Miracle-dz/UniFAR-FTUs huggingface dataset:
Line-Based Stereo SLAM by Junction Matching and Vanishing Point Alignment

In this paper, we propose a stereo simultaneous localization and mapping (SLAM) method based on line segments. For the front-end module of SLAM, we designed a novel method based on the coplanar junction detection, description, and matching. Then the junctions along with their multi-scale rotated BRIEF descriptors are used in other SLAM modules, including line tracking, mapping, and loop closure. The line extraction and matching thread runs at 20 ~ 40Hz for stereo image sequences on a laptop, making it a practical front-end for line-based SLAM system. For the back-end module, a cost function is designed to minimize both of the reprojection error of line segments and alignment error of the vanishing points. The experimental results demonstrate that the proposed method exhibits more accurate localization and reconstruction than state-of-the-art line-based SLAM systems in line-rich environments.
E-Government in Developed and Developing Countries: A Systematic Literature Review

The purpose of conducting this systematic literature review is to analyze the previous research published on e-governance services, to find out the differences between e-government projects in developing and developed countries. This research focuses on the factors that causes developing countries to refrain from providing e-governance benefits to everyone on the receiving end. This paper also finds out the factors that could be adopted from developed countries to improve e-governance in developing countries. The basic aim of e-governance is to provide “Equality of Opportunity”, because citizens are the main participants in the e-government services so the main focus would be to find out the factors that extend equality to everyone. Mostly e-government projects are trusted by the well-educated citizens so we aimed to find the reasons of trust issues on government. Through a systematic literature review, a study on the current research on e-governance services was performed. The findings were discussed and efforts were made to impose improvements where the flaws occurred in e-services in developing countries that in turn give trust and economic growth to countries.
Quadrature Index Modulation With Three-Dimension Constellation

Quadrature spatial modulation (QSM) is a novel index modulation technology, which extends the antenna index (AI) to two dimensions of both in-phase AI and quadrature AI. In order to further make full use of the idle transmit antennas (TAs) resource and to exploit the signal constellation domain, taking advantage of the spatial dimension of QSM, we propose a new three-dimension (3D) structure of quadrature index modulation (QIM), which is capable of not only transmitting directly a 3D constellation symbol but also carrying more extra information bits, named as quadrature index modulation with three-dimensional constellation (QIM-TDC). More specifically, a 3D framework of QIM-TDC is designed for transmitting a 3D constellation symbol that is constructed by the <inline-formula> <tex-math notation="LaTeX">$X$ </tex-math></inline-formula>-axis, <inline-formula> <tex-math notation="LaTeX">$Y$ </tex-math></inline-formula>-axis and <inline-formula> <tex-math notation="LaTeX">$Z$ </tex-math></inline-formula>-axis components. In the proposed QIM-TDC scheme, by utilizing an in-phase AI vector, two active TAs are activated simultaneously to transmit the <inline-formula> <tex-math notation="LaTeX">$X$ </tex-math></inline-formula>-axis and <inline-formula> <tex-math notation="LaTeX">$Y$ </tex-math></inline-formula>-axis components of the 3D symbol, respectively. Similarly, by utilizing the quadrature AI vector, an active TA is activated to transmit the <inline-formula> <tex-math notation="LaTeX">$Z$ </tex-math></inline-formula>-axis component of the 3D symbol. Then, for further achieving the better bit error probability (BEP) performance, the design of a modified 3D constellation for maximizing the squared minimum Euclidean distance (MED) between the transmitted spatial vectors (TSVs) is illustrated. Moreover, the squared MEDs for QIM-TDC are analyzed and compared with the squared MEDs of the conventional spatial modulation schemes. Finally, The average BEP is analyzed in this paper. Numerical results with comparison among the other schemes demonstrate the QIM-TDC scheme achieves the improved performance.
Using Eye-tracking to get information on the skills acquisition by the radiology residents

This paper describes the possibility of monitoring the progress of knowledge and skills acquisition by the students of radiology. It is achieved by an analysis of a visual attention distribution patterns during image-based tasks solving. The concept is to use the eye-tracking data to recognize the way how the radiographic images are read by recognized experts, radiography residents involved in the training program, and untrained users who graduated from biomedical engineering. The results of research presented in this paper support the usefulness of earlier elaborated eye metrics, Visual Attention Time Product VATP, for skills measurement when using Electronic Medical Record for CT images evaluation. Moreover, it appears that it is possible to differentiate the level of residents skills in radiology structures recognition. Presented methodology can also be utilized in other areas where operator performs image related tasks.
Design of Optimum Configuration and techno-economic analysis of a Hybrid Power System

Due to shortage of power and losses Pakistan is facing load shedding up to sixteen hours in some reigns of the country in summer season. This causes disturbance in daily routine life and disruption in case of sensitive loads like academics work and hospitals. Diesel generators are used as an alternate source in the shortage hours which has very high fuel cost, noise and emissions. The purpose of this paper is to study the integration of photovoltaic generators into an existing diesel-unreliable grid connected system at Shifa Hospital, Lakki Marwat. The main goal of implementing hybrid system is to reduce the consumption of diesel and the import of fossil fuel used. Detailed simulations and financial analysis of four different cases are performed with HOMER to compare different systems and their viability. PV-diesel hybrid system is proposed with a PV capacity of 25 kW, existing diesel capacity with 50 kw, an inverter output of 30 kW and battery bank. The system renewable fraction is 28.4% and the project life cycle is 25 years. The PV-diesel hybrid system is projected to produce electricity at a cost of 14PKR/KWh. This cost is significantly lower than the production cost of the existing diesel generator and grid system which is 32PKR/KWh. The suggested system significantly reduces the pollutant gases by 50%.
Sparse EEG Source Localization Under the Variational Bayesian Framework

In this paper we propose a new method for EEG source localization. Solving the above problem usually requires choosing an appropriate regularization term. Our method is based on the bayesian approach, hence, the regularization term is closely connected to the prior distribution. The proposed prior distribution has sparse properties favoring focal EEG sources. In order to obtain an efficient algorithm we use the Variational Bayesian framework which provides us a tractable iterative algorithm of closed form equations. We compare the proposed method with well-known approaches of EEG source localization and the results, using synthetic and real EEG data, have shown that our method presents state-of-the-art performance, especially in cases where we expect few activated brain regions.
Peachy Parallel Assignments (EduHPC 2020)

Peachy Parallel Assignments are high-quality assignments for teaching parallel and distributed computing. They are selected competitively for presentation at the Edu* workshops. All of the assignments have been successfully used in class and they are selected based on the their ease of adoption by other instructors and for being cool and inspirational to students. This paper presents a paper-and-pencil assignment asking students to analyze the performance of different system configurations and an assignment in which students parallelize a simulation of the evolution of simple living organisms.
Free Maternal and Child Health Services in Enugu State, South East Nigeria: Experiences of the Community and Health Care Providers

Enugu State, South East Nigeria launched free maternal and child health services in 2007 against the backdrop of high infant and maternal mortality rates in the State. This study determined the experiences and the perceptions of the community and health care providers on the free maternal and child health services. This was a cross sectional descriptive study carried out in Enugu state Southeast Nigeria. Pre-tested interviewer-administered questionnaire survey with 50 healthcare providers at health centers and 150 women of reproductive age were used to elicit information on the awareness, attitude, utilization and factors affecting utilization of MCH services, satisfaction with and willingness to continue use of these services. In addition, service data from the first health center to benefit from free MCH services was collected from 2007 to 2009. Among the women, there was a high level of awareness of the free MCH services. Antenatal (55.3%), maternal tetanus toxoid immunization (47.3%) and childhood immunization (44%) services were the most accessed. Factors likely to affect the intention to use the services were required services not rendered, drugs not available, delayed attention and distance to the health facility. There was a high willingness to continue use of maternal and child health services due to the free services, easy accessibility and availability of drugs. However, a fifth of the respondents paid for the free services. The service data showed an upward increase in utilization between 2007 and 2009. Although the health workers were receptive of the free MCH services, they opined that their workload had increased without any corresponding increase in their remuneration and that patients were making unnecessary visits to the health facilities to demand on drugs. There was a significant increase in MCH services utilization between 2007 and 2009. Conclusion: This study shows that the free MCH services have enhanced utilization of health services. However this has greatly increased the workload of health providers and consumers still pay for services. There is need therefore for provision of adequate personnel and infrastructure to cater for this increase. In the interim there should be better remuneration of health workers to motivate them to continue providing health services despite the workload. There is also need to check the reported over visitation of health centers for drugs created by the free MCH services and mechanisms should be put in place to ensure that the free services are really free.
Student Readiness for Online Learning in Relation to Gender and Stream of Study

A study was undertaken to determine the students’ readiness for online learning in relation to gender and stream of study. A questionnaire consisting of 79 statements and measuring seven components was sent to 30 institutions of higher learning. These components include: student access to technology, technology skills, life style factors, cognitive presence, teaching presence, social presence and study habits & skills, 1168 filled - in questionnaires were received. Majority of the students have access to technology, possess technological skills and required study habits, exhibit desired life style for e learning and would be able to participate productively in e learning environment. Female students showed higher mean scores on life style factors and teaching presence than the male students. Students of general education had significantly higher mean scores on social presence and study habits & skills than the students of technical education.
Analysis of Band Gap in AA and AB Stacked Bilayer Graphene by Hamiltonian Tight Binding Method

The electronic properties of AA and AB-stacked bilayer graphene has been carefully investigated by the principle of Hamiltonian tight binding model. It is determined that the AA-stacked bilayer graphene not showing any significant response to the change in the applied electric field. However, we find that the AB-stacked bilayer graphene showing a tunable energy band gap from 0 to 0.27 eV under the applied electric field. It is also concluded that the stacking sequence of bilayer graphene and charge distribution in the inter and intra-graphene layer determine the energy band gap structure. Based on the applied mechanism, the bandgap of AB-stacked bilayer graphene can be engineered under direct current (DC) and low amplitude electric filed potential for the optical excitation.
Ansatte på sykehus sine holdninger til eldre pasienter med urininkontinens

Staff members meet urinary incontinence (UI) among elderly in their daily practice. It is documented that knowledge about UI contains misunderstandings. The aim of this study was to get insight in staff's attitudes towards elderly patients with UI. Both qualitative and quantitative methods were included. Focus group interviews were used in the qualitative part. One group of six registered nurses and one group of six nursing assistants (one-year education), working in an elderly care setting in hospital, were included. The transcribed interviews were analysed and the data systematized and categorized before interpretation. The quantitative part is not described in this article. Results show that even though staff intended to take care of patients with UI and treat them with respect, UI was not considered specifically. One reason for this was a lack of consciousness because UI problems were trivial. Medical oriented diagnosis were given higher priority and there was a severe lack of knowledge among staff members of UI. Patients were not asked by the staff about their own reactions related to their UI. However, staff members were able to question their own practice and they claimed that the present study stimulated them to be more conscious about the patients' UI.
Dualattn-GAN: Text to Image Synthesis With Dual Attentional Generative Adversarial Network

Recent generative adversarial network based methods have shown promising results for the charming but challenging task of synthesizing images from text descriptions. These approaches can generate images with general shape and color but often produce distorted global structures with unnatural local semantic details. It is due to ineffectiveness of convolutional neural networks in capturing the high-level semantic information for pixel-level image synthesis. In this paper, we propose a Dual Attentional Generative Adversarial Network (DualAttn-GAN) in which the dual attention modules are introduced to enhance local details and global structures by attending to related features from relevant words and different visual regions. As one of the dual modules, the textual attention module is designed to explore the fine-grained interaction between vision and language. On the other hand, visual attention module models internal representations of vision from channel and spatial axes, which can better capture the global structures. Meanwhile, we apply an attention embedding module to merge multi-path features. Furthermore, we present an inverted residual structure to boost representation power of CNNs and apply spectral normalization to stabilize GAN training. With extensive experimental validation on two benchmark datasets, our method significantly improves state-of-the-art models over the evaluation metrics of inception score and Fréchet inception distance.
"Study of ER, PR & HER-2/NEU reactivity pattern in the patient of Breast Cancer in northern part of india"

ER,PR, and HER2 represent the most acceptable factors for predicting prognosis, response or resistance to treatment, and potential use of newer drugs such as trastuzumab in the case of HER2 over- expression Objectives- To find out ER, PR, & HER2/neu reactivity in breast cancer patient. Methodology- This descriptive type of observational study included 203 cases of breast cancer.After confirming the diagnosis, either trucut biopsy or final biopsy specimen was employed to ascertain ER/PR status and HER2/neu receptor. Results- In this study, 71(35%) out of 203 cases were HER2/neu positive &132(65%) cases were HER2/neu negative. A significantly higher rate of HER2/neu protein over-expression was found in patients with poor prognostic factors (like large tumor size, high grade tumor and lymph node metastasis). Most of the patients who had HER2/neu protein over-expression were also ER-/PR-. This group (Her2/neu+,ER-,PR-) appeared to represent an aggressive form of breast cancer, presenting at a younger age with large tumor size & lymph node metastasis.Conclusions- HER2/neu testing along with ER/PR status should be performed routinely in all the patients with newly diagnosed breast cancer and therapy against Her2/neu(traztuzumab), should be considered to all patients with HER2/neu over-expression to increase D.F. S. and O.S.
A Plain-Image-Related Chaotic Image Encryption Algorithm Based on DNA Sequence Operation and Discrete Logarithm

According to the research works of the literatures on chaotic cryptanalysis, many recent chaotic image encryption algorithms cannot resist chosen-plaintext attack. Although some chaotic image encryption algorithms introduce plain-image information, they still violate some design requirements of modern cryptosystems. Therefore, after analyzing many literatures related to chaotic image encryption, we propose a plain-image-related chaotic image encryption algorithm based on the deoxyribonucleic acid (DNA) sequence operation and discrete logarithm. As we know, the discrete logarithm calculation is a complex non-linear calculation, introducing it can increase the complexity of the encryption process. More importantly, discrete logarithm values are significantly different under different generators, and the multiplicative group adopted in the proposed algorithm has as many as 128 generators. Therefore, by using two generators determined by the secret key and the hash value of the plain-image respectively, we not only expand the key space, but also greatly improve the plain-image sensitivity and plain-image relevancy of the encryption process. In addition, the proposed algorithm improves the way of using the hash value of the plain-image. In this way, once the secret key is selected, chaotic sequences can be generated in advance and reused to improve the encryption efficiency. Similarly, the proposed algorithm also introduces the DNA sequence operation with high parallelism to further improves the encryption efficiency. Simulation tests and comparative analyses show that the proposed algorithm can not only resist common attacks, but also outperform some recent chaotic image encryption algorithms in many aspects.
Domain Adaptation with Multilayer Adversarial Learning for Fault Diagnosis of Gearbox under Multiple Operating Conditions

Deep learning has been widely developed to solve fault diagnosis issues, and it is becoming a crucial technology in the modern manufacturing industry. As an important transmission device of mechanical equipment, gearbox often runs at different speeds and loads, which may lead to changes in data distribution for the actual application. The cross-domain problem caused by the different data distribution may decline the performance of the fault diagnosis model based on deep learning. To overcome this challenge, a new domain adaptation method, named MAAN: Multilayer Adversarial Adaptation Networks, for fault diagnosis of gearbox running at multiple operating conditions. The basic framework of our MAAD is a deep convolutional neural network (CNN) and then an adversarial adaptation learning procedure is used for optimizing the basic CNN to adapt cross different domain. The results of the experiment demonstrate that MAAN has outstanding fault diagnosis and domain adaptation capacity, and it could obtain high accuracies for fault diagnosis of the gearbox with changing mode. For investigating the adaptability in this method, we use t-SNE to reduce the high dimension feature for better visualization.
Cloud-Based Automated Clinical Decision Support System for Detection and Diagnosis of Lung Cancer in Chest CT

Lung cancer is a major cause for cancer-related deaths. The detection of pulmonary cancer in the early stages can highly increase survival rate. Manual delineation of lung nodules by radiologists is a tedious task. We developed a novel computer-aided decision support system for lung nodule detection based on a 3D Deep Convolutional Neural Network (3DDCNN) for assisting the radiologists. Our decision support system provides a second opinion to the radiologists in lung cancer diagnostic decision making. In order to leverage 3-dimensional information from Computed Tomography (CT) scans, we applied median intensity projection and multi-Region Proposal Network (mRPN) for automatic selection of potential region-of-interests. Our Computer Aided Diagnosis (CAD) system has been trained and validated using LUNA16, ANODE09, and LIDC-IDR datasets; the experiments demonstrate the superior performance of our system, attaining sensitivity, specificity, AUROC, accuracy, of 98.4%, 92%, 96% and 98.51% with 2.1 FPs per scan. We integrated cloud computing, trained and validated our Cloud-Based 3DDCNN on the datasets provided by Shanghai Sixth People’s Hospital, as well as LUNA16, ANODE09, and LIDC-IDR. Our system outperformed the state-of-the-art systems and obtained an impressive 98.7% sensitivity at 1.97 FPs per scan. This shows the potentials of deep learning, in combination with cloud computing, for accurate and efficient lung nodule detection via CT imaging, which could help doctors and radiologists in treating lung cancer patients.
Science teachers’ perceptions of nanotechnology teaching and professional development: a survey study in Taiwan

Abstract Inclusion of nanotechnology in the science curriculum has received great attention in many countries. Taiwan’s government has been funding the National Program on Nanotechnology (NPNT) for nearly 10 years. The purpose of this study was to examine Taiwanese secondary school science teachers’ understanding of nanotechnology teaching after implementing the NPNT, as well as the teachers’ perceptions of school support and their professional development intentions. The study adopted the questionnaire survey method. Using stratified cluster sampling, a total of 1600 questionnaires were distributed to 178 secondary schools. Finally, the responses of 663 junior high school teachers and 632 senior high school teachers who completed the instrument were analyzed. The instrument for the study is the Teachers’ Perceptions of Nanotechnology Teaching Scale (TPNTS). The TPNTS included 42 Likert-scale items. The results reveal that secondary school teachers’ intentions to pursue professional development are high, but their perceptions of school support are low. Teachers’ knowledge and understanding of nanotechnology teaching is significantly above average, but failed to reach the “very satisfied” level. In addition, the senior high school teachers’ perceptions of nanotechnology teaching and professional development are significantly higher than those of the junior high school teachers. Implications of the findings are discussed.