Miracle-dz/UniFAR-FTUs huggingface dataset:
Zero Trust Network Intrusion Detection System (NIDS) using Auto Encoder for Attention-based CNN-BiLSTM

The large number of connected networks that underpin today’s IT ecosystem make them more vulnerable to cyber threats because of their connectivity, user diversity, amount of connected devices, and services and applications that are available worldwide. As a response to these cyberthreats, zero trust security has been recommended. However, it’s crucial to remember that this kind of security monitoring can be done by outside experts. When cloud-based third parties access network traces, there are threats to data security, thus the present trend in security monitoring needs to change to a "Never Trust, Always Verify" approach. Network Intrusion Detection System (NIDS) can be used to detect anomalous behavior. Convolution Neural Network (CNN) and Bi-directional Long Short Term Memory (BiLSTM) based classifiers and Auto-Encoder (AE) feature extractors have shown promising results in NIDS. AE feature extractor provides possibility of compressing the most important information and training the model unsupervised. CNNs are capable to capture local spatial relationships, while BiLSTMs are good at exploiting temporal interactions. In addition, Attention modules are good at capturing content-based global interactions, and can be applied on CNNs to attend to the most important contextual information. In this work, we utilized the advantages of all AE, CNN and BiLSTM structures using a multi-head Self Attention mechanism to focus and integrate CNN features for feeding into BiLSTM classifier. We proposed to use the bottleneck features of a pre-trained AE for an Attention-based CNN-BiLSTM classifier. Our experiments using 6 and 10 category NID system on UNSW-NB15 dataset showed that our proposed method outperforms state-of-the-art methods and achieved accuracy of 89.79% and 88.13% respectively. Also, we proposed a balanced data sampler for training 10 categories of NIDS which improved the accuracy up to 91.72%. We demonstrated the importance of Attention mechanism through our proposed method.
Rapport Building via a Digital Avatar with a “Voice” Entering into a Customer’s Personal Space

In this paper, we attempt to extend the interpersonal skills of salespeople in a virtual store through operations unique to virtual environments (VEs) that are not possible in a real environment. Utilizing the superiority of visual information over auditory information, we created an interpersonal situation in which only the sound image of an avatar invades the user’s personal space (PS). We investigated the impressions that 16 participants had of this avatar. The results showed that when the sound image invaded the user’s PS and approached the user, rapport significantly increased (p<0.05) for the questionnaire item “I have a harmonious relationship with this salesperson,” while rapport significantly decreased (p<0.05) for the questionnaire item “I feel comfortable engaging with this salesperson. ” These findings suggest that the manipulation of sound image position may allow the salesperson to manipulate the impression held by the customer and there is potential for improving the interpersonal skills of salespeople. The method proposed in this paper, in which the position of the visual and sound image diverge, is expected to improve rapport building and thereby the value cocreation of the interpersonal service in VEs, such as virtual stores, which have been increasing in recent years.
Machine-aided PPG Signal Quality Assessment (SQA) for Multi-mode Physiological Signal Monitoring

Photoplethysmography (PPG) is a non-invasive technique for recording human vital signs. PPG is normally recorded by wearable devices that are prone to artifacts. This results in signal corruption that decreases measurement accuracy. Thus, a signal quality assessment (SQA) system is essential in obtaining reliable measurements. Conventionally, SQA is mainly driven by human-knowledge and supervised through experts’ annotations. However, they are not tailored for the particularities of the domain applications. Hence, we propose a machine-aided SQA framework that generates respective quality criteria for applications. By using the proposed approach, quality criteria can be easily trained for different applications. Then, quality assessment can be applied to several PPG-based physiological signals telemonitoring. Compared with conventional approaches, the proposed system has a higher rejection rate for high-error signals and a lower mean absolute error is achieved when estimating heart rate (-3.06 BPM), determining respiration rate (–1.36 BPM), and predicting hypertension (+24%). The proposed method enhances accuracy in monitoring physiological signals and thus is suitable for healthcare applications.
Standing Balance Improved by Electrical Muscle Stimulation to Popliteus Muscles

Fall prevention is extremely important when it comes to ensuring the well-being of an aging population. There are currently two main fall prevention strategies: wearing exoskeletons to assist with postural stability and using electrical muscle stimulation (EMS) for training the lower limb muscles. However, the former has issues regarding size and weight, and the latter does not have immediate improvement effects. In this paper, we propose a small and lightweight EMS-based system that immediately improves standing balance by applying EMS to the popliteus muscles behind the knees, which leads to unlocking and bending the knees. Bending the knees lowers the center of mass of the human body and stabilizes the standing balance against unexpected perturbations. We conducted a user study with 20 participants to evaluate the proposed system and found that the postural sway decreased significantly more when EMS was applied within 200 ms after perturbation occurrence compared to when no EMS was applied.
To breach or not? Profiling students’ likelihood of breaching university ICT Codes of Conduct: Student Profiling of Breach of ICT Codes of Conduct

Requiring users to sign commitments to follow Information and Communication Technology (ICT) Codes of Conduct is a common strategy to protect an organisation’s ICT services and resources from misuse and cybersecurity threats posed by internal users. In a university context, students typically need to sign such an agreement prior to having their enrolment confirmed. Unfortunately, compliance with these codes is imperfect, posing organisational cybersecurity risks. This raises the question: can we predict which students are likely to breach these codes of conduct? To answer this question, we developed profiles to predict which students are likely to commit a code breach by collecting the responses of 260 students to five scenario-pairs (breach/non-breach) based on our university’s ICT policy. The study also captured participants’ demographics, moral stances, values, and cyber hygiene practices, to build predictive models of compliance towards the university’s ICT policy. Our findings reveal that most students could identify breaches and appropriate uses of ICT resources. Data modelling found the strength of students’ commitments to ethical principles and knowledge of their university’s ICT Policy were the main predictors of a breach versus non-breach behaviours and confirmed the importance of training in ethics, increasing commitment to the institution, and improving knowledge of the ICT policy and appropriate usage of ICT resources.
Tactile Vectors for Omnidirectional Arm Guidance

We introduce and study two omnidirectional movement guidance techniques that use two vibrotactile actuators to convey a movement direction. The first vibrotactile actuator defines the starting point and the second actuator communicates the endpoint of the direction vector. We investigate two variants of our tactile vectors using phantom sensations for 3D arm motion guidance. The first technique uses two sequential stimuli to communicate the movement vector (Sequential Tactile Vectors). The second technique creates a continuous vibration vector using body-penetrating phantom sensations (Continuous Tactile Vectors). In a user study (N = 16), we compare these two new techniques with state of the art push and pull metaphors. Our findings show that users are 20% more accurate in their movements with sequential tactile vectors.
Development of a Virtual Reality Treatment for Tinnitus - A User Study

Tinnitus is the perception of sound when no external sound source exists. There is currently no cure for tinnitus. Existing treatments aim to mitigate tinnitus through Cognitive Behavioural Therapy and Sound Therapy. Virtual Reality (VR) has been adopted in certain medical fields due to its ability to combine visual and audial stimuli, and create immersive, controlled environments. The purpose of this research was to develop a novel tinnitus treatment, combining VR with existing tinnitus sound therapy, and assess its usability. A user study with 18 healthy participants was conducted. Quantitative and qualitative analyses garnered largely positive results. Participants found the application enjoyable, relaxing, and not stressful. The combination of audial and visual elements inside the virtual environment delivered a unified audio-visual stimulus and a sense of control of the location of the auditory stimulus that would serve as a masker sound in future tinnitus masking paradigms. More elaborate environments (beach and forest) were perceived as more enjoyable and realistic than a scene with minimal content for functionality. The beach scene was perceived as the most relaxing set-up, but the forest scene was preferred overall. Our results suggest the VR application can be developed into a multisensory tinnitus treatment and that future testing of the application in a sample of patients with bothersome tinnitus is justified. We provide guidelines for future researchers looking to create their own VR tinnitus tools.
Ice Detection on Edge Device Based on Most Significant Digit First SVM

Abstract- The present notion of smart cities inspires urban planners and academics to provide citizens with modern, secure, and sustainable infrastructure and a decent standard of living. To meet this demand, video surveillance cameras have been installed to improve the safety and well-being of the populace. Despite technological advances in modern science, detecting anomalous events in surveillance video systems is difficult and takes extensive human effort. Due to the context-dependent nature of the anomalous concept, we identify several objects of interest and freely accessible datasets for anomaly detection. Iced surface in highways is one of the serious anomaly which causes a large number of accidents on the highway every year. CCTVs installed on highways can be a good tool to detect iced surface. Detection is a time-sensitive application of computer vision; hence, this paper has concentrated on investigating iced surface detection using edge devices and methods. We have leveraged Most-Significant Digit First arithmetic to improve the performance and resource utilization of the Support Vector Machine. We have applied our proposed method to address the problem of ice detection on highways, where the experimental results indicated a significant improvement in terms of accuracy, speedup, and energy consumption. These metrics are essential for edge computing and real-time intelligent surveillance applications.
Brain-Computer Interface using Directional Auditory Perception

We investigate the potential of brain-computer interface (BCI) using electroencephalogram (EEG) induced by listening (or recalling) auditory stimuli of different directions. In the initial attempt, we apply a time series classification model based on deep learning to the EEG to demonstrate whether each EEG can be classified by recognizing binary (left or right) auditory directions. The results showed high classification accuracy when trained and tested on the same users. Discussion is provided to further explore this topic.
Human Coincident Robot: A Non-contact Surrounding Robot Sharing the Coordinate with a Human Inside

The use of wearable robots is gaining traction in the field of human augmentation due to their potential to augment human physical capabilities. However, the design and specification of these robots are often constrained by the physical limitations of the human body. This paper proposes a novel approach called the Human Coincident Robot (HCR), which maintains a fixed positional and rotational relationship with a human without physical contact using a mobile mechanism. We verify the feasibility of this concept through the design and implementation of a two-wheeled mobile robot controlled by sliding mode control. Our experiments with the prototype demonstrate that the implemented system can be used in a situation where a human walks naturally and suggest that the HCR has the potential to overcome the limitations of conventional wearable robots and provide new opportunities for human augmentation.
Comparison of Lipoprotein Analysis Using Gel-Permeation High-Performance Liquid Chromatography and a Biochemistry Analyzer in Normolipidemic and Dyslipidemic Quaker Parrots (Myiopsitta monachus)

Abstract: Lipid accumulation disorders are common in psittacine birds and can be associated with changes in plasma lipoproteins, most notably low-density lipoprotein (LDL) and high-density lipoprotein (HDL). However, lipoprotein analysis by standard laboratory analyzers or an indirect method, such as the Friedewald formula, has not been validated in parrots. A research colony of 12 Quaker parrots (Myiopsitta monachus) were used to compare plasma values from the Roche Cobas c501 biochemistry analyzer for total cholesterol, total triglycerides, LDL, and HDL to gel-permeation high-performance liquid chromatography (GP-HPLC). To increase sample size and broaden the analytical range to include dyslipidemic samples, 2 cross-over studies were performed on a 0.3% cholesterol diet and a 20% fat diet. Agreement between methods was assessed by linear mixed models and Bland and Altman plots. The LDL concentrations calculated by the Friedewald formula and alternative formulas, and the effects of triglycerides on the biases, were also evaluated. Forty-five plasma samples were used. The cholesterol diet induced a marked increase in cholesterol and all lipoproteins, whereas the fat diet did not lead to dyslipidemia. Direct and indirect LDL measurements obtained with the clinical analyzer were not in clinical agreement with GP-HPLC, whereas HDL had acceptable agreement for normotriglyceridemic samples. Hypertriglyceridemic plasma samples were found to interfere with lipoprotein measurements. This study found LDL measured by the Roche Cobas c501 biochemistry analyzer and indirect estimations cannot be recommended in the Quaker parrot, and non-HDL cholesterol should be used instead. Lipoprotein panels obtained from hypertriglyceridemic samples should be interpreted with care.
Canonical frontal circulation patterns in terms of Green's functions for the Sawyer‐Eliassen equation

Green's function solutions for the Sawyer‐Eliassen equation are derived and compared for quasi‐geostrophic and semi‐geostrophic two‐dimensional frontal dynamics in vertically bounded domains. The semi‐geostrophic Green's functions provide a framework for understanding canonical frontal circulation patterns arising from interactions, or coupling, between upper‐ and lower‐tropospheric jet‐front systems. Previously documented conceptual models for these circulation patterns are reproduced by the solutions. A noteworthy finding is that vertical coupling produces a deep and narrow region of ascent when the upper‐ and lower‐tropospheric point sources for the Green's functions share the same sign and absolute momentum surface.
Generalized minimax theorems for two set-valued mappings

The generalized minimax theorems of two real set-valued mappings, which generalize and improve the corresponding conclusions of D. Kuroiwa (Appl. Math. Lett., 1996, 9: 97-101.) and Li et.al.(J. Optim. Theory Appl., 2000, 106: 183-200; J. Math. Anal. Appl., 2003, 281: 707-723.), and the generalized minimax theorems of two set-valued mappings valued in Frechet spaces are proved. Some examples are given also to show the results.
An analysis of team projects outcomes from student and instructor perspectives in online computing degrees

Abstract One of the core aims of higher education degrees is to provide an environment for students to acquire essential skills that will help them in the workplace. Team working is one of those essential skill and it is also one that experience and research show is regularly resisted by students. This resistance can become even more amplified when the degree is delivered online, although some have pointed out that a good team provides much-needed community spirit and support in such environments. The purpose of this study is to review the delivery of a team assessment format that has been specifically designed for the online environment. The results presented provide insight into the student’s perspective on the delivery as well as the reflections of the instructors involved in the delivery. The overall outcome is positive for both parties and provides further guidance on implementation to ensure the pedagogical design continues to be viable. This includes insights into team composition, instructor involvement, and peer review scoring formats.
Relating drought indices to impacts reported in newspaper articles

Relating drought indicators and real‐world impacts is fundamental for understanding and addressing drought vulnerability. We link drought indices and impacts from newspapers compiled in the Irish Drought Impacts Database (IDID) for the period 1900–2016. For three catchment clusters across the island of Ireland we link the Standardized Precipitation Index (SPI) with land‐based impacts and the Standardized Streamflow Index (SSI) with water‐based impacts by matching total reported articles per month with concurrent drought indices. Using logistic regression we find SPI‐3 links best with land‐based impact reports, whereas SSI‐2 links best with water‐based impact reports. Catchments in the east/southeast display the highest sensitivity to land‐ and water‐based impacts; however, in summer months at low deficits northwestern catchments show a higher likelihood of impact reports. In winter months the likelihood of water‐based impacts is considerably greater than the land‐based equivalent, particularly in east/southeastern catchments. Moreover, the likelihood of news‐worthy drought impacts has changed over the 117 year period. More severe deficits are required to induce a high likelihood (0.6) of land‐ and water‐based impacts in east/southeastern and southwestern catchments during 1961–2016 compared with 1900–1960. Largest changes emerge in the southwest with SPI‐3 values of −2.51 (<−3.00) required to reach the high impact likelihood threshold in the pre (post) 1961 period. Even greater reductions are found for water‐based impacts in the southwest with SSI‐2 values associated with high impact likelihoods changing from −2.04 to −2.58. Conversely, for catchments in the northwest more moderate drought deficits result in high impact likelihoods for both land‐based (from <−3.00 to −2.32 SPI‐3) and water‐based impacts (from <−3.00 to −2.29 SSI‐2) for the 1961–2016 period. These findings show the value of newspaper archives for understanding regional sensitivities to drought plus their potential for underpinning a near real‐time, drought monitoring and warning system in Ireland.
Influence of a thin dielectric layer on resonance frequencies of square SRR metasurface operating in THz band

Abstract This article investigates the effect of an additional thin dielectric layer on the top of the metasurface (MS), on the transmission of electromagnetic waves in the terahertz band. For this purpose, the split ring resonator-based MS was designed and analyzed in the terahertz band. The influence of permittivity, film thickness, and suspension height on S 21 transmission coefficient characteristics was studied. For this purpose, a numerical model was created and solved using the finite element method. The conducted study can be helpful in three cases. First, changing the suspension height of the dielectric layer may allow tunable MSs using MEMS structures. Also, this research can be used to determine the effect of applying an additional layer of protection when using the MS as a sensor to test substances that can damage it. In addition, there is an opportunity to study the dielectric properties of thin films using the proposed MS.
Why every library needs design

Abstract A library’s single most important principle is human engagement. Design is a necessary component for libraries to stay relevant with a willingness to learn and engage. This article details what it means to design, to think like a designer, and features transferable job skills to design. Design in libraries is emphasized in traditional and nontraditional forms. Practical applications also highlight the necessity for tutorials and design tools. A library that does not engage in design is a library that deteriorates for lack of organized function and human connection.
Perspective-Taking: A Key to Overcoming the Barriers and Limitations of Legal Inclusion for Students with Physical Disabilities in Physical Education

Abstract The purpose of this paper is to discuss the limitations of law interpretations and policy regulations as they pertain to inclusion and exclusion of people with physical disabilities in physical education. We believe interpretation of the law has professional implications that must be addressed. Specifically, the ideal and the reality of the laws as applied to the students with physical disabilities is not the same. We believe we have a duty to include people with physical disabilities in movement activities. To conclude the paper, we, the authors, discuss current research in perspective-taking for pre-service teachers as a solution for including people with physical disabilities in physical education, recreation, and sport.
The mentor–tutor partnership in Turkish special education initial teacher training: an exploration of collaboration and agency

ABSTRACT This paper explores the perspectives of the tutors and mentors involved in Turkish special education departments` initial teacher training, and how their understanding of and degree of agency shapes the nature of the partnership in it. The data collected from four partnership settings identified three sub-themes: expertise; experience; and expectations. The collective understanding within the teacher training environments shaped the behaviour of individuals. However, rather than working in collaboration with schools, the dominant role in the partnership is either taken by the tutors, and the mentor is largely ignored, or tutors leave the dominant role to the mentors and participate in the system superficially. Exploring the collaboration in Turkish teacher training programmes seems to be an important area to improve the overall quality of teacher training. Looking at ways in which mentors and tutors exert agency offers an opportunity to strengthen levels of collaboration.