Reviewerly/exHarmony huggingface dataset:
Low power membership function generator for interval type-2 fuzzy system

An analog type-2 fuzzy membership function generator is analyzed, while its low power features are demonstrated. Developed and designed to work as part of an energy-efficient type-2 fuzzy system (i.e. controller, neural network), it operates in current-mode, allowing multiple settings, such as: var iable shape, position, slope and size of the Footprint of Uncertainty. All these parameters can be updated/adjusted during actual operation, being suitable for real-time applications, even with online learning. The achieved robustness and flexibility of the architecture allow operation with different values of supply voltage and maximum degree of membership current. Simulations based on CADENCE software were performed to assess the functionalities. The circuit was prototyped in TSMC CMOS 0.18μm technology and experimental results show a power consumption of 72.56μW, 7.86μW, and 478.1nW when operating with power supplies of 1.2V, 1V, and even with 0.6V, respectively, much less than the nominal supply voltage of the TSMC CMOS 0.18μm technology (1.8V). These results attest the circuit is robust, low-power, functional and suitable for systems that require energy efficiency, presenting a high potential for practical implementations including those that require real-time dedicated hardware.
Drishti—Artificial Vision

Drishti is a computer vision and deep learning-based application developed using Python programming language for the sole purpose of envisioning the real-time environment by generating the natural language description of the real-time captured scenes. The primary objective of this project is to enable a visually impaired person to know about his or her environment in real time. In this, digital image processing is used to generate the annotations about the surroundings. To express the features, Python has been selected as an interacting language. For the ease of a user, GUI has been provided for their usage. Though the GUI has been operated and guided by Python script, there is no need for a person to know the language, for general usage.
The scientific library: The retrospective and modern term interpretation

The author investigates why the term “scientific library” may not be accepted as a separate class within the classification of libraries based on structural systematization. She also reviews the idea of the scientific library as seen by the national science in the 1930s when this phenomenon was first conceptualized. The concept by Dmitry D. Ivanov is examined; he made distinction between the two library processes: generation of library documents and their delivery to users. The author emphasizes the closeness of D. Ivanov’v ideas to her own interpretation of “the public library” concept. She concludes that the libraries of any structure (public or private individual) may support science though we may not identify a separate class of the scientific libraries within the general library classification based on structural systematization. However, the author does not rule out building an isolated classification where the concept of “the scientific library” will be divided into two types in accordance with the concept structure, namely “the public scientific library” and “private use library”. Further division would be similar to that of the general classification. The author considers the concept of “the research library” to be optional for the national library science.
Broadening Participation for Remote Communities

Our work is concerned with how embodied communication involving speech and gestures may be mediated through mobile tele-robotics and augmented reality to support hands-on distance mentoring. Following work in the psycholinguistics of embodied communication (e.g., meaning is expressed through gesture, gaze, and speech), a four design-implement-test-deploy-evaluate study was undertaken. We investigated whether and how powerful multimodal language to support explanation and mentoring may be mediated over distance through the designs.
IIT-Hyderabad launches course in Artificial Intelligence and Emerging Technologies

This program will include the study of AI, Internet of Things (IoT), Blockchain, and Quantum Computing from IIT-based professors. Candidates will have to live on the IIT-Hyderabad campus for five weeks. On completion of the course, students will get certificates.
Improving the method of implementing the accelerometer for mobile

Abstract The introduction of Yogyakarta Culinary game is a game with Indonesia theme with the aim to introducing Indonesia culinary especially focused into Yogyakarta region. A many of tourist from local or foreign country just known culinary that exist and famous in Yogyakarta only Gudeg and Bakpia. This research managed to build a game that can help introduced the other culinary interestingly. This game tested on usability and also Accelerometer sensory used to make character movements. Based on testing which is conducted a people who play the game can be concluded that game is easy to use even tough still have a minor weakness inside the game.
HostGator vs GoDaddy: Which is the Better Hosting Option?

The performance of your website, in terms of rendering speed, security, and user experience, is dependent on the hosting service you use. But selecting an efficient and reliable hosting service provider can be a daunting task. In many cases, people simply pick the hosting provider that appears to deliver results for their friends. This rarely works because your website and business mission are different from that of your friends. To further complicate things, many hosting service companies look similar, yet they have major underlying differences.
The Murky Ethics of Emoji: How Shall We Regulate a Web for Good?

This paper builds on our earlier investigation in The Emoji Factor: Humanizing the Emerging Law of Digital Speech by exploring how the social media industry is responding to public demand to expand the emoji collection to reflect our individual differences. We consider the ethical fallout of those decisions by asking two research questions: 1) how are emoji changing to reflect human diversity; and 2) do the resulting designs breach laws or ethical norms with respect to privacy, human rights, or data security. Our methodology includes a comparative examination of research and new ‘personalized’ offerings by internet companies such as Facebook and Twitter, as well as the standards board of the Unicode Consortium, to more accurately reflect emoji users’ physical, racial, age-related, and gender-based uniqueness. Our thesis is that through their graphic simplicity and broad accessibility, emoji are well placed as ambassadors of inclusion but we are challenged by the privacy invasions created by their data use by third parties and by a lack of algorithmic fairness in design choices imposed by artificial intelligence. We focus on examples involving the acceptance by the Unicode Consortium of certain emoji that raise ethical questions about their political messaging and machine biases that could discriminate on the basis of personal beliefs, convictions, race, age, or gender. We conclude that internet technology is a political and moral force and, as beneficiaries of its convenience, we have a responsibility to use ethical regulation to “rethink a Web that is truly inclusive and open, a Web for good.” Where better to begin than with that comedic, widely accessible, masterpiece of non-verbal speech: the emoji.
3D Face Recognition Based on Hybrid Data

Unlike 2D face recognition (FR), the problem of insufficient training data is a major difficulty in 3D face recognition. Traditional Convolutional neural networks (CNNs) can not comprehensively learn all proper filters for FR applications. We embed a handcrafted feature map into our CNN framework—A hybrid data representation is proposed for 3D face. Furthermore, we use a Squeeze-Excitation block to learn the weights of data channels from training face datasets. To overcome the bias of training model based on a small 3D dataset, transfer learning is applied by fine-turning pre-training models, which is trained based on a large 2D face datasets. Tests show that, under challenge conditions such as expression and occlusion, our method outperforms other state-of-the-art methods and can run in real-time.
Deep Residual Learning for Human Identification Based on Facial Landmarks

The face detection and recognition are still challenging research areas, since up to date there is no accurate integral model that works in every situation. As a result, the focus has been shifted to Convolutional Neural Networks (CNNs) and fusion techniques with the hope of better solution. The CNNs have enhanced the state-of-the-art of the human facial identification. However, the CNNs are not easy to train due to degradation problem called (gradient vanishing) when the network depth increased, so there is a need of residual network to solve this problem by going deeper without losing the gradient. In this paper, a pre-trained deep residual network for features extraction and ensembles of classifiers are implemented and facial landmarks are extracted and passed to the pre-trained model. Support Vector Machine (SVM) and random forest classifiers are fused at decision level using weighted and majority voting techniques. The experimental results conducted on ORL database show an excellent mean accuracy rate of about 100%. The accuracy rate of about 100% was achieved on LFW dataset with a minimum 70 facial images per person, and 99% with a minimum 10 facial images per person.
Development of mobile sensor terminals “Portable Go” for navigation in informationally structured and unstructured environments

This paper proposes a navigation system of a personal mobility robot in informationally structured and unstructured environments. First, we introduce a group of robots named Portable Go, which are equipped with laser range finders, gyros, and omni-directional wheels. The Portable Go robots expand the informationally structured environment by deploying in the informationally unstructured environment in advance. Then, a personal mobility robot based on an electric wheelchair is guided by eleven Portable Go robots in the new informationally structured environment which is just created by the Portable Go robots. Through navigation experiments, we verify that the proposed system navigates the personal mobility robot from the informationally structured environment to the informationally unstructured environment smoothly by using the Portable Go robots.
Some Insights and Observations on Depth Issues in Deep Learning Networks

In deep neural networks the depth of network is specified by number of layers and neurons in each layer. These parameters are basically set through trial and error methods. During past few years deep networks have provided successful results for various categories of constrained optimization problems at the cost of high memory and computation. With this motivation, here we propose some valuable insights and observations towards depth aspects in deep learning networks. As the number of parameters in these networks are redundant in nature they are often replaced through subtle architectures. The number of neurons in each layer of a deep network are obtained automatically through various complex functions. The different parameters of network are obtained various regularizers by certain operations on network neurons. This provides a single coherent framework which optimizes memory and computation time thereby generalizing network architectures. The process reduces number of parameters upto an appreciable amount while improving network accuracy. This has provided superior results for several regression and optimization computational scenarios.
Sub-optimal Graph Matching by Node-to-Node Assignment Classification

In the recent years, Graph Edit Distance has awaken interest in the scientific community and some new graph-matching algorithms that compute it have been presented. Nevertheless, these algorithms usually cannot be used in real applications due to runtime restrictions. For this reason, other graph-matching algorithms have also been used that compute an approximation of the graph correspondence with lower runtime. Clearly, in a real application, there is a tradeoff between runtime and accuracy. One of the most costly part in these algorithms is the deduction of the node-to-node mapping. We present a new graph-matching algorithm that returns a graph correspondence without the explicit computation of the assignment problem. This is done thanks to a classification of the node-to-node assignment learned in a previous training stage.
Red-Black Tree Based NeuroEvolution of Augmenting Topologies

In Evolutionary Artificial Neural Networks (EANN), evolutionary algorithms are used to give an additional alternative to adapt besides learning, specially for connection weights training and architecture design, among others. A type of EANNs known as Topology and Weight Evolving Artificial Neural Networks (TWEANN) are used to evolve topology and weights. In this work, we introduce a new encoding on an implementation of NeuroEvolution of Augmenting Topologies (NEAT), a type of TWEANN, by adopting the Red-Black Tree (RBT) as the main data structure to store the connection genes instead of using a list. This new version of NEAT efficacy was tested using as case of study some data sets from the UCI database. The accuracy of networks obtained through the new version of NEAT were compared with the accuracy obtained from feed-forward artificial neural networks trained using back-propagation. These comparisons yielded that the accuracy were similar, and in some cases the accuracy obtained by the new version were better. Also, as the number of patterns increases, the average number of generations increases exponentially. Finally, there is no relationship between the number of attributes and the number of generations.
Influence of atomic coherence on entanglement between dipole-coupled Jaynes-Cummings and isolated atom

We investigated the entanglement of a quantum system consisting of a Jaynes-Cummings atom, thermal lossless cavity and an isolated atom. The analytical expressions of the atom-atom negativity for separable, separable coherent and entangled initial atomic states were obtained. The influence of initial atomic coherence, detuning between the atomic transition frequency and the field frequency and direct dipole-dipole interaction on an atom- atom entanglement is examined. We showed that for a separable and separable coherent initial atomic states a detuning might cause high atom-atom entanglement in the presence of the dipole-dipole interaction even for thermal field with high intensity. We also obtained that for entangled initial atomic states a detuning causes a stabilization of an entanglement oscillations.
Study on the Effect of Key-to-Key Distance on Touch-Sensitive Key Operation

The current study investigated the key-to-key distance, which was defined as the distance between the margin points of two adjacent keys transversally and vertically. In view of forefinger operation, the combination of subjective measurement and objective measurement was used in the ergonomics assessment of key-to-key distance effects on the performance. 30 participants are recruited to attend the tests. One-way ANOVA is used to analyze operational performance at different key-to-key distance and then the S-N-K-hoc is conducted for pairwise comparison, α = 0.05. The results were obtained: when a reasonable key size is decided, key-to-key distance has no effect on the accuracy and efficiency of touch-sensitive key operation. Therefore, considering the user experience satisfaction, the recommended transverse key-to-key distances range for rounded corner key is from 6 mm to 12 mm, while lengthways key-to-key distances range is from 6 mm to 14 mm; the recommended transverse key-to-key distances range for round key is from 6 mm to 12 mm, while lengthways key-to-key distances range is from 6 mm to 16 mm. This research can provide a basis for the design of key size of enterprise electronic products, and has important guiding significance.
Introduction of Item Constraints to Discover Characteristic Sequential Patterns

This chapter introduces a method that discovers characteristic sequential patterns from sequential data based on background knowledge. The sequential data is composed of rows of items. This chapter focuses on the sequential data based on the tabular structured data. That is, each item is composed of an attribute and an attribute value. Also, this chapter focuses on item constraints in order to describe the background knowledge. The constraints describe the combination of items included in sequential patterns. They can represent the interests of analysts. Therefore, they can easily discover sequential patterns coinciding to the interests of the analysts as characteristic sequential patterns. In addition, this chapter focuses on the special case of the item constraints. It is constrained at the last item of the sequential patterns. The discovered patterns are used to the analysis of cause, and reason and can predict the last item in the case that the sub-sequence is given. This chapter introduces the property of the item constraints for the last item.
Metrological characterization of a low-cost portable stereo vision system for dynamic measurements

Abstract In recent years, camera and computer systems have been miniaturized considerably. The market now offers several low-cost products to assemble a small scale portable stereo vision system which can be completely autonomous (since it can acquire and process image). However, the metrological characteristics of such a portable stereo vision device should be assessed and compared with the state of the art of stereo vision system. In this work a portable stereo vision system composed by small board cameras and a single board computer is metrologically characterized and validated with respect to fixed non-portable systems. The analysis focused on the application of such a stereo rig to DIC and stereoscopic measurements performed with commercial software. For these tests two algorithms with different correlation techniques are evaluated in Matlab and in Halcon, moreover, a 3D DIC analysis is conducted on a H-shape specimen. To perform a metrological characterization, the points clouds obtained from the triangulations are confined to a region of the scene containing only a part of the specimen, after that they are fitted with a LOWESS fitting model. The uncertainty is assessed by computing the discrepancy between the points of the cloud and the ones of the fitting model. In some algorithms more than others the errors distribute in a strongly periodic manner with a period linked to integer values of disparity. Eventually the experimental analysis demonstrated that the accuracy of such a lightweight stereo system is similar to the accuracy of traditional not-portable ones.
Using Boolean- and Self-Enforcing-Networks for Mathematical E-Tutorial Systems

Mathematical thinking as an important instrument in science is a stumbling block for many students in the first years. A lot of investigations occur to help the students understanding the principles of mathematics. The proposed tutorial system for the basics focuses on the analysis and visualizations of the solution algorithms and solution processes with Boolean Networks and Self-Enforcing Networks. The students can check not only the correctness of their results, but also if the solution steps are complete. In addition, in case of wrong results the students can check in which step of the solution they made a mistake and what kind of mistake. The goal is to promote the explorative learning and to help understanding the problems through self-recognition.
When to Build an FAQ: A Case Study

Column description. The Technology column examines current and developing technology topics in libraries. The column?s focus is creative uses of technology, introductions to new technologies, and critiques of current technologies, their uses, or their future. Readers interested in contributing ideas or writings to this column may contact column co-editor Derek Marshall.
Modern Information and Communication Technology for Improving Computer Lite

Purpose of research. This article discusses modern information and communication technologies to improve computer literacy in Russia, defines the concept of computer literacy and its classification. It turned out that the problem of computer illiteracy is very relevant today. The aim of the work is to develop a method and algorithm to reduce the level of computer illiteracy. Methods. We have proposed a method by which the level of computer literacy will increase in certain groups of the population, these are schoolchildren, pensioners, through the creation of certain institutions for training in the field of information technology. This method is based on the hierarchical model of Saati. To analyze the initial data, the results of a study of the degree of digital literacy of residents of the Russian Federation by the analytical center of NAFI were used. Considering programs of professional development within the program "University of the elderly person", projects on which train pensioners and pupils of schools of computer literacy. Eaten a comparative analysis of training programs for different categories of citizens, for example, one of the largest in the city of Kursk organization "Center of social service "Part" of the city of Kursk Kursk region", which annually serves more than two thousand people of retirement age and the disabled. Results. It is shown that the program, according to which the training of people of retirement age of computer literacy, differs from similar training programs for other categories of citizens. For example, based on the assessment of the integral criterion, it was found that computer crime in the field of computer information in the world has increased, and the most vulnerable segments of the population are schoolchildren and pensioners. Conclusion. The article presents a computational modelling of the proposed technique and an algorithm for its implementation as well as a diagram of the integral quality indicator for improving computer literacy.
Time to Ride the Wave of Precision Medicine

Almost a decade has passed since we first heard about <strong><em>Precision Medicine&nbsp;</em></strong> from the National Research Council, USA. With more technology, expertise and understanding, the time has come for the Philippines to stop watching and instead, ride this tide of change, with the patient at the center. &nbsp;
An ensemble integrated mailing system for detecting spam mails

Abstract In Internet, today most widely issues occur with security. Security plays the vital role in Internet. Many software and hardware systems are affecting with the security issues. This may cause major problem for the companies to maintain the network securely. Attackers mainly concentrate on attacking the servers and systems with any type of malware and virus to hack the system or mail account. Today the most popular attacking by the attackers are spam mails. This brings lot of security issues if it is implemented in gmail, yahoo and other mail service providers. Spam zombies are the spam activities done by the spam developers to attack the system. In this paper, an ensemble spam mail detection system named ESMDS by observing outgoing and incoming messages of a network. ESMDS is developed based on a powerful analysis tool called Sequential Probability Ratio Test (SPRT). Results show the performance of the ESMDS.