the impact and opportunities of the GDPR on the Internet of things (IoT) and connected cars by highlighting two examples:
PROFESSIONALLY SIGNIFICANT QUALITIES OF STUDENTS IN A HIGHER TECHNICAL EDUCATION INSTITUTION

The article is devoted to the problem of studying the professionally significant qualities of students in a higher technical educational institution, namely, Tyumen Industrial University branch in Nizhnevartovsk. The research problem is caused by the genuine interest of the influence of professionally significant qualities on the peculiarity of the individual under consideration (Akker, 1994). The contradictions between the individual characteristics of the development of personal qualities and professionally significant qualities are revealed in this work. It is noted that the person is the perfect value in the content of the subject. The considered approach gives the freedom to choose education, the purpose of which is to satisfy spiritual, educational, life, as well as cultural interests and needs of the individual, a humane attitude to the individuality, its formation and the possibility of realization in the cultural and educational environment. The study presents the results of a survey of students of the Tyumen Industrial University branch in Nizhnevartovsk to identify knowledge characteristics related to professionally significant qualities. Graphs reflecting the manifestation of these qualities of students in everyday life and learning activities are constructed. A comparative analysis of indicators of the presence of professionally significant competences of students and their manifestation in educational and extracurricular activities is presented. The research results, as a reflection of the manifestations of professionally significant competences in various socially significant activities, are tabulated.
Generalized Word Equations: A New Approach to Data Compresion

Let Σ be an alphabet. A generalized word equation, GWE for short, is a set of triples and pairs. A triple is in form (p, q, l) where p, q, l are positive integers. A pair is in form (a, i) where a ∊ S and i is a positive integer. A solution of a word equation e is any word w such that, for each triple (p, q, l) in e, w[p..p + l − 1] = w[q..q + l − 1] and, for each pair (a, i) in e, w[i] = a. If there is only one shortest solution w of e, then we say that e defines w. Observe here that if e defines w, then the solution set of e is {ws : s ∊ Σ*}. The triples and pairs of an equation e are called constraints. If an equation e defines a word w, we say that e is a compressed representation of w. Let G be a GWE with m triples and pairs defining a word w. There is an algorithm reconstructing w from G in O(m+ |w|) worst case time [1]. Therefore decompression is optimal. It is not difficult to prove that in simple modifications of GWE generalize LZ77, LZ78 and LZW algorithms. We consider a natural variant of GWE called pGWE and prove that, for a word w, it is a little more efficent and more general than LZ77 for a reversed word wR. Moreover, it can be proved that GWE approach generalizes the bidirectional scheme. We compared GWE with Straight Line Programs (SLP for short) [2, 3] and prove that if SLP for a word w is of length n, then there is a GWE defining w with n constraints. We are not aware of any reasonable simulation in the other direction. We propose a variant of GWE which compresses an input word w in O(|w|L2) worse case time where L is the longest repeating factor in w. This version was tested on files in Canterbury Corpus. It gives better results than gzip on text files and slightly worse on the other files. It is worth mentioning here that gzip is a result of 20 years studies on LZ77 so it is unfair to compare it with our approach. Our current best approach is significantly worse than bzip2 which is based on the Burrows-Wheeler transform.
An Ensemble Model for Multiclass Classification and Outlier Detection Method in Data Mining

Real life world datasets exhibit a multiclass classification structure characterized by imbalance classes.Minority classes are treated as outliers' classes.The study used cross-industry process for data mining methodology.A heterogeneous multiclass ensemble was developed by combining several strategies and ensemble techniques.The datasets used were drawn from UCI machine learning repository.Experiments for validating the model were conducted and represented in form of tables and figures.An ensemble filter selection method was developed and used for preprocessing datasets.Point-outliers were filtered using Inter quartile range filter algorithm.Datasets were resampled using Synthetic minority oversampling technique (SMOTE) algorithm.Multiclass datasets were transformed to binary classes using OnevsOne decomposing technique.An Ensemble model was developed using adaboost and random subspace algorithms utilizing random forest as the base classifier.The classifiers built were combined using voting methodology.The model was validated with classification and outlier metric performance measures such as Recall, Precision, F-measure and AUCROC values.The classifiers were evaluated using 10 fold stratified cross validation.The model showed better performance in terms of outlier detection and classification prediction for multiclass problem.The model outperformed other well-known existing classification and outlier detection algorithms such as Naïve bayes, KNN, Bagging, JRipper, Decision trees, RandomTree and Random forest.The study findings established ensemble techniques, resampling datasets and decomposing multiclass results in an improved detection of minority outlier (rare) classes.
Towards an Information Archetypes Framework: Exploring the Types of Information Used in Open Source Design Engagements

Abstract Across disciplines such as software engineering to architectural design, it is well acknowledged that the different types of information employed during the design process impacts the potential of the final design. However, a lack of understanding exists about how designers utilize and navigate the abundance of complex information types, making it difficult to develop design methodologies that support the development of competitive products and services. As part of an ongoing effort to develop an Information Archetypes Framework, this study focuses on identifying the emergence of information dimensions and archetypes during decision making. This was accomplished through a detailed analysis of interviews with designers who engage in open source work as part of their employment. The findings of this study provide empirical evidence of the types of information used during the design process, validates existing information archetypes, and identifies new archetypes that emerge from co-occurring information dimensions.
Standardized Reflection Transformation Imaging (RTI) for Documentation and Research

Reflection Transformation Imaging (RTI) is a powerful tool to capture the surface of an object for later examination [1]. We brought RTI to the next level regarding reproducibility, simplicity and image quality [2]. Besides the possibility to capture the surface topography, we can measure and reproduce materials composed of complex reflectance behaviours, with high colour and gloss fidelity. Full-featured cross-platform software for the creation and viewing of such enhanced RTIs has been developed and commercialized. The application allows simple interaction and comparison of RTI datasets. However, the crucial feature of RTIs is their interactivity and the possibility to individualize viewing configurations for specific surface examinations. In the context of image interoperability, it is essential to be able to describe such viewing configurations to ensure reproducibility, e.g.in case of collaborative work. The trend of linked open data shows that RTIs as well must follow open access rules. The success of standardized access to image data is demonstrated well by the international image interoperability framework (IIIF). In this paper, we address two issues: The importance of standardized web-access to RTI data as well as an approach to store and disseminate specific RTI viewing configurations.
Masquerade Attack Detection Through Observation Planning for Multi-Robot Systems

The increasing adoption of autonomous mobile robots comes with a rising concern over the security of these systems. In this work, we examine the dangers that an adversary could pose in a multi-agent robot system. We show that conventional multi-agent plans are vulnerable to strong attackers masquerading as a properly functioning agent. We propose a novel technique to incorporate attack detection into the multi-agent path-finding problem through the simultaneous synthesis of observation plans. We show that by specially crafting the multi-agent plan, the induced inter-agent observations can provide introspective monitoring guarantees; we achieve guarantees that any adversarial agent that plans to break the system-wide security specification must necessarily violate the induced observation plan.
FOR THE FANS OF THE SCRATCH PROGRAMMING LANGUAGE: MATHEMATICAL EMBROIDERY OF ASTROID

The article shows a method for constructing curves as envelopes of a family of lines in the Scratch environment. The clarity of the method allows it to be used in the classroom and in extracurricular activities in computer science in grades 5–6.
Multi-batch Reinforcement Learning

We consider the problem of Reinforcement Learning (RL) in a multi-batch setting, also sometimes called growing-batch setting. It consists in successive rounds: at each round, a batch of data is collected with a fixed policy, then the policy may be updated for the next round. In comparison with the more classical online setting, one cannot afford to train and use a bad policy and therefore exploration must be carefully controlled. This is even more dramatic when the batch size is indexed on the past policies performance. In comparison with the mono-batch setting, also called offline setting, one should not be too conservative and keep some form of exploration because it may compromise the asymptotic convergence to an optimal policy. In this article, we investigate the desired properties of RL algorithms in the multi-batch setting. Under some minimal assumptions, we show that the population of subjects either depletes or grows geometrically over time. This allows us to characterize conditions under which a safe policy update is preferred, and those conditions may be assessed in-between batches. We conclude the paper by advocating the benefits of using a portfolio of policies, to better control the desired amount of risk.
A Shallow Learning - Reduced Data Approach for Image Classification

Shepard Interpolation Neural Networks (SINN) lay a foundation addressing the flaws of deep algorithms, inspired by statistical interpolation techniques rather than biological brains it can be mathematically proven and the neuron interactions can be intuitively described. They also possess the ability to discriminate well with limited training data during the algorithm process. To enhance SINN from just regular vectorized images, we look to utilize hand designed and natural image features to help the SINN perform better on benchmark image classification data sets. We compare these input feature vectors using the SINN framework on three benchmark image classification test sets, showing comparable results to the state-of-the-art (SOTA) for a fraction of the computational and memory requirements due to SINN shallow learning ability.