Reviewerly/exHarmony huggingface dataset:
Mean Distance Parameter Based Facial Expression Recognition System

Human-like facial expression recognition is the ultimate goal of all automatic facial expression recognition system. Facial expression recognition is mostly achieved by comparing the test image of a person with his/her neutral image. In this paper, “mean distance parameter” (MDP) has been proposed, and is used to recognize the facial expression. In this proposed methodology, database is not required to train the system for expression recognition, but neutral images from the database have been used only once for calculating the mean distance parameter. After establishment of the mean distance parameter based on region of interest (ROI) height, action units (AUs) have been detected by comparing it with the test image’s fiducial point distance. Facial expression recognition has been performed based on these detected AUs in the test image, and recognition rate of 96.66% has been achieved for Cohn-Kanade database.
Estimation of Skew Angle from Trilingual Handwritten Documents at Word Level: An Approach Based on Region Props

In this work, an efficient technique for segmenting the words from multilingual unconstrained handwritten documents at word level is proposed. In the proposed model, morphological operations and connected component analysis are used for word identification. Based on that, the bounding box for each word is drawn and then words are segmented. The proposed algorithm also works on documents with any orientation. We conducted experimentation on our own 300 unconstrained multilingual handwritten documents. The result shows the performance of the proposed algorithm.
A Novel Secret Key Exchange Mechanism for Secure Communication and Data Transfer in Symmetric Cryptosystems

Secure communication and Secure data transfer are one of the significant challenges in the era of Internet. With the development in information technology, there arose a need for invulnerable transfer of data. Visual Cryptography is the method in which the secrets are encoded in the form of shares which can be decrypted by overlapping the shares that are obtained. As the usage of images in the industrial process is rapidly rising, it is vital to protect the confidential image data from unauthorized access. The (2,2) Visual Cryptography scheme involves the encoding of the image to create two shares. It is later obtained through the stacking process. Further, Halftoning technique can be applied by the dithering process for the approximation of the colors in the image. It makes use of Floyd’s Steinberg Algorithm which uses the dithering process by mapping the required color from the eight color bit palette assigned. The design layout is broken down into two module. The first module is used to convert the image into a binary image, and the other module is used to pass the input image to Floyd’s Steinberg algorithm. This technique can be best suited for the application in the banking system or any other field where confidentiality is the primary concern.
Incidence of Motion Sickness

Now that we have a basic understanding of what the term “motion sickness” means and how it affects the individual, we can examine the problem in more detail. We shall begin by getting a feel for just how common motion sickness has been found to occur in various forms of provocative motion. I am sure that these numbers will convince you that this response is prevalent across the population. This in itself would support what I said in the last chapter, namely, that this is a perfectly normal protective response and we should not be surprised at the high incidence that is associated with the various modes of transport. It should also alert us to the fact that motion sickness can have a significant effect on crew performance and operational efficiency. Although I seem to stress the military situation, one must not forget that this malady is also equally common in both commercial and social settings.
Mapping and Analysis of the Reactive Power Balance in the Danish Transmission Network

This paper investigates the reactive power balance of the Zealand side of the Danish transmission system (DK2) by using QV-curves. The study is performed in cooperation with Energinet, who is the Danish transmission system operator (TSO). Firstly, this paper aims to map the reactive power balance with the current challenges in the system, which appears due to a decision of changing overhead lines in the scenic area to cables. Secondly, a method is derived for obtaining a comprehensive overview of the impacts that future projects might have on the system. By dividing the transmission system into smaller areas, it is possible to analyze how the reactive power will affect the voltage; moreover, it is favorable to analyze and handle the challenges in the reactive power balance locally. This helps the TSO to quickly determine the lack of reactive power devices and issues that might occur in future expansions of the system. For this paper, a full-scale model of DK2 and SCADA-data has been utilized. It covers the period from 01-01-2016 to 20-08-2017 between the TSO and the Distribution System Operator (DSO). The studies have shown how the location of the wind production will create issues in the reactive power balance.
Quantum key distribution for ultra-long distances based on microsatellites

The authors of this work made a device for free space quantum key distribution with using of polarization encoding, operating at frequencies of 0.3–1.6 GHz. According to BB84 protocol, the polarization states of photons, with a wavelength of 1.55 µm, are being used for encoding information. At the probability to find a photon in single pulses of 0.20, there is a sifted quantum key distribution rate of 170 kbps with the corresponding quantum bit error rate of 1.4 %. At short distances between the transmitter and the receiver, the possibility of quantum key distribution with phase encoding was experimentally proved.
Compact Implementation of Modular Multiplication for Special Modulus on MSP430X

For the pre/post-quantum Public Key Cryptography (PKC), such as Elliptic Curve Cryptography (ECC) and Supersingular Isogeny Diffie–Hellman key exchange (SIDH), modular multiplication is the most expensive operation among basic arithmetic of these cryptographic schemes. For this reason, the execution timing of such cryptographic schemes in an implementation level, which may highly determine the service availability for the low-end microprocessors (e.g., 8-bit AVR and 16-bit MSP430X), is mainly relied on the efficiency of modular multiplication on the target processors. In this paper, we present new optimal modular multiplication techniques based on interleaved Montgomery multiplication on 16-bit MSP430X microprocessors, where the multiplication part is performed in a hardware multiplier and the reduction part is performed in a basic Arithmetic Logic Unit (ALU) with optimal modular multiplication routine, respectively. This approach is effective for special modulus of NIST curves, SM2 curves, and SIDH. In order to demonstrate the superiority of proposed Montgomery multiplication, we applied the proposed method to the NIST P–256 curve, of which the implementation improves the previous modular multiplication and squaring operations by 39% and 37.1% on 16-bit MSP430X microprocessors, respectively. Moreover, secure countermeasures against timing attack and simple power analysis is also applied to the scalar multiplication of NIST P–256, which achieves the 9,285,578 clock cycles and only requires 0.575 s (@16 MHz). The proposed Montgomery multiplication has broad applications to other cryptographic schemes and microprocessors.
Computer Intelligent Systems for Manufacture and Control

Automation of production and assembly processes is one of the important tasks in micromechanics. To produce totally automated micro factory or automate the solar concentrator production and assembly, it is necessary to develop a computer vision system that can replace an operator. A computer vision system may have several functions, for example, recognition of objects on the image of working area, recognition of mutual position of several components on the image, and measurement of component size, etc. We select several tasks that are connected with the micromechanics area and automatization—for example, size measurement of micro components. The object of measurement is a micro piston. Micro pistons are the components of heat engines that transfer the heat energy from solar concentrator to electrical energy. The goal of this work is the research and development of the LIRA (Limited Receptive Area) neural network and its application to measure the micro piston size. To obtain micro piston sizes, it is necessary to recognize its boundaries in the image. We propose to use LIRA neural network to extract and classify piston boundaries. In this chapter, we describe and analyze the preliminary results of LIRA application to micro piston boundaries recognition. Experiments with the recognition system have given us the information to improve the structure and parameters of the developed neural network. Experiments with the LIRA neural network showed the necessity to accelerate its processing time by implementing the neural network algorithms with electronic schemes such as Altera. The advantage of the neural network is its parallel structure and possibility of the training. FPGA allows the implementation of these parallel algorithms in a single device. This chapter contains brief description of ensemble neuron networks and some results of storage capacity estimation. We propose to apply this ensemble neural network to the problem of selection of adequate maneuver for robot-manipulator or for mobile robot.
Assessment of the impacts of TLS vulnerabilities in the HTTPS ecosystem of China

In order to assess the regional impacts of TLS vulnerabilities in China, by using the combination of CT logs and IPv4 scans, we made measurements of the HTTPS ecosystem of China and obtained a representative dataset. Based on the dataset, we analyzed the impacts of TLS vulnerabilities on China, including Heartbleed, Logjam and the use of weak hash algorithms. Then we represented the results of the impacts of these vulnerabilities. Our studies showed the severity of these vulnerabilities in China has been controlled at a low level, except the attacks on outdated hash algorithms like SHA1 that is proved to be not secure recently, which affect over 33% of available HTTPS servers in China. And we found the impacts of these vulnerabilities are concentrated in where information industry is developed relatively. Lastly, we concluded with the lag situation of HTTPS ecosystem of China needed to solve urgently in the development of Internet security.
Analysis of Optimization Capability of Selection Operator for DE Algorithm

Differential Evolution Algorithm (DE) is an intelligent algorithm widely used in recent years. Many scholars have studied DE algorithm from many aspects, such as theory and application. Selection operator using greedy strategy is an important part of DE algorithm. Traditionally thought, the DE selection operator is only a means to maintain effective population evolution of DE. In fact, the DE selection operator also has some capability to optimize. For this reason, this paper constructs some DE variants, and compares the optimization results of them with the standard DE algorithm. Simulation results show that the new algorithm which only using greedy selection can achieve certain optimization results, meanwhile, DE algorithm which removing its greedy selection operator only has poor performance. This proves that DE selection operator has certain optimization capability.
Enterprises and Future Disruptive Technological Innovations: Exploring Blockchain Ledger Description Framework (BLDF) for the Design and Development of Blockchain Use Cases

This digital age is viewed as a space that will herald greater innovation focus and spirit. Kindled by Blockchain Technologies (BT) or Distributed Ledger Technologies (DLT) potentials for disruptive innovations across a wide range of industries, the question of how enterprises can prepare for future, next-generation digital technological innovations is raised. This paper examines the current approaches in Enterprise Modelling (EM), Enterprise Architecture (EA) design and Enterprise Governance of IT (EGIT) and deploy them as useful models and tools to aid management of new innovative technologies. The scope is restricted to the domains of Blockchain or Distributed Ledger Technologies (DLT) as the underlying platform for technological innovations in modern enterprises. The contributions of this paper include: (a) mapping of EM/EA for new digital innovations exemplified by the case of DLT; (b) applying suitable EM/EA framework for design and building of blockchain use cases; (c) validating of the framework via participatory actions research method and (d) discussing challenges and research areas that impact enterprises and new disruptive digital innovations.
Long-Term Face Image Analysis Based on Canonical Correlation Analysis on Physical and Psychological Evaluation of Face

In this paper, we analyze the relationship between impression of facial skin and skin pigmentation distribution by applying Canonical Coefficient Analysis (CCA) to multiple physical and psychological features obtained from facial skin. Based on the acquired relationship expression, we modulate the skin pigment features, and appearances of the face with arbitrary psychological features are reproduced. In our previous work, we applied principal component analysis (PCA) to the melanin pigment variation of the facial skin, and we obtained individual differences in it occurring over seven years. In the previous method, as the factor causing individual difference, we considered the frequency of UV care. However, actual skin appearance is thought to depend not only on melanin but also on several other factors. Therefore, in this study, we photographed the faces of women of various ages for 12 years, and at the same time obtained psychological features of appearance. As physical features, melanin and hemoglobin pigmentation distributions, shading and the frequency of UV care for 12 years were obtained. Subjective evaluation values were acquired as psychological features. As a result of CCA, it was found that the whole face can be made lighter in appearance by using UV protection every day continuously for six years or more.
An Efficient Anonymous Authentication Scheme Based on Double Authentication Preventing Signature for Mobile Healthcare Crowd Sensing

With the widespread growth of cloud computing and mobile healthcare crowd sensing (MHCS), an increasing number of individuals are outsourcing their masses of bio-information in the cloud server to achieve convenient and efficient. In this environment, Cloud Data Center (CDC) needs to authenticate masses of information without revealing owners’ sensitive information. However, tremendous communication cost, storage space cost and checking time cost lead to CDC that give rise to all kinds of privacy concerns as well. To mitigate these issues, To mitigate these issues, we propose a data anonymous batch verification scheme for MHCS based on a certificateless double authentication preventing aggregate signature. The proposed scheme can authenticate all sensing bio-information in a privacy preserving way. We then present that the proposed CL-DAPAS scheme is existentially unforgeable in the Random Oracle Model (ROM) assuming that Computational Diffie-Hellman problem is difficult to solve. Furthermore, we provide an implementation and evaluate performance of the proposed scheme and demonstrate that it achieves less efficient computational cost compared with some related schemes.
Improving Generalization Ability of Deep Neural Networks for Visual Recognition Tasks

This article discusses generalization ability of convolutional neural networks (CNNs) for visual recognition with special focus on robustness to image degradation. It has been long since CNNs were claimed to surpass human vision, for example, in an object recognition task. However, such claims simply report experimental results that CNNs perform better than humans on a closed set of testing inputs. In fact, CNNs can easily fail for images to which noises are added, when they have not learned the noisy images; this is the case even if humans are barely affected by the added noises. As a solution to this problem, we discuss an approach that first restores the clean image from an input distorted image and then uses it for the target recognition task, where a CNN trained only on clean images is used. For solutions to the first step, we show our recent studies of image restoration. There are multiple different types of image distortion, such as noise, defocus/motion blur, rain-streaks, raindrops, haze etc. We first introduce our recent study of architectural design of CNNs for image restoration targeting at a single, identified type of distortion. We then introduce another study, which proposes to use a single CNN to remove combination of multiple types of distortion with unknown mixture ratio. Although it achieves only lower accuracy than the first method in the case of a single, identified type of distortion, the method will be more useful in practical applications.
Criteria for Adequacy Estimation of Mathematical Descriptions of Physical Processes

In this chapter, adequacy estimation criteria for mathematical descriptions in the form of ordinary differential equations were proposed.Adequate mathematical descriptions can increase the objectivity of the results of mathematical modeling for future use.These descriptions make it possibly reasonable to use the results of mathematical modeling to optimize and predict the behavior of physical processes.Interrelations between criteria are considered.The proposed criteria are easily transferred on mathematical descriptions in algebraic form.
Formation of geochemical anomalies in loess-paleosol sequence at the Dahu Gold Mine, central China: A clastic-hydromorphic-gaseous dispersion model

Modern mineral exploration requires a comprehensive understanding of how geochemical anomalies form, particularly where the mineral deposits are covered by unconsolidated sediments. However, the mechanisms that form anomalies vary as a function of cover type and are not well understood. The Dahu Gold Mine in central China is characterized by a lode gold deposit, overlain by a younger loess-paleosol sequence (including saprolite). Thus, the site provides an opportunity to examine how elements associated with primary mineralization have been dispersed through the loess to form anomalies in this poorly-investigated cover type. Fine-grained (<74 μm) samples were collected to determine the concentrations of Au, Cu, Pb, Zn, As, Mo, Co, Ni and Mn in the loess-paleosol sequence. The results from two vertical profiles over the deposit show that anomalies of Au, As, Mo, Pb, Zn and Cu were developed in three layers. From the bottom up, it includes (1) the saprolite, (2) the lower Wucheng Loess and (3) the upper Lishi Loess. In contrast, non-mineralized Co, Ni and Mn show a uniform distribution along the profiles. The vertical profile outside the context of primary mineralization, however, shows no anomalous zones of metal enrichment. Generally, the anomalies in the lower Wucheng Loess and upper Lishi Loess are 2 to 5 times higher than the background, for instance, >70 μg/g of Pb vs. the average 30 μg/g of Pb in the Chinese loess. Anomalies in the saprolite are interpreted to have formed by in-situ weathering of the primary mineralized rocks. In contrast, anomalies in the lower Wucheng Loess which correspond to the calcrete horizon were probably formed by the precipitation of metals from ascending Ca (HCO3)2-rich mineralized groundwater. The SN directed horizontal profile shows that anomalies of Au, Cu, Mo and Pb in the upper Lishi Loess which are not in direct contact with the mineralization, spatially coincide with major faults (i.e. the Huashan Frontal Fault) and fractures in the loess-paleosol sequence. Moreover, Pb isotopic ratios documented for the sulphide ores and anomalous and background loess suggest that they are partially derived from the sulphide ores. The anomalies in the upper Lishi Loess are interpreted to be formed by a possible gaseous dispersion process. Elements, probably in metallic form (e.g. nanoparticulate Au), were carried by gases that flowed up faults and fractures to the surface and were precipitated in carbonate-rich clayey loess. Therefore, the formation of anomalies in the loess-paleosol sequence is a synthesis of clastic, hydromorphic and gaseous dispersion processes.
Application of image stitching method in corrosion morphology analysis

An image stitching technique is introduced to automatically composite a panorama of the corroded surface with a series of scanned microscopic corrosion images. In this method, the features in the overlapping area of adjacent corrosion images are extracted to establish the geometric transformation for registration, and the weighted average method is used to minimize the visible seam existing in the stitching result. A sequence images alignment strategy is introduced to complete the whole stitching process. The effect of overlapping area on stitching accuracy was examined and the advantage of applying image stitching method in corrosion morphology analysis is demonstrated by the segmentation of corrosion image with support vector machine (SVM) based on texture feature. The result shows that the high-resolution corrosion image can be segmented more accurately and easily. Therefore, it is believed that image stitching is a powerful method for the analysis of corrosion morphology in microscopic images, which could make the quantitative study of the corrosion process easier and more efficient.
Toward the Improvement of Emergency Response Utilizing a Multi-Tiered Systems Integration Approach

This chapter presents an extension of the Emergency Description Information Technology (EDIT) project to facilitate the effective collection and communication of information during an emergency. New academic findings and industry technologies inform a modified research framework. The research framework contains four primary research areas that are described in detail. Extending the design-science approach used for the EDIT project could improve emergency communications during large-scale international gatherings, as well as for community emergency response.
Influence of anthropogenic aerosols in near atmosphere in the city of Tirana on ground budget of solar energy

Concentration of anthropogenic aerosols in near atmosphere in the city, mainly due to traffic, plays an important role on reduction of ground insolation, affecting the solar energy budget. There is uncertainty in distinguishing natural from anthropogenic aerosols. However one of main characteristics of anthropogenic aerosols is their time dependence, it is their dependence on the human activity which is the source of aerosols. In a previous work we studied evolution solar insolation on a horizontal surface during a cloudless sky day with number of days after last intensive rain in two close sites in the city of Tirana, two kilometers apart, with very different traffic intensity. It showed quite distinct rates of reduction of daily solar energy after fifteen days, approximate time needed to achieve saturation, of 8.5% and 18.4%. In the present study we try to evidence how this factors influence long term monthly and yearly average solar energy budget. We analyzed solar energy data for two sites during ten consecutive years. It results a mean yearly reduction of daily solar energy not less than 6.5 % between two sites. However the differences differ from one month to the other, achieving a value as high as around 8.2% in summer and around 2.7% in winter.