Reviewerly/exHarmony huggingface dataset:
A New Efficient Airborne Video Dehaze System for UCAV

Arming at the problem of image degradation during the UCAV capture the image for the interested target in the haze day, we propose a novel system for video dehaze based on embedded technology. The system adopts TS1601 as the main unit for the whole hardware system to complete dehaze parameterization control, H.264 video compression processing and framing processing, peripheral interface design and control command response and other functions. This paper introduces the design of the system's design framework, software design frame and modules works. The experimental results indicate that the system can fulfill the demand of video dehaze in real time and have some advantages such as low power consumption, easy implement etc. It can achieve the demand of the airborne dehaze application.
Fast 3D reconstruction method based on 2D gold matrix

The optical three-dimension measurement methods have been widely used in face recognition, machine vision, biomedical imaging, virtual reality and aerospace with the advantages of fast speed, high precision and non-contact measurement. Recently, the trend of structured light 3D reconstruction tends to be real-time with improving accuracy and reducing the dependence of time domain. The structured light coding is an active measurement method which could provide abundant feature points. The 2D gold matrix is a spatial coding method and it provides a new type of structured light for optical 3D measurement. This scheme provides the dynamic 2D spatial information based on the fast decoding from the encoded projected light. Here, we proposed a binocular stereo vision system based on the structured light encoded by 2D gold matrix. Only a pair of images, which could be captured in real-time by the two cameras, are needed for 3D reconstruction. The experiment shows that the decoding success rate is up to 99.48% for non-planar object. The system is simple in structure and low in cost. It is expected to be applied to real-time 3D measurement fields such as face recognition and biomedical imaging in the future.
Affective Communication: Exchanges between People and Nature via Information Technology

Ironically, the material infrastructure that underpins the digital platforms we use to share information related to environmental degradation comprises reliance on heavily polluting forms of energy which are a staple part of that very same degradation rallied against online. As it is implausible to suggest that we would move away from our new digital reality, it is argued that we should embrace its communicative capacities despite the fact that our digital infrastructure is environmentally destructive. And, it is argued that the greatest capacity of digitality lies not in its ability for information sharing, but in its ability to affect us on a level beyond the consumption of environmental information. In doing so, great caution should be exercised so as not to fall into the trap of reifying the powers of information technology. Rather, we should see it as yet indeterminate and as capable of producing exchanges between people and nature that are of surprising potential. In order to read the potential of these exchanges, the article draws on a philosophical framework developed by the post- structuralist duo Deleuze and Guattari. Following this, two nature-oriented digital artefacts are examined for their ability to communicate with us on a level beyond information exchange.
A discerning algorithm for authorization

Abstract In the article, we consider a discerning authorization algorithm that eliminates the contradictions in the assignment of access rights to security principals in complex infrastructures, which are using concepts such as group and inheritance. It also can use for the identification of security risks and it ensures that the security risk assessments produce consistent, valid and comparable results.
CROSS DOMAIN OPINION MINING USING MAXIMUM ENTROPY BASED CLASSIFIER

Abstract The current analysis is play a dominant role in opinion mining is additionally referred to as sentiment analysis because of clear volume of opinion made net resource like discussion type, review sites, blogs, and tweets area unit on the market in digital type. Sentiment analysis is that the field of study that analyzes client opinion, feedback, sentiment analysis, attitudes and feeling from communication. At intervals fraction second, we have a tendency to classify the text in several manner in several seconds. It’s one in all the active analysis areas in linguistic communication process [NLP]. There are a unit range of techniques we want to classify the Opinion reviews. The main problematic in the sentiment analysis is to understand the usage of negation and the taxonomy of positive and negative sentiments recorded by the users in the social group. The proposed approach that extracts and classifies opinion words from one domain called source domain and predicts opinion words of another domain called target domain using a semi-supervised approach, its combines modified maximum entropy and bipartite graph clustering. A comparison of opinionclassification of reviews on four different product domains are presented. The results demonstrate that the proposed method perform relatively well in comparison to the other methods. Comparison of SentiWordNet of domain-specific and domain-independent words reveals that on an average 72.6% and 88.4% words, respectively, are correctly classified.
Comparing Optimization Methods of Neural Networks for Real-time Inference

This paper compares three different optimization approaches for accelerating the inference of convolutional neural networks (CNNs). We compare the techniques of separable convolution, weight pruning, and binarization. Each method is implemented and empirically compared in three aspects: preservation of accuracy, storage requirements, and achieved speed-up. Experiments are performed both on a desktop computer and on a mobile platform using a CNN model for vehicle type classification. Our experiments show that the largest speed-up is achieved by binarization, whereas pruning achieves the largest reduction in storage requirements. Both of these approaches largely preserve the accuracy of the original network.
A Systematic Review on Humanizing Factors for Online System

Online systems have improved our lives in many ways compared to traditional method. Recently, humanizing online systems become an important issue and an interest of professionals and academician as it is believed can improve online systems become more user-centric. However, the systematic review to report the current state of humanizing online systems research is very limited. Thus, this paper aims to systematically review and contributes better understanding of humanizing for online systems research. To collect and review previous studies, we used systematic literature review method consisting three phases which are planning, conducting and reporting the reviews. A set of research questions for the review covers the meaning, problems and factors of humanizing online systems from various fields. As a result, we selected 33 papers that have relevant information to address the research questions been set. Based on the review, we also found that humanizing in online system is still undefined. Therefore, further study that investigate human behavior in online system is necessary.
Improving classification and clustering techniques using GPUs

Summary Classification and clustering techniques are used in different applications. Large‐scale big data applications such as social networks analysis applications need to process large data chunks in a short time. Classification and clustering tasks in such applications consume a lot of processing time. Improving the performance of classification and clustering algorithms enhances the performance of applications that use such type of algorithms. This paper introduces an approach for exploiting the graphics processing unit (GPU) platform to improve the performance of classification and clustering algorithms. The proposed approach uses two GPUs implementations, which are the pure GPU or GPU‐only implementation and the GPU‐CPU hybrid implementation. The results show that the hybrid implementation, which optimizes the subtask scheduling for both the CPU and the GPU processing elements, outperforms the approach that uses only the GPU.
Implementation of String Matching Algorithm in Customer Data PT. PLN (Persero) Krueng Geukueh District

Abstract According with the development of information technology and the expand of the internet in the community, the need for computers is very important to support the increasingly high utilization of information technology. Processing data and information requires speed and accuracy of data, to achieve it, it is requires an information technology that can support work so the work becomes more effective and efficient. PT. PLN (Persero) Krueng Geukueh District is a company that runs in the area of electricity and provides services to the community in the provision of services related to electricity, which has a large number of customers. The process of managing customer data at PT. PLN (Persero) Krueng Geukueh District has used a customer data system, but still has a disadvantage of requiring more time in searching customer data, to solving this problem, the author designed the development of the system using the string matching algorithm method, which is one of the most important parts in various processes related to data and text types, one of which is the search for words in customer data. The performance of the string matching algorithm is to match a letters per letter with the keywords given by the staff. The results of this study indicate that by using this method, searching for customer data can be easier. With the development of this system, it is expected that staff or admin in the company can do the work more effectively and efficiently.
Old Data, Changed Times, New Resource? A Case Study, Barrytown, New Zealand, Ilmenite Garnet Gold Zircon

SummaryThe project geology has been compiled reviewed and a new, modern, resource database has been developed for the Barrytown New Zealand, Ilmenite Garnet Gold Zircon project.The work required existing databases to be updated to include all historic mineral sands and gold data, and consolidated and checked versus original records.The NZ Petroleum and Minerals (NZPAM) Mineral Report (MR) documents for the Barrytown project were checked and the data was compared to that contained in the project databases compiled prior to this recent 2018 work. Additional information was extracted and added into the databases including omitted holes, collars, size fractions, magnetic fractions, lithology, and especially gold assays. Within the project budget, as much additional data as could possibly be extracted was found by being persistent and systematically working through the contained information. The NZPAM system, although not ideal, does contain a wealth of information.
State-of-the-Art Techniques for Mammogram Enhancement: A Comprehensive Discussion of Emerging Research Gaps and Remedial Solution

Breast cancer may be predicted via variety of appearances on mammograms: from the obvious benign or malignant masses, to density variations, subtle asymmetries, to rarely visible and obscured calcifications.
Assistive Technologies to Support Communication with Neuro-motor Disabled Patients

The paper describes the evolution in design and implementation of a new complex electro-informatics assistive medical system used for the communication with neuromotor disabled patients. These patients are severe handicapped persons who cannot interfere with real world by normal ways like speech, writing or language signs. Fortunately, these persons can see or can hear and they understand the meaning of different messages. The developed medical system is made by the following main functional components: the patient equipment, server, and caretaker device, connected together by using Internet available infrastructure. The bidirectional communication is performed by using keywords technology or ideograms presented on the patient’s screen provided by an application running at the server and accessed by the patient through a web browser. Patient needs are performed by using for interfacing with a software application by using different types of sensors including switch-type sensors (tactile, pressure, strain gauge) or eye tracking devices, all of these adapted to the patient’s physical condition. The medical system has also a secondary function, the remote monitoring of few vital physiological parameters needed for patient treatment and rehabilitation, based on wireless and wearable sensor network, that share the same hardware platform. The application running on caretaker device displays the patient’s needs together with the values of the selected physiological parameters in real time. The medical devices are responsible for physiological parameters acquiring, preprocessing and forwarding into the server. The server performs the parameters processing and computing the medical condition of the patient and also has the ability of sending alerts to the caretaker when one or more parameters are outside the normal limits. The application running on server manages the system databases, the communication protocols between patient and caretaker devices, records and processes the remote monitored data values and alarms the caretaker devices in emergency situations. The prototype of the developed medical system has been successfully within Clinic of “Geriatrics and Gerontology” at “Dr. C. I. Parhon” Hospital of Iaşi, Romania. The assistive solution proposed can be used in hospitals, care and treatment centers, nursing homes and also for patients treated in outpatient settings. The system contributes to increasing the level of care and treatment for neuromotor disabled patients, lowering costs in health care system.
A Survey of Ontology-Based Frameworks for Sustainable Supply Chain Interoperability and Collaboration

Accurate and meaningful sharing of knowledge across the supply chain enables effective and timely decision making, a key requirement for ensuring cost-effectiveness, availability, and quality of products and services. Effective elicitation, analysis, classification, and representation of domain knowledge are all essential activities for effective sharing of information. Ontology-based frameworks create a common formal representation of a particular domain that can be communicated, and understood by people and machine agents in addition to integrating different knowledge bases to connect heterogeneous engineering applications. Such frameworks have been exploited in the manufacturing domain as buyer-supplier discovery systems that can be used for quick matchmaking, intelligent connectivity, knowledge-driven collaboration, and possible establishment of stronger, sustainable, long-term, and strategic supply chains. A literature review has identified many frameworks with varying knowledge sharing capabilities that are highly determined by the underlying ontological formalism.
STYLISTIC MEANS OF EXPRESSING TRANSHUMANISM IN OLES BERDNYK'S EARLY NOVELS

The article examines stylistic devices in which distinguished Ukrainian writer Oles Berdnyk expresses transhumanist ideas. The author is famous for being one of the brightest representatives of native science fiction. His early novels “Paths of Titans”, “The Arrow of Time” and “Children of Infinity”, which depict a utopian future, have been chosen as an object to be studied. It is found out that the message translated by the author in a given period of his creative activity reproduces primarily the techno-optimistic discourse that prevailed in the middle of the twentieth century and has some obvious transhumanist and immortalist indications, which can be observed both at substantive (the evolution of a man into an omnipotent immortal being is being depicted) and stylistic level. In its simplest form, this is manifested in the active use of positively colored epithets, hyperbolized metaphors, metonymic embodiments and other stylistic means which shape central features of the author's idiostyle. The tropes and figures of speech used by the author are in most cases emotionally expressive, that is, they contain elements of value (mostly positive, in this case). One common characteristic of Berdnyk’s prose is its high expressiveness, that is, solemn and pompous style, contrast and bright images. Building on the ideas of cosmism philosophy, he follows the scientistic trends of the Golden Age of western science fiction on the one hand and introduces some distinctive elements of national Ukrainian conceptosphere into the established genre on the other. His late works, however, underwent drastic philosophical changes, resulting in a gradual departure from his previous views.
Body Height Detection System Using Russel &amp; Rao Method

Abstract Height body detection is an interesting thing to study, because of height is often using in various fields. Measurement height with a manual tool, it is very easy to use. Retrieval of objects using a webcam camera then measured with the Russel &amp; Rao method. This system was built using Borland Delphi 07 programming language. His research method was obtained from literature studies of various books and articles which consisted of several stages, like the grayscale stage, and russel &amp; rao. And at the time of height detection, this system will doing well if around the object that will be taken into account there are no other objects, such as the meter will move to another thing. So to simplify the measurement, you must choose the right place. Russell &amp; Rao’s performance has a true detection percentage of 65%. Based on 8 sample tests that have been carried out, only 3 have been detected correctly.
A learning-based method using epipolar geometry for light field depth estimation

A novel method is proposed in this paper for light field depth estimation by using a convolutional neural network. Many approaches have been proposed to make light field depth estimation, while most of them have a contradiction between accuracy and runtime. In order to solve this problem, we proposed a method which can get more accurate light field depth estimation results with faster speed. First, the light field data is augmented by proposed method considering the light field geometry. Because of the large amount of the light field data, the number of images needs to be reduced appropriately to improve the operation speed, while maintaining the confidence of the estimation. Next, light field images are inputted into our network after data augmentation. The features of the images are extracted during the process, which could be used to calculate the disparity value. Finally, our network can generate an accurate depth map from the input light field image after training. Using this accurate depth map, the 3D structure in real world could be accurately reconstructed. Our method is verified by the HCI 4D Light Field Benchmark and real-world light field images captured with a Lytro light field camera.
Accuracy Analysis of Sun Position Calculation Algorithms: Ineichen and SPA

Sun position calculation algorithms are widely used in solar tracker photovoltaic plants and softwares to design photovoltaic projects. The scientific community has several algorithms that compute the sun position, and they vary in accuracy, complexity and validity time. The accuracy analysis of the algorithms is important because the different applications require different levels of accuracy. In applications such as measuring instrument callibration, e.g., it is required high precision algorithms. This work presents a statistical analysis of the accuracy of two sun position algorithms: the algorithm proposed by Ineichen, which is used for PVSyst <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">®</sup> software, and the Solar Position Algorithm, taking into consideration both the standard deviation and the maximum errors, as well as quartiles and quantiles. The algorithm that has the highest accuracy is the SPA, where 99% of the samples have solar vector errors below 0.1187695°.
Coprocessor for Koblitz Curves

Koblitz curves [20] are a special class of elliptic-curves which enable very efficient point multiplications and, therefore, they are attractive for hardware and software implementations. However, these efficiency gains can be exploited only by representing scalars as specific $$\tau $$-adic expansions. Most cryptosystems require the scalar also as an integer (see, e.g., ECDSA [25]). Therefore, cryptosystems utilizing Koblitz curves need both the integer and $$\tau $$-adic representations of the scalar, which results in a need for conversions between the two domains.
The Technological Gaze

In addressing the question of how we think and model the participant, user or audience for interactive systems, we initiate an interrogation of who we think we are, and what we think technology is in relation to who we think we are. Future-proofing innovation in design thinking must involve serious thought about conceptual models for how we see ourselves as makers and audiences, since they precede design solutions. Here, lessons and transferable insights from live performance and experience design can inform design thinking in digital materialities. This paper will explore the nature and direction of the technological gaze on audiences or human system users and interrogate its influence on design. Subsequently, it introduces observations from live event design that modifies techne with metis to invite the sublime as an integral part of immersive experience.
How to Evaluate the Effect of School Educational Innovations in Russia in 2000-2010’s: Ways to Overcome Research Problems and Risks

The article is devoted to the problem of scientifi c research and evaluation of innovative processes in Russian school education. The article indicates the one-sidedness of the existing approach to the analysis and evaluation of the eff ectiveness of educational innovations; reveals the main reasons for the prevailing in science and politics uncritical, “hassle-free” view of the eff ectiveness of introduced innovations; promising ways to overcome existing research problems and risks are proposed.
Analysis of electrical patterns activity in artificial multi-stable neural networks

An improved mathematical model of artificial neuron with active generation of action potentials was developed, and the behavior of an artificial network consisting of thousands of described neurons was investigated. The passive part of the neuron consists of soma and asymmetric dendritic branches that provide multi-stability. The active component of the neuron is described with the help of a simplified non-linear neuron model with mechanisms for the spiking generation. The presented model reproduces all types of electrical generations of known biological neurons, e.g. neocortical. The model combines the biological similarity of the Hodgkin-Huxley type dynamics and the computational efficiency of integrative-spiking neurons. It is shown that switching between different modes of generation is possible under the condition of structural three-stability of the neuron in common. A neural network consisting of multi-stable neurons is capable of generating synchronous regular spikes if all neurons in the network are in a similar electrical state. In the case where a part of the neurons at non-similar stable condition, the network generates asynchronous regular spikes, without adding any synaptic plasticity mechanisms or modulating stimulation processes. The obtained model can be used for studying the features of real-time data processing by artificial neural networks, which can be used for such modern tasks as recognition and classification of biophysical signal patterns or for the development of elements of artificial intelligence.