Reviewerly/exHarmony huggingface dataset:
Implementation of Backpropagation Method for Identified Javanese Scripts

Abstract Literacy is one important component in a culture, one of which is Javanese culture. Javanese script is used as the main script that is used daily by most people in Central Java. Along with the development of human civilization and the expansion of global life, Javanese script began to be abandoned, even by the Javanese themselves. The use of Javanese characters is reduced because of the difficulty of learning Javanese characters themselves. Java character sets consist of basic characters, numbers, complementary characters, and so on. Javanese script is a traditional Indonesian script known as Hanacaraka or Carakan. Backpropagation is a systematic method of artificial neural networks using supervised learning algorithms and is usually used by perceptron with multiple screen layers to change the weights in the hidden layer. Text recognition application in alphabetical letters with neural networks. In the research we made, the training results of this application are good, because it can recognize letters well, the maximum characters that can be read by the application are 128 characters [Latin characters], based on ASCII code pages, this text recognition application can recognize letters and numbers, namely AZ and 0-9 with a percentage of success of up to 90%, Input characters to teach on the form train can only teach 1 character only.
Action Permissibility Prediction in Autonomous Driving through Deep Reinforcement Learning

Abstract This paper proposes a new nature based on deep deterministic policy gradient for deep reinforcement learning in continuous state and action space, which can greatly accelerate the emergence of artificial intelligence training and solving problem: state-action permissibility. The proposed method is integrated into the latest DDPG algorithm to guide its training and is applied to solve the lane keeping (steering control) problem in autonomous driving or automatic driving. Finally, the TORCS which is the open racing car simulator simulation software builds various simulation environments, including different tracks to verify the effectiveness of the algorithm. The results show that the proposed method can significantly speed up the algorithm training speed of the lane keeping task.
The United States and global regulation of convertible virtual currencies

The regulation of convertible virtual currencies (for instance Bitcoin) is an area both of global cooperation and global competition. On the one hand, virtual currencies create serious problems of payment for illegal transactions, money laundering, tax evasion, and consumer fraud. On the other hand such currencies, have the potential to lower the costs of commercial and consumer transactions and to facilitate international trade. Both dealing with the problems and realizing the potential of virtual currencies require international cooperation.There is no uniformity in national legislation on virtual currency. A recent survey of over 100 countries showed a wide variation in both the amount and methods of regulation 2 . While, at this stage, experimentation with various types of regulation may help discover better ways to deal with this currency, on the other hand, there is a real danger that some countries will be come unregulated virtual currency havens where the worst aspects of virtual currency can flourish.This article will look at United States law, and also at existing and needed international cooperation in the areas of taxation, investor protection, consumer protection, monetary regulation, and crime prevention.
Gesture Vocaliser using leap motion controller

In present-day societies, talking is the main form of communication between humans. Different thoughts that are shaped in the human psyche are conveyed by discourse through the form of words, expressions, and sentences by applying some appropriate syntactic rules. One of the major challenges for people with hearing impairment is their fettered communication with the outside world. Deaf people make use of sign language or gestures to convey their thoughts and to make understand what they are trying to say but it is impossible to understand or comprehend for a person who does not understand sign language. Limited access to technology owing to their inability to communicate has a significant impact on their quality of life.American sign language is the most standardized and famous sign language used by ill abled people throughout the world for communication. We propose a gesture recognition system called ‘Gesture Vocaliser’ which detects American sign language alphabets (ASLA) as gestures. This system aims to provide high reliability and fast response. Upon showing these signs the gesture detection system detects the sign shown with the help of a classifier. The gesture detection system consists of a vision sensor which uses tracking technology to track the hand gestures. Whenever the proposed system senses any gesture, it converts these gestures into text, which is then converted into an audio message. There is a reverse phase in which human speech is recognised as a text and is then converted into sign language gestures for each corresponding character.
A novel numerical function optimization framework: campaign based optimization framework

Abstract This paper proposes a new optimization framework: campaign optimization framework (COF), which is based on the historical results of traditional swarm intelligence algorithms and uses two different campaign rules to get better solutions. Firstly, the candidate solution set is generated by running the swarm optimization algorithm. Secondly, cross campaign rule (CCR) or increment campaign rule (ICR) is used to update the candidate solution set. The campaign rule describes the steps to get better solutions. In CCR, the better solution is obtained by combining the variable bits of two randomly selected solutions. But in ICR, it is generated by every variable bits’ optimal pools. Then, the best candidate solution is optimized by swarm optimization algorithm again. Finally, the proposed framework is tested on two well-known benchmark functions. Through the analysis of the experimental results, the proposed algorithm is compared with traditional swarm optimization algorithm. And two campaign rules are compared in terms of results and optimization time dimensions.
Zero-Shot Learning on Human-Object Interaction Recognition in Video

Recognition of human activities is an essential field in computer vision. Much of human activities consist of humanobject interaction (HOI). A lot of successful works has done on HOI recognition and achieved acceptable results, but they are fully supervised and need to training labeled data for all HOIs. The space of possible human-object interactions is huge, and listing and providing training data for all categories is costly and impractical. We tackle this problem by proposing an approach for scaling human-object interaction recognition in video data through the zero-shot learning technique. Our method recognizes a verb and an object from video and makes an HOI class. Recognition of the verbs and objects instead of HOIs allows the identification of a new combination of verb an object as a new HOI class that not seen by the recognizer model. We introduce a neural network architecture that can understand video data. The proposed model learns verbs and objects from available training data at the training phase, and at test time can detect the pairs of verb and object in a video, and so identify the HOI class. We evaluated our model by recently introduced charades dataset which has lots of HOI categories in videos. We show that our model can detect unseen HOI classes in addition to the acceptable recognition of seen types. And so more significant number categories are identifiable than the number of training classes.
STABILITY OF A SMART WALKER IN FALL RELATED EVENTS

The development of a gait disorder leads to the loss of the ability to walk and increases the frequency of fall events. To help improve the lives of people affected by reduced mobility and return the patient’s own dependency and confidence, smart walkers (SW) are used to empower the user’s residual capacities and promote functional recovery. An example presented in this paper is the ASBGo Smart Walker, a customized motorized rehabilitation tool that provides an innovative combination of real-time multimodal sensory information. The design of this augmentative device is centered on safety and stability, both fundamental to provide rehabilitation to the affected individuals. In this paper, it is presented an assessment of the ASBGo Smart Walker’s stability during forward and lateral falls. To evalute if the SW has the ability to support the patient during a fall and not overturn, leading to fatal falls, theoretical stability tests were performed. These tests proved and verified the safety of the ASBGo SW, in most of the conditions and situations when the device is handled. Nonetheless, in order to minimize fall-related impact it is proposed in future work the implementation of prevention methods and strategies.
Whatsapp Messenger Among Higher Education Students: A Study on Whatsapp Messenger Usage for Project Learning

Teaching learning process at universities and other higher educational institution have advanced from traditional lecturing or one direction learning to group work and project learning which involving technologies. In recent years, educational institutions have modified its learning processes by using networking technologies in conducting their group or project learning. This research is aimed to investigate the usage WhatsApp Messenger among higher education students for Project Learning. Several factors will be measured such as student's attitudes and competencies towards WhatsApp for project learning. This study was conducted in higher education institutions which applies project learning and students who used WhatsApp. This study adopted a quantitative approach. Researcher will employ survey for this study in which the researcher will gather accurate information and generalize definite research results. A questionnaire was designed to collect information to a sample of population. .
THE EFFORTS OF KING ABDULLAH II BIN AL HUSSEIN TO PROTECT ISLAMIC SANCTITIES

&#x0D; &#x0D; &#x0D; The purpose of this study was to present the efforts of King Abdullah II to protect the Islamic shrines, and this was done using a historical approach and a descriptive analytical approach that identifies the origins of the Hashemites and their ongoing efforts to restore the Islamic shrines, then it was first identified and the second reconstruction of the Hashemites. Finally, third, King Abdullah II's efforts were made to monitor the Hashemite ancestors in restoring and protecting Islamic and Christian holy sites, and at the end of the study, potential outcomes of King Abdullah II's efforts to restore and protect Islamic holy sites were identified. He called for a series of results, the most important of which is that King Abdullah II reiterated his real and practical interest in restoring and protecting Islamic holy places after the campaign of his Hashemite ancestors.&#x0D; &#x0D; &#x0D;
3D Nasal Magnetic Resonance Image Registration by Maximization of Mutual Information

Abstract The magnetic resonance image (MRI) is widely used in medical treatment, which is harmless for human body. However, more noise than the CT image sometimes can be a problem when doctor focus on details of some narrow structure of human body such as nasal. It is necessary to process the MRI like image fusion before using it. Subjects have to move head during a few MR scans. Image registration can help all corresponding points find their own correct position, so that it can be processed and give us more information from not only one time scan. Mutual information is a good mathematics tool in statistics and information theory. It can describe the relationship between input signal and output signal. In this paper, they are reference image data set and float image data set, and the process between them are some little bit head move and some other influence during scanning. The rigid body transformation is used to reduce the impact of head move because the nasal consisting of bones almost don’t changes shape during scan. Registered images from another scan and reference image can get together to be used in image fusion and reconstruction.
The Need and Focus of Transforming Vocational Education Management at the Regional Level

The paper focuses on the importance of vocational education for the development of industry, IT development of society, changes in business processes and industrial technologies, solving problems of state regulation of the economy, changes in the social sphere, and environmental aspects of the development. Appropriate staff assistance in these areas is necessary. The increasing complexity of technical objects and technologies leads to the rise in both material and intellectual costs. The success of new projects is largely determined by the skills of foresight and strategy. In this regard, the formation of an effective regional model of staffing becomes urgent, which requires appropriate management decisions. Regional enterprises are ready to cooperate with educational institutions for the organization of practice-oriented training and internships. However, in the system of long-term interaction regional producers occupy the position of the consumer rather than the customer toward the training system today. There is no qualitative description of the requirements for future graduates, which would allow universities to modify the content of educational disciplines and the key features of practical training. There is no effective formation of project student groups to perform work and achieve a specific result of enterprise orders. In this regard, we propose to reconsider the management model of functioning and strategic development of educational institutions based on long-term cooperation with enterprises of the real sector of the economy, and to improve internal processes of achieving strategic goals.
Dialogue Policy Optimization Based on KL-GAN-A2C Model

Reinforcement Learning (RL) is a promising research direction in dialogue policy optimization (policy learning). In the Adversarial A2C model dialogue policy optimization process, the Actor uses a fixed step size to update the policy, which is prone to frequent oscillations, so that the convergence speed of the policy learning cannot be guaranteed. For overcoming, this shortcoming, this manuscript proposes the KL-GAN-A2C model based on the Adversarial A2C framework. The model uses KL divergence to measure the probability distribution difference between the 'new' and 'old' policy, and automatically adjusts the learning step size of the Actor according to this difference, thereby ensuring that the dialogue policy is updated to the maximum extent within a reasonable range. The experimental results show that the KL-GAN-A2C effectively improves the frequent oscillations in the process of Actor learning, accelerates the convergence speeds of policy learning, and has better performance in dialogue policy optimization.
Lower resources of spoken language understanding from voice to semantics

Abstract Spoken language understanding is traditionally designed as a pipeline consisting of multiple components. First, the speech signal is mapped into text through the automatic speech recognition module, and then the natural language understanding module converts the recognized text into structured data, such as domain, intention and slot value. Usually these modules are trained separately. End-to-end speech comprehension, on the other hand, derives structured data directly from speech through a single model. However, end-to-end spoken language understanding based on a large amount of training data is difficult to achieve in different fields and different groups of people. For this reason, we introduced end-to-end oral comprehension based on pre-training with low resources and combined it with capsule vector. The experimental results show that the oral comprehension of this model with low resources is robust under different data sets.
A Lossless Joint Image Compression Using Wavelet Decomposition and Hierarchical Tree Encoding

Wavelet decomposition and hierarchical tree encoding can be used to achieve joint lossless image encryption and compression simultaneously. It is done on the basis of BLAKE-2 Hash algorithm, Integer Wavelet Transformation (IWT) and Set Partitioning In Hierarchical Trees (SPIHT) encoding. BLAKE-2 Hashing algorithm is used to generate sensitive keys from the input image and it results different key values for different images. BLAKE algorithm is very sensitive to changes occurred in the input. In IWT, images are decomposed in to various layers and hence are more immune to attacks. One of the most powerful image compression algorithm used to produce an embedded bit stream form that has the best reconstructed images which shows a significant perceptual improvement as well as an increased PSNR is SPIHT. SPIHT encoding never uses a code book and hence there is no burden to send the coded book while transmission. By combining all the three methods we obtained a decrypted image with high security, good lossless compression performance, high PSNR value and a better quality factor.
Afore, The Measuring Instrument in South Nias Culture

Humans are called as homo economicus because they are able to count and fulfill their economic needs. The process does not just happen in human life, but based on experience, demands and certainly because of the knowledge possessed by the community. This ability becomes a science that deserves appreciation. The results of these cultural sources are the result of community technology that must be preserved as a local wisdom. Afore is a measurement tool in South Nias community and as a source of cultural technology that the community needs be preserved. The technology of society as a proof of civilization and has a calculation tool that when converted to modern mathematics has almost the same size. The results showed that the afore gauge was the traditional measurement tool for the people of South Nias used in measuring the unit of weight (kg) in this case determining the price of the weight and quantity of the pig. The smallest size in afore is kudri. If in custom, the smallest unit of measurement afore starting from dua zo'e, dua zo'e amatona, tölu naso'e, tölu naso'e amatona, öfa zo'e, öfa zo'e amatona, otu öri, dua alisi, tölu alisi, öfa alisi, lima alisi, önö alisi, fitu alisi, walu alisi. The afore measuring instrument for the people of South Nias is a tool for transactions. Because afore, in the form of arithmetic operations of addition, subtraction, multiplication and division. Thus, it can be concluded that the people of South Nias have a source of cultural knowledge technology as local knowledge and local wisdom that is continuously preserved. Local knowledge should be inherited from the ancestors of South Nias, namely afore used as a means of buying and selling and economic transactions with local wisdom.
Extremity Extraction Based on Curvature with Skeleton Filtering and the Ability of Recognizing of Hidden Features Human Pose Representation

Silhouette border's extremities can be considered as describing features for human postures. Using of extremities for posture representation, and hence action recognition, is a simple and time efficient method that can also reduce the detection error rate. But unfortunately, popular extremity extraction methods e.g. star skeleton methods, encountered with enormous faults. This paper proposes a new method for extremity extraction with minimum error rate. First of all, curvature is introduced as a feature that can be used for extraction of candidate extremities. Since, the curvature is a boundary feature, it is insensitive to posture situations. Two filtering steps are then applied for minimizing wrong features. Since some of features may be blocked by occlusion a prediction step based on previous frames is employed. Pose representation is then carried out using a multi layer perceptron neural network. Promising achieved result verified the effectiveness of the proposed method. Experimental results demonstrate the privileged performance of the proposed algorithm to extract the extremities and so the human posture against the best reported works.
Development of Risk-Oriented Thinking for Sustainable Functioning of the Technosphere

Abstract The increasing dependence of the mankind on technical systems makes us a “risk society.” Therefore, in order to minimize consequences of anthropogenic activity those specialists who have access to complex technical systems need to develop advanced risk-oriented thinking. The purpose of this study is to formulate and clarify the concept of “risk-oriented thinking” and substantiate integration of the systemic and the competency-based approaches. According to the authors hereof, the use of the Perrow model is the most effective educational condition of development of risk-oriented thinking in future engineers. Study results include both a definition of the “risk-oriented thinking” and criteria of the advanced risk-oriented thinking.
Radio Anomaly Signal Recognition Methods Based on Clustering

Abstract Identifying radio anomalies is one of the main purposes of radio monitoring. The current radio anomaly signal identification is mainly finished manually by the radiops, using professional radio knowledge and their work experience. However, because the anomaly signal is hidden in the “massive” data, accompanied by a large amount of noise, and also data imbalance, the anomaly signal is difficult to find. In this paper, we combine the data unevenness processing method SMOTE and the (guorong: cluster detail) to identification the anomaly signal during radio monitoring. Experimental results show that our method can improve the efficiency of existing radio anomaly signal recognization. Moreover, our experiments also shows that data imbalance processing plays a key role in anomalyq signal recognition.
Analysis of numerical series of moving homogeneous video images

The article considers the problem of identifying the most significant properties of the numerical series of pixels of a moving video image in order to develop a mathematical model. The development of a mathematical model applied to a moving paper mass in the future will improve the parameters of the functioning of the paper machine. The problem of forming a mathematical model is solved by using and singular decomposition of numerical series (SSA method), represented by pixel intensity values within a given video sequence. By isolating the trend, harmonic and random components, it is possible to study the properties of the numerical series. As a result of the singular decomposition, it is established that the eigenvectors of the decomposition do not have a trend component, but contain periodic components and a random component within the framework of the accepted hypothesis, which is well approximated by the RSS model.
The Impact of English EFL Technology PowerPoint in Learning Speaking for English Pre-Service Teacher

Abstract Language is a communication tool to convey ideas or opinions and feelings to others. Through language, people can be interconnected, share, learn from each other, and improve their intellectual abilities. The ability to communicate in English is very crucial in the world of work. One of the abilities demanded by alumni of English education study programs is the ability to communicate in English. So far, based on the experience of researchers while teaching, there are still students who are unable to speak in public or make English presentations. They have less confidence to do it. The fourth-semester students of the English Education Study Program applied This English Presentation method. This research uses descriptive qualitative method to describe in public speaking by using English.