Reviewerly/exHarmony huggingface dataset:
Artificial Bee Colony-Based Associative Classifier for Healthcare Data Diagnosis

Data mining is likely to explore hidden patterns from the huge quantity of data and provides a way of analyzing and categorizing the data. Associative classification (AC) is an integration of two data mining tasks, association rule mining, and classification which is used to classify the unknown data. Though association rule mining techniques are successfully utilized to construct classifiers, it lacks in generating a small set of significant class association rules (CARs) to build an accurate associative classifier. In this work, an attempt is made to generate significant CARs using Artificial Bee Colony (ABC) algorithm, an optimization technique to construct an efficient associative classifier. Associative classifier, thus built using ABC discovered CARs achieve high prognostic accurateness and interestingness value. Promising results were provided by the ABC based AC when experiments were conducted using health care datasets from the UCI machine learning repository.
Developing a Highly Secure and High Capacity LSB Steganography Technique using PRNG

Being a modern way of secret messaging, steganography has become one of the trending topic for researchers and scientists. Using image in data secrecy is most common among all other ways of digital communication. In steganography, a carrier object behaves as a cover for the secret object such that intruders are not aware of its existence. Thus, it is important to create a steganography technique which is highly secure and also has a high data hiding capacity. In the technique proposed, each pixel has an enhanced capacity of 3-6 bits. This capacity is directed by the most significant bits of the indicator channel. Use of PRNG has made this technique more secure. The results achieved by the experiment signify the profoundness of this technique.
Interpreting Machine Learning Models (Decoding the Black Box)

Interpreting Machine Learning models is no longer a luxury but a necessity. In this session, we will explore practical techniques to interpret ML models using real time datasets across domains. Explainable AI is a developing field and many of the ideas presented here are pretty new.Below are the broad topics to be covered :•Feature Importances•Partial Dependence Plots•ICE Plots•Model Prediction Explanations with LIME•Building Interpretable Models with Surrogate Tree- based Models•Model Prediction Explanation with SHAP values
60‐3: <i>Invited Paper:</i> Machine Learning Approaches to Active Stylus for Capacitive Touch Screen Panel Applications

This paper introduces machine learning approaches on adding the stylus‐touch to the capacitive touch screen technology. The proposed schemes can discriminate the stylus‐touch from finger‐touch as well as no‐touch by means of classification algorithms using support vector machine and anomaly detection. The high frequency pulses are sent from a stylus to a touch screen and the receiver classifies the received sample sequences into three classes of no‐touch, finger‐touch, and stylus‐touch. In addition, some possible applications of data transmission and user authentication are demonstrated.
Ensuring the Blind Signature for the Electoral System in a Distributed Environment

We analyze several alternatives of blind digital signatures, for an electronic electoral system in a distributed architecture environment, in view of the persistence of blind signature problems in electoral processes. The objective is to recognize and propose an alternative of a blind signature scheme to improve privacy, confidentiality for the voter and in this way reduce any type of vulnerability with respect to the information of the same. The deductive method is used to summarize the information of the scientific articles studied. It results in a blind signature prototype based on algorithms to mitigate the vulnerabilities of voter information. It is concluded that, in order to guarantee privacy and confidentiality, several blind signature schemes must be implemented together to obtain the benefits of each of them, thus reducing the risks to which the voter's information is exposed in this process.
Calculus Teaching Method Based on Artificial Intelligence Application

Calculus plays a very important role in our research on artificial intelligence. From model analysis to method research, the research on calculus teaching method has been integrated into many aspects of our application of artificial intelligence. Calculus belongs to higher mathematics. It is precisely foreign science that uses the concept of calculus to solve the problems in the application of artificial intelligence. According to the current development of calculus and its application in the field of artificial intelligence, the basic teaching methods and contents have remained unchanged. Traditional teaching excessively pursues theoretical study and computational ability. So much of the current mathematics education is theoretical education, and there is no prominent application. Once theory and practice are combined, the shortcomings of students’ weakness in innovation ability are highlighted. The development of society needs more innovative and applied talents. Therefore, based on the deficiencies of back propagation (BP) neural network (one of the applications of artificial intelligence), this paper proposes the teaching reform of the course of Applied Calculus based on artificial intelligence.
Design and Implementation of Laboratory Fault Reporting System Based on Asp.net

With the continuous improvement of Internet status, The number of computer courses offered by colleges and universities has increased, The computer equipment in the laboratory has increased dramatically, The device problems caused are becoming more prominent. In order to solve the problems of missed hearing and untimely repair caused by traditional telephone reporting, In this paper, a laboratory fault reporting system is designed to serve the laboratory management, Speed up the speed of fault reporting, Optimize the process of repair report, And the data statistical analysis is carried out, Thereby improving the service level of the management team and forming a complete fault handling emergency mechanism, It can guarantee the normal progress of experimental teaching activities.
Interoperability Between Heterogeneous Multi-agent Systems Recommended by FIPA: Towards a Weakly Coupled Approach Based on a Network of Recurrent Neurons of the LSTM type

In this paper, we propose an approach that combines a CNN convolution neural network and an LSTM-type recurrent neural network to ensure interoperability between heterogeneous multi-agent systems recommended by FIPA (Foundation for Intelligent Physical Agents). FIPA has proposed a set of standards and specifications to maximize interoperability between heterogeneous multi-agent platforms. These FIPA standards and specifications focus on the communication aspect between agents based on the FIPA-ACL language, which is not sufficient to ensure interoperability between heterogeneous agents. Message content, and higher semantic levels that are more domain-specific (e.g. ontologies), must also be standardized while maintaining separation from the communicative level. Similarly, the lower level and the message transport must also be interoperable. In this context, we propose in this paper to integrate in the architecture of these systems, in a first step, a Broker that relies on the AMQP (Advanced Message Queuing Protocol) protocol, such as RabbitMQ, to ensure interoperability in the message transport level between agents. Secondly, a neural network composed of two layers: the CNN layer to extract the main characteristics of a message sent by an agent and send them to the second layer; a recurrent neural network of the LSTM type, which will process them characteristic by characteristic in order to interpret the content of the message.
Application of Photoshop Technology Based on Computer Graphic Design Software

With the continuous development of computer technology, both hardware and software equipment have undergone upgrading. At the same time, in order to meet the aesthetic needs of the public and the application needs of various industries, the computer is directly used in graphic design, which can give graphic design Bring new changes. Designers have gradually developed from the use of paper and pen as a carrier to use a variety of design software as a carrier to make the designed floor plan more in line with the aesthetic needs of modern people. From the design concept to the presentation of works, continuous innovation can be achieved, thereby expanding the scope of graphic design applications. This article is based on the use of Flash AIR programming and development + Photoshop technology to build a flat visual design platform to meet the needs of customers in the graphic design process. It has the aesthetics of graphic layout, shortens creative design time, improves work efficiency, safe and reliable system, and convenient operation.
A Counting Proof for When 2 Is a Quadratic Residue

Using the group consisting of the eight Möbius transformations x, – x, 1/x,−1/x, (x−1)/(x+1),(x+1)/(1−x), (x+1)/(x−1), and (1−x)/(x+1), we present an enumerative proof of the classical result for when the element 2 is a quadratic residue in the finite field Fq .
Arithmetic Precision Reconfigurable Convolution Neural Network Accelerator

Deep neural networks have demonstrated unprecedented results on core AI and computer vision tasks. They are typically executed on general purpose GPUs with large form factors and high power consumption, unsuitable for mobile deployment. We present a VLSI architecture that is able to execute quantized, low precision convolution neural networks (CNNs). Compared to high precision, our approach significantly reduces power consumption from memory access and increases processing speed at limited area budget, making it particularly suitable for mobile applications. We propose a dataflow with high data reuse rate specially designed for quantized models. To fully utilize low precision data, we also design a microarchitecture for subword parallel computing of low bit-length data, an on-chip memory hierarchy and data realignment flow for power saving and avoiding buffer bank-conflicts, and finally a corresponding processing element (PE) array. The architecture is highly flexible to suit various CNNs and re-configurable for low bit-length quantized models. We have implemented the proposed VLSI architecture in the TSMC 90nm cell library. At a hardware cost of 180KB on-chip memory and 1,340k logic gate counts, the implementation result shows state-of-the-art hardware efficiency.
A Computational Understanding of Classical (Co)Recursion

Recursion and induction are mature, well-understood topics in programming. Yet their duals, corecursion and coinduction, are still exotic and underdeveloped programming features. We aim to put them on equal footing by giving a foundation for corecursion based on computation, analogous to the original computational foundation of recursion. At the lower level, we show how the connection between the two can be strengthened through their implementation details in an abstract machine. At the higher level, we develop a syntactic equational theory for inductive and coinductive reasoning based on control flow. We also observe the impact of evaluation strategy: call-by-name has efficient recursion and strong coinductive reasoning, but call-by-value has efficient corecursion and strong inductive reasoning.
Manipulator Calibration-Free Hand-Eye Coordination Based on ADRC Under Eye Fixation

The forward kinematics of the manipulator and the Jacobian matrix of the manipulator are analysed and the D-H (Denavit-Hartenberg) method is used in manipulator modeling. The nonlinear relationship between the manipulator and the camera system is analyzed, and it is built into the form of ADRC (Active Disturbances Rejection Controller). The ESO (extended state observer) in ADRC is used to compensate the inaccuracy and unknown interference of system modeling, and realize the hand-eye coordinated control of the manipulator under the eye fixation. The feasibility and effectiveness of this method are verified by the simulation.
Compiling Czech Parliamentary Stenographic Protocols into a Corpus

The Parliament of the Czech Republic consists of two chambers: the Chamber of Deputies (Lower House) and the Senate (Upper House). In our work, we focus on agenda and documents that relate to the Chamber of Deputies exclusively. We pay particular attention to stenographic protocols that record the Chamber of Deputies’ meetings. Our overall goal is to (1) compile the protocols into a ParlaCLARIN TEI encoded corpus, (2) make this corpus accessible and searchable in the TEITOK web-based platform, (3) annotate the corpus using the modules available in TEITOK, e.g. detect and recognize named entities, and (4) highlight the annotations in TEITOK. In addition, we add two more goals that we consider innovative: (5) update the corpus every time a new stenographic protocol is published online by the Chambers of Deputies and (6) expose the annotations as the linked open data in order to improve the protocols’ interoperability with other existing linked open data. This paper is devoted to the goals (1) and (5).
Designing SignSpeak, an Arabic Sign Language Recognition System

Deaf and hearing-impaired individuals who communicate using sign language face several communication difficulties. Because the vast majority of people do not know sign language, the need for a sign language translator is growing significantly, especially for Arabic sign language (ArSL). Today, technology plays a significant role in people’s lives. Leap Motion technology can be used to address the aforementioned issues and improve communication between Saudi Arabia’s deaf and hearing individuals. In this study, we investigated the possibility of using a Leap Motion system to provide continuous ArSL recognition for two-way communication to improve communication between deaf and hearing individuals in terms of speed and independence. The system translates ArSL into spoken words for hearing individuals and transcribes spoken Arabic language into text for deaf individuals.
Partisipasi Masyarakat dalam Pengembangan Perpustakaan Perguruan Tinggi: Kajian Implementasi UU RI No. 25 Tahun 2009 Tentang Pelayanan Publik di Perpustakaan PTKIN se-Propinsi Jawa Timur

This study aims to determine form of collaboration between library and community while measuring level of utilization and participation of community in development of libraries. The community in this study can be Government Agencies, Corporations / Companies and Non-Governmental Organizations. There are five interrelated elements in library management concept that can be used as objects of cooperation in improving services, namely collections, Human Resources, users, services, and infrastructure. During this time main constraints of library are operational costs in procurement and development of both collections, human resources, and infrastructure. In library science, procuring collections can be done by buying, gifts, donations, and exchanges. Perhaps this is gap that can be used by librarians in procuring and developing collections in library. Librarians can collaborate with community in an effort to increase collections, HR and services without having to be constrained by lack of available funds. This is also implementation of RI Law No. 25 of 2009 concerning Public Services Chapter VI Article 39 paragraph 2 which states that the participation of community as referred to in paragraph (1) is realized in form of cooperation, fulfillment of rights and obligations of community, and an active role in preparing public service policies. This research was conducted by taking a sample of four PTKIN libraries in East Java Province namely UIN Sunan Ampel Surabaya, UIN Maulana Malik Ibrahim Malang, IAIN Kediri, and IAIN Ponorogo. The method of data collection is done by method of observation, interview, and questionnaire.
Convolutional Network for Image Steganography With Redundant Embedding

Image steganography is one of the secure methods of information communication. Based on deep learning, the steganography models have obtained better performance than those based on handcraft features, but they can not ensure absolute correctness when extracting bit message. To improve extracting accuracy, we propose a new redundant embedding method. Also, to improve robustness and security against steganalysis, we introduce generative adversarial training into our model. From the experimental results, our proposed methods reduce the extracting inaccuracy significantly while maintaining the capability of resisting steganalysis attack. What's more, our proposed methods can be easily generalized to cover images with different size and embedding capacity of different bit message length. Therefore, the proposed model can have a wider application in real use.
The Role of Human Resource Management Processes in Achieving Information Security: An applied Study on Saudi Government Universities

This study aims to reveal the reality of the Human Resources Management Units contribution to achieving information security at Saudi government universities by examining their compliance with the international standard of the Information Security Management System (ISO/IEC 27002:2013).&#x0D; The study was based on qualitative research methods, where a checklist was designed to collect the data needed for the study, using semi-structured interviews, direct observation, and documents examination used in Human Resources management units. The gap analysis method has also been used to analyse data in order to determine the range of compliance of the Universities Human Resources Management Units to the information security controls provided by the international standard (ISO/IEC 27002:2013).&#x0D; The study reached a number of results, the most important of which was the commitment of the participating universities in different rates ranging from medium to high in the application of the international standard (ISO/IEC 27002:2013) controls concerning human resources management processes (before employment, during employment, termination or change of employment).&#x0D; In the light of those findings, the study made several recommendations that guide universities towards full compliance with controls of that international standard in order to raise the level of the contribution of human resources management processes to achieve full information security.
TFPMS: Transactions Filtering Pattern Matching Scheme for Vehicular Networks based on Blockchain

An Intelligent Transportation System (ITS) aims to achieve efficiency of traffic by minimizing its problems, such as traffic congestion, road accidents, etc. It is not only limited to control traffic congestion but also enhances the safety and comfort of the commuters. For road traffic safety and efficient infrastructure usage, vehicles need to communicate with each other to disseminate information related to traffic. However, vehicles cannot directly communicate with each other and other infrastructure because of privacy and security concerns. In the proposed work, blockchain is implemented on Road Side Units (RSUs) that are used to provide reliable communication between vehicles. Furthermore, cloud and edge servers are used to tackle the storage issue. We proposed a Transactions Filtering Pattern Matching Scheme (TFPMS) to filter the transactions before sending them to the blockchain network. In this way, it saves storage space and reduces computational overhead of blockchain. Moreover, we are exploiting consortium blockchain to implement our proposed scheme. Simulations are performed based on the number of transactions and cost to achieve high-quality data sharing between vehicles, which result in a reduction in storage overhead as compared to the existing schemes.
Text Sentiment Analysis Based on Amazon Product Evaluation

This article expounds and demonstrates how to help the Amazon online products gain the favor of the users. It selects the user evaluation text from some Amazon products. It uses the methods of data analysis, coefficient of variation, literature review and questionnaire to select the relevant indicators. Nine factors are chosen as indicators such as average product score, total number of comments and number of helpful comments and so on. The user preference evaluation index system is established, and the weight is determined by swing weight method. Based on the theory and method of grey fuzzy comprehensive evaluation and text emotion analysis, a comprehensive evaluation model is established, and the evaluation results and suggestions are obtained.
Visual Methods for Sign Language Recognition: A Modality-Based Review

Sign language visual recognition from continuous multi-modal streams is still one of the most challenging fields. Recent advances in human actions recognition are exploiting the ascension of GPU-based learning from massive data, and are getting closer to human-like performances. They are then prone to creating interactive services for the deaf and hearing-impaired communities. A population that is expected to grow considerably in the years to come. This chapter aims at reviewing the human actions recognition literature with the sign-language visual understanding as a scope. The methods analyzed will be mainly organized according to the different types of unimodal inputs exploited, their relative multi-modal combinations and pipeline steps. In each section, we will detail and compare the related datasets, approaches then distinguish the still open contribution paths suitable for the creation of sign language related services. Special attention will be paid to the approaches and commercial solutions handling facial expressions and continuous signing.
A Kind of Soft Started Regulated Power Supply

The regulated power supply (the stabilized voltage supply) is an important device that can provide alternating current (AC) or direct current (DC) to various electronic equipment. At present, it can be used in most electronic devices and instruments. We need to use the direct current stabilized power it provided to make the equipment work normally. The AC power grid provides voltage with the effective value of 220V and the frequency of 50Hz. We need to use the regulated power supply to convert the power into stable direct voltage with a specific amplitude, so that the power can be applied to all kinds of appliances in our life. This paper studies the soft start voltage stabilizing circuit based on the integrated circuit LM317 through the simulation software of Multiuse. The whole power circuit is mainly composed of the transformer, the filter circuit, the rectifying circuit and the voltage stabilizing circuit. This kind of power supply has the advantages of small size, good stability and high cost performance. This paper mainly introduces the principle of the regulated power supply and how to realize it, and further analyses the working principle of specific hardware circuits and specific methods to realize their functions. After many times of simulation in the software, it is found that the power supply designed in this paper has flexible adjustability as well as good control effect. Therefore, this kind of power supply can be more widely used in electronic instruments, measuring instruments, other electronic control circuits and other occasions. According to the results, the function and index of this soft started regulated power supply circuit with the load function can meet the requirements of this experiment.