Miracle-dz/UniFAR-FTUs huggingface dataset:
AF Relaying Secrecy Performance Prediction for 6G Mobile Communication Networks in Industry 5.0

Industry 5.0 has developed in full swing, and accelerated the process of the sixth-generation (6G) mobile communication. Physical layer security is important for complex 6G mobile communication networks. To process active complex events in 6G mobile cooperative networks, predicting secrecy performance in time is essential for the mobile communication quality evaluation. Using amplify-and-forward (AF) relaying, we propose a transmit antenna selection (TAS) based secrecy scheme in this article. To analyze the security of 6G mobile cooperative networks, signal-to-noise ratio of the end-to-end link is used to derive the novel expressions for secrecy outage probability (SOP). The theoretical results are confirmed by simulation results. Then, we use SOP as the important merit to evaluate the secrecy performance, and set up the dataset. To achieve secrecy performance prediction, a convolutional neural network (CNN) based SOP prediction algorithm is proposed. The designed CNN model has five convolution layers, which all use the same convolution in the padding and do not change data size. For this improved CNN structure, we adopt the idea of SqueezeNet, which belongs to the lightweight CNN. The improved CNN model can greatly reduce the parameters and network complexity on the premise of ensuring the prediction accuracy. We also examine the following state-of-the-art techniques, first, Elman, second, InceptionNet, third, deep neural network (DNN), and fourth, support vector machine methods. The proposed CNN algorithm can achieve better SOP prediction results than other existing methods. In particular, compared with DNN method, the prediction accuracy is increased by 66.7%.
A Ligthweight Wayfinding Assistance System for IoT Applications

: In this paper, we propose to design an indoor sign detection system for industry 4.0. In order to implement the proposed system, we proposed a lightweight deep learning-based architecture based on MobileNet which can be run on embedded devices used to detect and recognize indoor landmarks signs in order to assist blind and sighted during indoor navigation. We apply various operations in order to minimize the network size as well as computation complexity. Internet of things (IoT) presents a connection between internet and the surroundings objects. IoT is charac-terized to connect physical objects with their numerical identities and enables them to connect with each other. This technique creates a kind of bridge between the physical world and the virtual world. The paper provides a comprehensive overview of a new method for a set of landmark indoor sign objects based on deep convolutional neural network (DCNN) for internet of things applications.
Accessibility of maternal health information and its influence on maternal health preferences in rural Tanzania: A case study of Chamwino District

Background: The access to quality maternal health information amongst pregnant women plays an important role in determining woman’s health behaviour during pregnancy. Yet, access to maternal health information remains a major challenge in Tanzanian rural communities especially for pregnant women leading to low utilisation of skilled maternal health services.Objectives: The study aimed at examining the accessibility of maternal health information amongst pregnant women in rural Tanzania.Methods: A qualitative phenomenological study involving 25 pregnant women, 5 skilled healthcare providers (SHPs) and 5 traditional birth attendants (TBAs) was carried out in Chamwino District, Dodoma Region, Tanzania for a period of 6 months. Data were analysed thematically using the six-stage guide to thematic data analysis with NVivo Software.Results: The acute shortage of healthcare personnel and traditional beliefs influenced pregnant women’s access to quality maternal health information. The majority of women used mothers-in-law and TBAs as their primary source of maternal health information rather than skilled healthcare providers.Conclusion: Despite the acute shortage, healthcare providers need to play a leading role in providing maternal health information amongst the rural populations. Furthermore, skilled health providers need to work in collaboration with the TBAs to increase access to maternal health information and build a well-informed healthy society.
Informing engineering education for sustainable development using a deliberative dynamic model for curriculum renewal

Literature from around the world clearly suggests that engineering education has been relatively slow to incorporate significant knowledge and skill areas, including the rapidly emerging area of sustainable development. Within this context, this paper presents the findings of research that questioned how engineering educators could consistently implement systematic and intentional curriculum renewal that is responsive to emerging engineering challenges and opportunities. The paper presents a number of elements of systematic and intentional curriculum renewal that have been empirically distilled from a qualitative multiple-method iterative research approach including literature review, narrative enquiry, pilot trials and peer-review workshops undertaken by the authors with engineering educators from around the world. The paper also presents new knowledge arising from the research, in the form of a new model that demonstrates a dynamic and deliberative mechanism for strategically accelerating for curriculum renewal efforts. Specifically the paper discusses implications of this model to achieve education for sustainable development, across all disciplines of engineering. It concludes with broader research and practice implications for the field of education research.
Construction of gait adaptation model in human splitbelt treadmill walking

There are a huge number of studies that measure kinematics, dynamics, the oxygen uptake and so on in human walking on the treadmill. Especially in walking on the splitbelt treadmill where the speed of the right and left belt is different, remarkable differences in kinematics are seen between normal and cerebellar disease subjects. In order to construct the gait adaptation model of such human splitbelt treadmill walking, we proposed a simple control model and made a newly developed 2D biped robot walk on the splitbelt treadmill. We combined the conventional limit-cycle based control consisting of joint PD-control, cyclic motion trajectory planning and a stepping reflex with a newly proposed adjustment of P-gain at the hip joint of the stance leg. We showed that the data of robot normal subject model and cerebellum disease subject model experiments had high similarities with the data of normal subjects and cerebellum disease subjects experiments carried out by Reisman et al. 2005 and Morton and Bastian 2006 in ratios and patterns. We also showed that P-gain at the hip joint of the stance leg was the control parameter of adaptation for symmetric gaits in splitbelt walking and P-gain adjustment corresponded to muscle stiffness adjustment by the cerebellum. Consequently, we successfully proposed the gait adaptation model in human splitbelt treadmill walking and confirmed the validity of our hypotheses and the proposed model using the biped robot.
Authentication of a User Using a Combination of Hand Gesture and Online Signature

In real world most of the biometric system shows authentication of user using uni-modal system. In this they use single source of information to authenticate the user such as face segmentation approach or mouse gesture dynamic approach or hand gesture or online signature approach. Some of the limitations exposed by uni-model system can be overcome by using combination of any two approaches. We have already implemented authentication of a user using hand gesture and online signature separately. In order to increase the level of security it is very much essential to combine two authentication modes. The main goal of this paper is to develop a model to authenticate a user using a combination of hand gesture and online signature. When user logs in, they need to register by using both authentication methods. First user is asked to record a gesture using accelerometer followed by signature using digital tablet and pen. Hand gesture device consisting of a tri-axial accelerometer and microcontroller transmission to sense the hand gesture and collect the same. Online signature device consisting of a digital tablet, pen and microcontroller transmission board to sense the online gesture and collect the same. Personal computer receives both gesture and signature as a input and stores in database. During verification user is asked to give both gesture and signature for verification. This work ensures better accuracy and more effectiveness in result and also helps to minimize system error rate. As a result the performance of combination method is 100% and false acceptance ratio and false rejection ratio is zero. Our work has been found to provide better accuracy when compared to existing works.
Numerical simulation on operation of closed‐loop experimental facility with subsonic MHD generator

The operating characteristics and operation procedure of the closed‐loop experimental facility under subsonic power generation have been investigated by means of time‐dependent quasi‐one‐dimensional numerical simulations. Two ways of operation for subsonic power generation were found: (1) subsonic operation both under nonpower and power generation and (2) supersonic operation under nonpower generation and subsonic operation under power generation. For operation (1), Mach number at channel inlet decreases to ∼0.6, therefore it is required to generate plasma under this Mach number. On the other hand, if the plasma cannot be generated, operation (2) needs to be carried out. In this case, a shock wave appears in the generator channel, then the influence of a large pressure change and a vibration caused by a shock wave in the generator channel needs to be considered. © 2008 Wiley Periodicals, Inc. Electr Eng Jpn, 163(1): 25–33, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20399
At the Intersection of Technology and Teaching: The Critical Role of Educators in Implementing Technology Solutions

Educators are critical for the successful implementation of any technology. Acrobatiq by VitalSource can use data to demonstrate the dramatic impact instructors—and their course policies—can have on courseware engagement. Acrobatiq courseware incorporates learning content, formative practice, homework assignments, adaptive practice, and summative assessments into a single learning environment for students, with additional data dashboards for instructors. Previous research has shown that the “learn by doing” approach, central to the courseware, has a six-times effect size on learning than reading alone, so engaging with the formative practice is critical to student success. A statewide system of colleges and universities used Acrobatiq’s Probability and Statistics courseware in a grant-funded initiative. The instructors were all provided extensive training on the courseware features, instructor dashboards, and pacing suggestions before the term began, however, each instructor was able to dictate how they incorporated the courseware into their teaching practice and course grades. We analyzed the courseware data using a visualization called engagement graphs and found a surprising level of variability between instructors. These findings demonstrate the impact that instructors and their policies have on the successful implementation of the courseware. Because engagement is a vital component for the learning benefit of the courseware learning environment, research is needed to better identify implementation practices which affect student engagement. At this intersection of learning science-based technology and teaching practice is immense potential to increase student success.
Exploring the Elements Influencing the Behavioral Adoption of E-Commerce by Chinese Small and Medium Enterprises (SMEs)

This study investigated the behavioral adoption of electronic commerce (EC) among small and medium enterprises (SMEs) in China. This was undertaken by integrating the Technological, Organizational, and Environmental (TOE) framework into the Unified Theory of Acceptance and Use of Technology (UTAUT). The data generated from 349 SMEs were analyzed with SPSS and SmartPLs 3.0 via the utilization of the structural equation modeling (SEM) procedure. The results reveal that while the environmental factor was a positive predictor of the performance expectancy of EC among SMEs, it does not, however, encourage the adoption of EC. Again, while the knowledge factor was not significant in driving the performance expectancy of EC, it was a significant determinant of the adoption of EC among SMEs. Also, the study found that organizational factor was a positive predictor of both performance expectancy and the adoption of EC by SMEs. The technological factor was not a significant predictor of the intention to use EC but was significant in determining the performance expectancy of EC. Finally, the study demonstrated that the performance expectancy of EC was a significant predictor of the behavioral adoption of EC. The managerial and research implications of these findings are deliberated.
A New Trend for Reverse Engineering: Robotized Aerial System for Spatial Information Management

The robotized aerial systems (RAS) are automated systems whose main characteristic is that can be remotely piloted. This property is especially interesting in those reverse engineering works in which the accuracy of the model is not reachable by common aerial or satellite systems, there is a difficult accessibility to the infrastructure due to location and geometry aspects, and the economic resources are limited. This paper aims to show the research, development and application of a RAS that will generate geo-referenced spatial information at low cost, high quality, and high availability.
Comparative study on deep learning models in humor detection

Humor detection is one of the most popular tasks in natural language processing. Yet humor is abstract to numerate, and there isn’t an acknowledged standard for humor assessment. Toward this end, this paper explores the performance of CNN, RNN, BiLSTM in tackling humor detection. We use the regression method and classification method, respectively, to identify the best model. The experiment was conducted on a dataset that is composed of 15,000 news headlines. Results show that the CNN network is a preferable choice, and combined with the classification method, the model obtains the best performance. Though there is plenty of more sophisticated sentiment analysis models, our work offers an intuition for short text sentiment analysis.
Development of a User-Centric Bridge Visual Defect Quality Control Assisted Mobile Application: A Case of Thailand’s Department of Highways

Digital innovations have changed the way many industries operate, but the construction industry has been slow to adopt these technologies. However, challenges such as low productivity, project overruns, labor shortages, and inefficient performance management have motivated Thailand’s Department of Highways to adopt digital innovations to build a competitive advantage. Because this industry requires a large work force, obstacles to collaboration can result in ineffective project management. We aimed to improve collaboration on bridge inspections that typically requires the involvement of many people, personal judgement, and extensive travel to survey bridges across the country. One major challenge is to standardize human judgement. To address these challenges, we developed a user-centric bridge visual defect quality control mobile application to improve collaboration and assist field technicians to conduct visual defect inspection. Our results can be used as a case study for other construction firms to embrace digital transformation technologies. This research also demonstrates the new-product development process using the new technology in known markets innovation development and technology acceptance model. We offer several recommendations for future research, including other infrastructure applications.
The Perspective of Safety Engineers on Safety Climate

The aim of this study was to investigate safety climate and how it relates to the safety performance of employees from the perspective of safety engineers. Using Griffin and Neal's (2000) safety climate model as a theoretical basis, we hypothesized that the organizational safety climate is a higher‐order construct that relates to the safety compliance of employees and their safety participation via the mediating roles of safety knowledge and safety motivation. Hypotheses were tested among 236 safety engineers working in the wood and metal‐processing industries in Austria. Structural equation modeling (SEM) analysis showed that safety climate is a higher‐order construct comprising manager values, safety communication, safety practices, safety training, and safety equipment. Moreover, from the perspective of safety engineers, the safety climate of the organizations was related to employee safety motivation, which in turn related to their safety compliance and safety participation. In contrast to our assumptions, the safety knowledge of employees was, in the view of safety engineers, neither related to employee safety compliance nor to their safety participation. Multigroup analysis revealed no differences between internally and externally employed safety engineers for these relations. Thus, although the safety climate model was generally confirmed from an engineer's perspective, engineers rated motivational aspects of safety climate is more important compared to knowledge aspects.
Groundwater Potential Zone Mapping Using Analytical Hierarchy Process and GIS in Muga Watershed, Abay Basin, Ethiopia

Groundwater is an important resource that contributes significantly to the total annual water supply. The purpose of the present study is to assess and delineate the groundwater recharge zone using geospatial technology through an analytical hierarchal process (AHP) method in to the Muga watershed, Abay Basin. Remote sensing satellite images and the corresponding data are used for the preparation of thematic layers, viz., geology, rainfall, slope, soil, curvature, topography wetness index, elevation, drainage density, land use land cover, and lineament density of the study watershed. All thematic layers are integrated with a multicriteria evaluation technique. Weighted overlay index analysis is carried out to give rank for each parameter. The weight is assigned for each thematic layer depending on the AHP technique. The reliability of the output is checked by the calculated consistency index and consistency ratio which is reasonably acceptable (0.044 < 0.1). Verification is done by considering the groundwater well locations in the validation datasets. The receiver operating characteristic curve and area under curve (=82.9%) are used to explore the prediction accuracy.
Constant time O(1) image fog removal using lowest level channel

In this reported work, the lowest level channel prior is proposed for image fog removal. The use of the lowest level channel is simplified from the dark channel prior. It is based on a key observation that fog-free intensity in a colour image is usually the minimum value of trichromatic channels. To estimate the transmission model, the dark channel prior then performs as a min filter for the lowest intensity. However, the min filter results in halo artefacts, specifically for neighbours of edge pixels. Instead of the min filter, this work utilises the exact O (1) bilateral filter to solve this problem. Experimental results show the high performance of the proposed method.
Needing TPACK without Knowing It: Integrating Educational Technology in Social Studies

Preparing future elementary teachers to connect social studies content and skills with technology necessitates the integration of technology into teacher preparation methods courses. Such integration hinges on the identification of pre-service teachers’ level of Technological, Pedagogical, and Content Knowledge (TPACK). These three knowledge areas help shape smart uses for educational technology beyond entertainment that utilize technology in educationally profitable ways. The TPACK model is useful for identifying the knowledge required by pre-service teachers for the purpose of wedding instructional technology to social studies content and instruction. The purpose of this mixed-methods study was to describe and to analyze the integration of an instructional technology lesson in an elementary social studies methods course in a large Midwestern university. The study, specifically, describes and reports on 25 pre-service teachers’ perceptions of the utilization of a social studies software technology called Timeliner. The study reports on the level of TPACK awareness of the study’s pre-service teachers and offers implications related to instructional technology integration in elementary social studies methods courses.
Applying Routine Activity Theory: A Case Study of the Sonya Farak Drug Scandal

Sonja Farak was a chemist for a state crime lab in Massachusetts. She was arrested for tampering with evidence while abusing narcotics at work. Her arrest led to the dismissal of thousands of drug cases in Massachusetts. Given the account that Farak was a law-abiding citizen, it is questioned as to how an educated person with a stable job would commit a crime of this magnitude. Though Farak provided testimony of her behavior, no research has been conducted on the explanation for her crime. To examine her behavior, data from Farak’s Grand Jury testimony are analyzed using a qualitative content document analysis. Examination of the data allows for the application of Cohen and Felson’s Routine Activity Theory, which provides a theoretical understanding of Farak’s evidence tampering and drug use. All three components (motivated offender, suitable target, and absence of a capable guardian) are presented. By doing so we get a better understanding as to how a law-abiding citizen, while participating in everyday routine life, can commit crime but remain undetected.
Nanomaterials for Chronic Kidney Disease Detection

Chronic kidney disease (CKD) is a dilapidating problem that causes great global burden since the current therapeutic options are mostly ineffective. Early diagnosis and efficient treatment are essential to prevent the progression of CKD. Nanoparticles as technological drivers of innovation have emerged in biomedical studies for different theranostic applications. Several nanoparticles have been developed, which can be labeled with targeting moieties for both drug delivery and/or imaging systems and are investigated to detect different pathological conditions. The focus of this review is to demonstrate the current research and clinical applications for nanoparticles in the diagnosis of CKD and other renal diseases that will probably result in CKD.