Reviewerly/exHarmony huggingface dataset:
Teaching aptitude of teacher educators in relation to their professional ethics

Teaching is a challenging profession and only such teachers can shoulder the heavy responsibilities of nation-building, as they are adequately prepared and have a sound professional aptitude. A teacher is a well-informed person and he makes every effort to assist the student in learning, has the ability to build good human relationships, understanding and skill related to the process of interaction, those who help the student most, is said to have aptitude towards teaching. A teacher not only has to be competent in his subject, method of teaching and in understanding his student, but also should have interest in the profession and have a favorable aptitude towards teaching. Professional ethics is a term used extensively by different people in different contexts. So it is defined in different ways. Teacher competence depends on teaching in a particular setting, the culture and values held in the community. It also depends on the innumerable teacher and student characteristics and the classroom context. Based on these contexts, teacher education and job performance of a teacher are used. Competencies are the requirements of ethics-based teacher education, which includes knowledge, skills and values the trainee teacher must demonstrate for successful completion of the teacher education programme.
An efficient hierarchical identity-based encryption based on uppercaseSM9

分层标识加密能有效减轻标识密码体制中密钥生成中心生成用户私钥和分发私钥的工作量. SM9标识密码作为我国商用密码行业标准和国家标准, 在金融、政务等方面起着重要的作用, 但SM9标识加密算法不具备分层加密的功能, 不适合大规模网络的应用场景, 阻碍了SM9加密算法的部署. 本文基于商密SM9标识加密算法提出一个高效的分层标识加密方案SM9-HIBE. 相比SM9标识加密算法, 方案的密文只增加一个群元素, 解密开销只增加一个双线性对运算, 与接收者标识的长度无关. 方案的安全性基于判定性BDHI困难问题, 在随机谕言模型中可证明方案满足静态选择明文攻击模型下的不可区分性. 最后, 对方案进行比较分析, 结果表明SM9-HIBE在计算开销和通讯代价方面与现有HIBE方案是可比的.
A study on visuomotor and visuotactile synchronization in full body ownership illusion with virtual avatars

Body ownership illusion (BOI), which means 'the illusion that a non-bodily object feels like my body', has been actively studied since the Rubber-hand Illusion showed that a person can feel a rubber hand like one's own hand.It has been proven that BOI can be elicited for virtual bodies in virtual reality.Although many studies have been examined the effect of visuomotor (VM) and visuotactile (VT) stimuli, which are mainly used for the elicitation of BOI, there were very limited studies that delivered both stimuli to the whole body at the same time.In this paper, we investigated how each stimulus affects BOI when delivering VM and VT stimuli simultaneously to the virtual avatar, and examined user experience that appears as presence, emotion, and virtual motion sickness.The results showed that BOI was high when VM is synchronous, but there was no significant difference according to VT levels.In the case of presence, it was confirmed that VT affects only when VM is synchronous, and in the case of emotion, both VM and VT affect valence, and in the case of virtual motion sickness, a statistical difference is not found.These results suggest that overall synchrony of VM is important factor in BOI with virtual avatars, but that the matching VT affects subjective experience such as presence when VM is synchronous.
Non-Homogeneous Haze Synthesis for Hazy Image Depth Estimation Using Deep Learning

Image depth estimation is a technology that is the basis of various image analysis.As analysis methods using deep learning models emerge, studies using deep learning in image depth estimation are being actively conducted.Currently, most deep learning-based depth estimation models are being trained with clean and ideal images.However, due to the lack of data on adverse conditions such as haze or fog, the depth estimation may not work well in such an environment.It is hard to sufficiently secure an image in these environments, and in particular, obtaining non-homogeneous haze data is a very difficult problem.In order to solve this problem, in this study, we propose a method of synthesizing non-homogeneous haze images and a learning method for a monocular depth estimation deep learning model using this method.Considering that haze mainly occurs outdoors, datasets mainly containing outdoor images are constructed.Experiment results show that the model with the proposed method is good at estimating depth in both synthesized and real haze data.
Developing ICT competencies while training scientific personnel

The article analyses the formation and development of ICT competencies when training scientific personnel. It has been shown that the integrated development of science is directly linked to the development of information and communication technologies, regardless of the existing infrastructure for these technologies. The close relationship and mutual influence of science and information technology in different historical periods of human development has been examined. The lists of laws regulating scientific activities have been given, as well as the main principles and definitions of these activities recognized by the legislation of the Republic of Belarus. The prerequisites for the formation of competences in the field of information and communication technologies in a scientific environment have been described. The current competencies that are necessary to conduct scientific and/or scientific-technical (technological) research with further commercialization of scientific and/or scientifictechnical (technological) results in the form of implementation of innovative projects aimed at solving economic, social or other socially important tasks have been analyzed. The article presents a list of the main components of the currently adopted pan-European competence framework which have been divided into three groups: instrumental, reflecting the level of development of cognitive and methodological abilities, technological and linguistic skills of an individual; interpersonal, revealing individual skills&#x0D; (expression of feelings, attitude towards criticism and selfcriticism), social skills (interpersonal relationships, teamwork); systemic, enabling the parts of the competences to be seen in their connection and unity. The article analyses the key modern ICT competencies important for research and academic careers that need to be developed and shaped by young researchers.
Children's Early Reading Ability Through Make-A-Match Based Number Card Play Activities

The purpose of this study was to examine the influence of playing number cards in improving children's initial reading ability based on making a match with a total sample of 20 children. The research uses a quantitative approach with a pre-experimental type of research using one group pretest-posttest design. Based on the research results, the use of number cards improves children's early reading ability. The results of this increase can be seen in the average value of the indicators used, namely distinguishing words and distinguishing sounds/letters at the time of pretest is 2.05, and the percentage of learning completion is 33%. in the posttest there was an increase of 3.65 and learning completion was achieved for all children. This is because in carrying out word card-playing activities, teachers run well according to the stages of playing word cards and learning scenarios that have been prepared.
Fuzzy Logic Controller in a Cuk Converter for Aerospace Application

The paper presents a design of the fuzzy logic controller for Cuk converter. The fuzzy logic controller provides an adaptive control for better system performance and it is used for controlling the non-linear processes. FLC is designed to regulate the output voltage of the converter. Cuk converter is modeled and analyzed using Matlab/Simulink software and it was designed in a closed-loop configuration. Simulation is performed in Cuk converter to verify the proposed fuzzy logic controller. The results confirm that the proposed method achieve much better robustness and adaptability in terms of load change, in input voltage and output voltage variation. It presents better dynamic performance, such as small overshoot, more damping and fast transient time for Cuk converter.
Joint Contrast Enhancement and Noise Suppression of Low-light Images Via Deep Learning

The captured images suffer from low sharpness, low contrast, and unwanted noise when the imaging device is used in conditions such as backlighting, overexposure, or darkness. Learning-based low-light enhancement methods have robust feature learning and mapping capabilities. Therefore, we propose a learning-based joint contrast enhancement and noise suppression method for low-light images (termed JCENS). JCENS is mainly composed of three subnetworks: the low-light image denoising network (LDNet), the attention feature extraction network (AENet), and the low-light image enhancement network (LENet). In particular, LDNet produces a low-light image devoid of unwanted noise. AENet mitigates the impact of LDNet’s denoising process on local details and generates attention enhancement features. Ultimately, LENet combine the outputs of LDNet and AENet to produce a noise-free and normal-light-enhanced image. The proposed joint contrast enhancement and noise suppression network is capable of achieving a balance between brightness enhancement and noise suppression, thereby better preserving salient image details. Both synthetic and realistic experiments have demonstrated the superior performance of our JCENS in terms of quantitative evaluations and visual image qualities.
A Selective Population-based Algorithm with Multi-Perturbative Operators for Traveling Salesman Problems

A selective population-based algorithm with multi-perturbative operators is proposed in this article for the classical combinatorial optimization problem: traveling salesman problem. The proposed algorithm is composed of two important components: perturbative operator set and operator management method. Two types of operators are contained in the perturbative operator set: (1) five basic operators that are most commonly used by metaheuristics in solving traveling salesman problem, (2) five composite operators that are proposed based on the execution sequence of five basic operators. A scoring table method is proposed in this article to manage the operators in the set. Thirty-seven datasets from TSPLIB are adopted to demonstrate the performance of the proposed algorithm. From the experimental results, two phenomena are observed: (1) composite operators obtain better solutions than basic operators on all datasets while consume more running time than basic operators especially on larger datasets, (2) scoring table mechanism enables the algorithm to obtain better solutions on 34 of 37 datasets. Additionally, among eight state-of-the-art metaheuristics, the proposed algorithm outperforms six of them on all datasets used while outperforms the remaining two on 9 of 11 datasets and 21 of 23 datasets respectively.
Risk Reduction Privacy Preserving Approach for Accessing Electronic Health Records

In the healthcare field, preserving privacy of the patient's electronic health records has been an elementary issue. Numerous techniques have been emerged to maintain privacy of the susceptible information. Acting as a first line of defence against illegal access, traditional access control schemes fall short of defending against misbehaviour of the already genuine and authoritative users: a risk that can harbour overwhelming consequences upon probable data release or leak. This paper introduces a novel risk reduction strategy for the healthcare domain so that the risk related with an access request is evaluated against the privacy preferences of the patient who is undergoing for the medical procedure. The proposed strategy decides the set of data objects that can be safely uncovered to the healthcare service provider such that unreasonably repeated tests and measures can be avoided and the privacy preferences of the patient are preserved.
Adopting Organizational Cultural Changes Concerning Whistle-Blowing in Healthcare Around Information Security in the “Internet of Things” World

Medical labs, hospitals, doctor's offices, and medical devices face significant cyber risks. The insecurity of medical devices, including imaging hardware, threatens patient safety. Health organizations are rich with valuable data as well as weak with information security expertise, protocols, and infrastructure. It is critical for more health organizations to focus creating organizational cultures with processes that offer all employees to fully understand the nature of information security risks and have the ability to be active participants in the minimization and reporting of observable risks. This article will lay a foundation to establish techniques and practices for open door policies.
Cybercrime and Private Health Data

As the adoption of electronic health records has reached unprecedented levels and continues to rise rapidly, the issue of criminal activity related with unauthorized patient data acquisition, black market distribution, and illegal exploitation/use becomes increasingly important. This article will provide a historical review of recorded data breaches that resulted in extensive patient data leaks as well as subsequent efforts of monetization via black market structures that utilize the anonymity and counter-tracking environment that the dark/deep web and cryptocurrency provide. It will also focus on the methods and tools used by the villains, the types of vulnerabilities that can result in a successful attack, as well as latest developments and future trends in the field of scientific, technical, and legal/regulatory countermeasures that can be employed in order to prevent sensitive health data from falling into the wrong hands.
Secure Healthcare Monitoring Sensor Cloud With Attribute-Based Elliptical Curve Cryptography

Sensor networks are integrated with cloud in many internet of things (IoT) applications for various benefits. Healthcare monitoring sensor cloud is one of the application that allows storing the patients' health data generated by their wearable sensors at cloud and facilitates the authorized doctors to monitor and advise them remotely. Patients' data at cloud must be secure. Existing security schemes (e.g., key policy attribute-based encryption [KP-ABE] and ciphertext policy attribute-based encryption [CP-ABE]) have higher computational overheads. In this paper, a security mechanism called attribute-based elliptical curve cryptography (ABECC) is proposed that guarantees data integrity, data confidentiality, and fine-grained access control. It also reduces the computational overheads. ABECC is implemented in .NET framework. Use of elliptical curve cryptography (ECC) in ABECC reduces the key length, thereby improving the encryption, decryption, and key generation time. It is observed that ABECC is 1.7 and 1.4 times faster than the existing approaches of KP-ABE and CP-ABE, respectively.
Medical Signal Security Enhancement Using Chaotic Map and Watermarking Technique

This chapter explores medical signal security enhancement using chaotic map and watermarking techniques. This new approach provides security to both the medical image and also maintains the confidentially of both the patient and doctor. Medical image encryption is done by using 2D Gaussian iterated map and BARCODE ECC200. Personal data is encoded in barcode. The encrypted image and barcode are embedded using DCT and DWT, which provides high PSNR values and higher NC value, which help to provide more security.
Implementation of a Reversible Watermarking Technique for Medical Images

Electronic health records (EHR) contain patients' medical as well as personal details. With the increased use of digital media, these data are stored and transferred through the electronic media all over the world. This makes it vulnerable to unauthorized people. Digital image watermarking can be a useful process of protecting these data from attacker but causes severe and unrecoverable damage to cover media. In the case of highly sensitive images like medical images, this might creates a problem during further diagnosis. In this chapter, a reversible data hiding algorithm is proposed which also is capable of holding a large chunk of data without affecting the cover media. The main cover image is first reconstructed and hidden behind a bigger media and then the extra pixels are used to hide encrypted forms of EHR data along with an authentication signature. As EHR data and the digital signature is passed through various encryption stages while encoding, it is made more secure. The algorithm is developed on the spatial domain adding some cautious measures which made it fragile as well.
Electronic Health Record Security in Cloud

Security is the primary issue nowadays because cybercrimes are increasing. The organizations can store and maintain their data on their own, but it is not cost effective, so for convenience they are choosing cloud. Due to its popularity, the healthcare organizations are storing their sensitive data to cloud-based storage systems, that is, electronic health records (EHR). One of the most feasible methods for maintaining privacy is homomorphism encryption (HE). HE can combine different services without losing security or displaying sensitive data. HE is nothing but computations performed on encrypted data. According to the type of operations and limited number of operations performed on encrypted data, it is categorized into three types: partially homomorphic encryption (PHE), somewhat homomorphic encryption (SWHE), fully homomorphic encryption (FHE). HE method is very suitable for the EHR, which requires data privacy and security.
A New Perspective on the Swiss Cheese Model Applied to Understanding the Anatomy of Healthcare Data Breaches

The healthcare industry has been lagging behind other industries in protecting its vital data. Over the past few years, researchers and practitioners have been trying to gain a better understanding of the anatomy of healthcare data breaches. In this chapter, the authors show how Reason's swiss cheese model (SCM) provides a powerful analytic model to explain the human, technical, and organizational factors of healthcare data breaches. They also show how the SCM brings forwards the latent conditions of healthcare data breach incidents that have often been overlooked in previous studies. Based on an extensive literature review and an analysis of reported breaches from credible sources, the authors provide an explanation of the cheese layers and the associated holes. Since the SCM endorses the “defenses in depth” approach, it can assist healthcare organizations and business associates in developing a comprehensive and systematic approach to prevent and mitigate data breach incidents.
“Sensitive but Essential Information”

As fitness trackers and applications grow popular, many actors involved in the development, use, and regulation of these devices expressed concerns of privacy and control of data gathered through these platforms. This chapter explores how government representatives, industry leaders, regulators, and politicians discursively constructed and critiqued data privacy in fitness applications in congressional contexts. Findings indicate the following discourses: (1) fitness trackers as indicative of larger data collection issues, (2) weighing the pros and cons of use, (3) military implications for fitness application data security, (4) consumers as responsible for their own data privacy, (5) organizations failing to keep pace with cyber security threats, and (6) the misuse of data collected in fitness applications for promotion/strategic communication uses.
Integer Transform-Based Watermarking Scheme for Authentication of Digital Fundus Images in Medical Science

This chapter presents an integer transform-based watermarking scheme for digital fundus image authentication. It is presented under multimedia applications in medicine. The chapter introduces image authentication by watermarking and digital fundus image. The key requirements in developing watermarking scheme for fundus images and its challenges are identified and highlighted. Authors describe a proposed watermarking scheme on integer transform. The experimental results emphasize the proposed scheme's ability in addressing key requirements and its attainment. The detailed results are summarized.
Blockchain for Healthcare and Medical Systems

Blockchain is one of the trendy technologies in the current era. All industries are merging blockchain with their production line to benefit from its features such as security and decentralized data. One of the main problems in the healthcare system is the lack of interoperability (i.e., data should be patient-centered and not institution-centered). Healthcare information systems, in the current state, cannot communicate. Each organization works within its boundaries and owns its data. To make this shift, many challenges should be solved such as data privacy, standards, scalability, and others. Blockchain can solve these problems by giving the patients control over their data; therefore, they can share it with any institution for a time period. It is expected that blockchain will improve healthcare data management. In this chapter, the authors study the opportunity of blockchain to leverage biomedical and healthcare applications and research. Blockchain also contributes to the medication manufacturing area.
Cyber-Physical Security in Healthcare

The healthcare sector has been considered a part of critical infrastructure (CI) of society and has faced numerous physical-cyber threats that affect citizens' lives and habits, increase their fears, and influence hospital services provisions. The two most recent ransomware campaigns, WannaCry and Petya, have both managed to infect victims' systems by exploiting existing unpatched vulnerabilities. It is critical to develop an integrated approach in order to fight against combination of physical and cyber threats. In this chapter, key results of the SAFECARE project (H2020-GA787005), which aims is to provide solutions that will improve physical and cyber security, to prevent and detect complex attacks, to promote incident responses and mitigate impacts, will be presented. More specifically, healthcare critical asset vulnerabilities; cyber-physical threats that can affect them; architecture solutions, as well as, some indicative scenarios that will be validated during the project will be presented.
Multiple Blind Watermarking Framework for Security and Integrity of Medical Images in E-Health Applications

Nowadays, e-health applications carry the most advanced information and communication technologies for ensuring quality, remote healthcare services, and support diagnostics. These applications are sharing and transmitting of medical data over the internet, which makes them serious targets for alteration and illegal access. Image watermarking presents a compelling solution for protecting patient's information and ensures medical image integrity. This paper gives a new secure framework to protect medical data based on blind multiple watermarking schemes. The proposed approach consists of combining LWT (lifting wavelet transform), QR decomposition, and Arnold chaotic map in transform domain for the first watermark, while for the second watermark is encrusted in the spatial domain. During the de-watermarking process, both extracted watermarks are compared to detect any alterations during transmitting. The experimentation results demonstrate that the suggested method achieves good image fidelity and alters detection and robustness contra different kinds of attacks.