Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving the Path Programmability for Software-Defined WANs under Multiple Controller Failures

Enabling path programmability is an essential feature of Software-Defined Networking (SDN). During controller failures in Software-Defined Wide Area Networks (SD-WANs), a resilient design should maintain path programmability for offline flows, which were controlled by the failed controllers. Existing solutions can only partially recover the path programmability rooted in two problems: (1) the implicit preferable recovering flows with long paths and (2) the sub-optimal remapping strategy in the coarse-grained switch level. In this paper, we propose Programmability Guardian to improve the path programmability of offline flows while maintaining low communication overhead. These goals are achieved through the fine-grained flow-level mappings enabled by existing SDN techniques. Programmabil-ityGuardian configures the flow-controller mappings to recover offline flows with a similar path programmability, maximize the total programmability of the offline flows, and minimize the total communication overhead for controlling these recovered flows. Simulation results of different controller failure scenarios show that ProgrammabilityGuardian recovers all offline flows with a balanced path programmability, improves the total programmability of the recovered flows up to 68%, and reduces the communication overhead up to 83%, compared with the baseline algorithm.
Disruption and creativity in live coding

Live coding is an artistic performance practice where computer music and graphics are created, displayed and manipulated in front of a live audience together with projections of the (predominantly text based) computer code. Although the pressures of such performance practices are considerable, until now only familiar programming aids (for example syntax highlighting and textual overlays) have been used to assist live coders. In this paper we integrate an intelligent agent into a live coding system and examine how that agent performed in two contrasting modes of operation—as a recommender, where on request the the agent would generate (but not execute) domain-appropriate code transformations in the performer’s text editor, and as a disruptor, where the agent generated and immediately executed changes to the code and the streaming music being performed. A within-subjects study of six live coders suggested that participants of the study preferred the agent’s disruptive mode as a mechanism for enhancing the creativity of their live coding performances.
A Novel Architecture of SQU SMART LMS: The New Horizon for SMART City in Oman

The smart city along with smart technologies are becoming increasingly important. Few factors are considered as the drivers for the city's sustainability and competitiveness. The most important factor is represented through the readiness of the citizens to face the new lifestyle, which is embedded with smart knowledgeable tools. Hence, citizens need to be smartly educated in all areas of science and humanities. From this point of view, researchers are motivated to explore the best existing tools or design new tools to enhance the technology towards Smart Learning Environment (SLE). SLE would promote not only effective learning for learners but also provide adequate learning resources and convenient tools for interaction. This paper concentrates on using the aspects of software engineering in designing the novel architectural model for SQU smart LMS to foster smart education. This architecture integrates a smart learning environment into the service layer of the framework of the smart city system in Oman. This paper presents the abstract novel model of ongoing research work.
Relationships between obesity, body composition and continuous glucose monitoring parameters in subjects with type 2 diabetes on insulin therapy

Background and aimInsulin resistance often develops against the background of obesity and can modify daily blood glucose fluctuations in men and women with diabetes (DM). In this study we aimed to determine the relationships between obesity, body composition and daily dynamics of glucose, assessed by continuous glucose monitoring (CGM), in individuals with type 2 DM treated with insulin.Materials and MethodsOne hundred and thirty sixpatients with type 2 diabetes treated with insulin were examined. Real-time and blinded CGM was performed in hospitalized patients. Time in ranges and a panel of parameters of glucose variability (GV) were identified from CGM recordings.ResultsSubjects with obesity, as compared to those without, demonstrated significantly reduced Time Below Range, Low Blood Glucose Index, Lability Index, Men Absolute Glucose (all p <0.05) and a tendency to lower Mean Amplidude of Glucose Excursions (p=0.08), higher glycated hemoglobin A1c (p = 0.07). There were negative correlations (all p < 0.05) between total fat mass (FM) and Standard Deviation (r = −0.53), Mean Amplitude of Glucose Excursions(r= - 0.38), Lability Index (r = −0.51), HighBloodGlucose Index (r = −0.33), MAG (r = −0.57). Truncal FM, android and gynoid FM demonstrated negative correlations with these GV parameters also.ConclusionsThese data demonstrate the association between obesity, body composition and CGM parameters in insulin-treated in type 2 DM patients. Reduced GV and diminished risk of hypoglycemia is associated the presence of obesity and accumulation of adipose tissue.
Frequency dielectric spectroscopy and an innovative optical sensor to assess oil-paper degradation

In this paper, frequency dielectric spectroscopy (FDS) and an innovative optical sensor for the detection of 2-furaldehyde (2-FAL) are used to check the degree of ageing of differently processed oil-paper specimens when exposed to thermal stress. The analysis of the trend of moisture content and of 2-FAL concentrations confirms the influence of drying pre-treatment of the specimens on their ageing conditions. FDS elucidated the nature of the drying process of the specimens and the optical sensor correctly assesses a lower 2-FAL production for the vapour phase dried specimens during thermal exposure.
Low Offset and Noise in High Biased GaN 2DEG Hall-Effect Plates Investigated With Infrared Microscopy

This article presents GaN two-dimensional electron gas (2DEG) Hall plates with low residual offset and noise at 3 V input bias. We studied devices made from three consecutive fabrication generations through current spinning offset measurements in a zero-field chamber. When operated above 1 V, the first-generation devices charted high residual offsets >1 mT. We reduced these residual offsets by three orders of magnitude in later device generations. Two experiments were performed to confirm the improvements. First, the GaN 2DEG Hall-effect plates were measured with infrared microscopy during current spinning to investigate current crowding and Joule heating. The low offset devices had minimal thermal gradients while the high offset devices had large thermal variations during current spinning. Second, zero-field current spinning was used to compare GaN 2DEG Hall-effect plates against typical commercial silicon Hall-effect plates. The Si devices had residual offsets <inline-formula> <tex-math notation="LaTeX">$> 10\mu \text{T}$ </tex-math></inline-formula> biased at 3 V and AlGaN/GaN devices had residual offset <inline-formula> <tex-math notation="LaTeX">$< 4~\mu \text{T}$ </tex-math></inline-formula> at 3 V, and an InAlN/GaN devices operated at 2 V had a residual offset <inline-formula> <tex-math notation="LaTeX">$< 4~\mu \text{T}$ </tex-math></inline-formula>. Thus, for the first time, GaN 2DEG Hall-effect plates were shown to operate with high bias with low offsets and noise, which enables high fidelity sensing applications in extreme environments. [2020–0176]
Detection of Spinal Fracture Lesions Based on Improved Yolo-tiny

Spinal CT images are very important for the diagnosis of spinal diseases. However, due to the complication of spine CT images, and also artificial bias and low efficiency in clinical, which makes doctors to take many time in reading spine CT images, so it can not satisfy the clinical real time demands. In this paper, we prestent a method to detect spinal fracture lesions of (cervical fracture, cfracture), (thoracic fracture, tfracture), (lumbar fracture, lfracture) by proposed Yolo-tiny. We add three 1×1 convolution layers to the original Yolo-tiny network to make spinal lesions easier to detect. Our experimental results shows the mAP (mean Average Precision) of our proposed method is 86.63%, detection time is 0.02155 seconds per detection, IOU ((Intersection Over Union) is 87.3.
The Use of ICT to Promote Learning: A Case Study of a Primary School in Phnom Penh

The purpose of this study has been to determine the use of ICT to promote learning as a case study of a private primary school in Phnom Penh. The researcher adopted the Sangapac Online Learning (SOL) used to gather information regarding the first-grade students. The researcher used one group pre-test and post-test design of data collection in which 109 students were given the opportunity of participants as test-takers. Inference statistic was used to investigate the result of this modern way of leaning Khmer language in the first-grade students adopted by Sangapac Online Learning as pre-test and post-test. The results indicated the statistically significant difference between pre-test and post-test of the first-grade students. To conclude, the results of this study should be considered in the positive effectiveness on ICT to promote learning of the modern way.
Fixed-TimeBackstepping Control of Quadrotor Trajectory Tracking Based On Neural Network

This paper aims at the trajectory tracking of a quadrotor. A novel fixed-time backstepping control design scheme is proposed for the quadrotor based on adaptive neural control approach. The suggested adaptive controller ensures that the quadrotor well tracks the desired trajectory in finite time in spite of appearance of model uncertainties. Finally, simulation results are given to verify the effectiveness of the proposed control strategy.
On the Study of Digital Learning Interactive Method in Situated Learning

The digital learning has been an important subject for improvement and research in education, especially the development of the Internet and the advancement of computer multimedia tools. This study involves the design of teaching materials and how the role of the teacher acts in digital teaching videos. Thus, two teaching methods are concerned to capture the teaching videos, one is only to capture teaching screen (PPT) without teacher's body language, and the other is to capture teacher's presentation in front of an interactive whiteboard such that the teacher can reveal the situation of problem-solving and logical thinking. Contributions of this research are clearly to state "Teaching Material Favorability" and "Learning Motivation" which will really allow students to cause accompanied effect and reflection in their learning interest from situated impacts.
A Beamforming Scheme With Doppler Suppression for High-Mobility Wireless Communications

In this letter, we consider the high-mobility wireless communications between a high speed train (HST) and a base station (BS) and propose a beamforming scheme with Doppler suppression for the stationary node BS. The typical Rician channel model is assumed, which occupies most of the HST communication scenarios. Based on the fact that the channel time-variation induces interference to the standard time-invariant signal model, the beamforming is then designed to maximize the signal-to-interference-plus-noise ratio (SINR) for both uplink and downlink transmissions. Simulation results are provided to verify that the channel time-variation can be effectively suppressed by the stationary BS through the proposed beamforming scheme.
LiEBiD - A LIDAR based Early Blind Spot Detection and Warning System for Traditional Steering Mechanism

The proposed work LiEBiD - Lidar based Early Blind spot Detection system is designed to provide early warnings with regard to the proximity of other vehicles in “no zones” and blind spots Additionally, the designed product is an important module of the Advanced Driver Assistance System (ADAS) to provide timely corrective action to prevent imminent collision. And with the help of Triangulation Range System Resolution, it provides much accurate results. The LiEBiD system is highly effective in real-time proximity sensing as it classifies the obstacles for three different threshold limit zones for early identification and warning. This technique places the LiEBiD product an edge above its contemporaries. Further, the response time of the proposed system is under 500$\mu$ s which makes this 10x faster than the existing techniques which has response in the order of milli seconds.
Development of Ready-To-Serve Organic Tomato Powder Mocktail

Purpose: Tomato being a widely consumed fruit has the potential for meeting the increasing demand for quality fruit and vegetable juices in India and abroad. In this present scenario application of various vegetable juice powders is growing enormously. However use of organic tomatoes and its value added products are rarely seen. Objective: Hence to increase the demand and explore the possibility of developing new products the present study was carried out, to develop a product with different fruit blends by using organic tomato powder as a base material. Method: Tomato slices were dried at 50 C for 14-16 hours in a tray drier and later milled into powder with the help of pulverizer. Results: Study showed better results for both powder and RTS juice of organic samples. Sensory evaluation showed good results with respect to all quality attributes like colour, aroma, consistency, flavor, taste, sweetness, mouthfeel and overall acceptability for all selected juice combinations however S4 (tomato powder + papaya fruit pulp) ranked first with an overall acceptability score of 8.0. Further, the highest scored sample (S4) was analyzed for bio-chemical properties, on confirming colour (L* 20.26, a* 14.57, b* 27.90), TSS (12.5°Brix), pH (4.5), aw (0.94), viscosity (5.43 cP), acidity (0.19%), vitamin C (10.00 mg/100 ml) and lycopene (0.50 mg/100 ml). Statistical analysis showed a significant differences among the samples at (P<0.05). Conclusion: Tomato powder acts as a potential substitute in the prepared RTS juice which is a healthy drink to relish.
Application of Stochastic Adaptation in Block Method for Estimating Image Sequence Deformation Field

The paper proposes a block method for estimating the deformation field for image sequences using a stochastic adaptation procedure. As a target function, the paper considers mean square inter-frame difference and interframe correlation coefficient. The developed algorithm has a high noise resistance and allows one to reduce the influence of global inter-frame geometric changes. Also, by adjusting the size of the blocks, it makes it possible to remove or highlight moving objects of small size (rain, snow, falling leaves, etc.).
Using ADAPT-ITT to Modify a Telephone-Based HIV Prevention Intervention for SMS Delivery: Formative Study

Background African American adolescent females are disproportionately affected by sexually transmitted infections (STIs) and HIV. Given the elevated risk of STIs and HIV in African American women, there is an urgent need to identify innovative strategies to enhance the adoption and maintenance of STI and HIV preventive behaviors. Texting is a promising technology for creating preventive maintenance interventions (PMIs) that extend the efficacy of the original intervention. However, little guidance in public health literature is available for developing this type of application. Objective This paper describes a formative pilot study that incorporates user experience methods to design and test PMI texts for Afiya, an original evidence-based intervention (EBI) specifically designed for African American adolescent females. This study aims to describe the adaptation process of health educator–led phone calling to text-based communication. Methods The formative process followed the assessment, decision, adaptation, production, topical experts-integration, training, testing (ADAPT-ITT) framework for adapting EBIs and using them in a new setting, for a new target population or a modified intervention strategy. This study presents the details of how the phases of the ADAPT-ITT framework were applied to the design of the adaptation. An advisory board was constituted from the target population, consisting of 6 African American women aged 18-24 years, participating in formative activities for 12 weeks, and involving components of the PMI design. As Afiya included a telephone-based PMI, developers of the original Afiya phone scripts crafted the initial design of the SMS-based texts and texting protocol. The advisory board participated in the 1-day Afiya workshop, followed by 4 weeks of texting PMI messages and a midcourse focus group, followed by 4 more weeks of texting PMI messages, ultimately ending with a final focus group. At the advisory board’s request, this phase included an optional, additional week of text-based PMI messages. Results The methods provided a rich source of data and insights into the fundamental issues involved when constructing SMS-based PMI for this target population and for this EBI. Prior contact and context are essential as the health educator was identified as a key persona in the process and the messages were situated in the original (workshop) context. Narrative adaptations for personas emerged from advisory board discussions. Suggestions on how to expand the PMI to current, specific social contexts indicated that the use of narrative analysis is warranted. Conclusions The use of existing EBIs incorporating telephone-based PMI scripts facilitated the initial design of the texts, with a subsequent narrative analysis of the advisory board data providing additional adjustments given the actual context. Additional examination of the advisory board feedback revealed that personas would offer insight into and opportunities for a persona-specific modification of texting narratives.
Solder Volume Effect on Electromigration Failure Mechanism of Cu/Ni/Sn-Ag Microbumps

Effects of solder volume on the electromigration (EM) failure mechanism of Cu/Ni/Sn-2.5Ag microbumps were systematically investigated at 150 °C with a current density of $1.5\times 10 ^{5}$ A/cm2. While the electrical resistances of Cu/Ni/Sn-Ag microbump with large solder volume increased quickly, those with small solder volume increased slowly, which depends on the difference in solder volume effect on the intermetallic compound formation mechanisms. For a structure with large solder volume, the Ni barrier layer was extensively consumed due to substantial reaction between Ni barrier and large solder volume. For a structure with small solder volume, the initial Ni barrier structure was preserved due to the limited volume of solder reacting with Ni barrier, which mainly contributes to better EM reliability of Cu/Ni/Sn-Ag microbump.
Implementation of an energy harvesting powered orientation estimation sensor

The Internet of Things and Wireless Sensor Nodes are spreading into more and more homes and offices. Current wireless sensor systems rely on the use of batteries. Since batteries are made from scarce resources and have to be exchanged regularly their use is not optimal. To avoid these limitations energy harvesting is a possible alternative. Currently most energy harvesting based sensor nodes use simple low energy sensors. To expand the possibility of energy harvesting this paper presents a sensor node using a geomagnetic sensor, which normally is used in battery or mains powered devices.
Enabl: Visual Aid for Dyslexic based on Natural language procesing

Text to 3D scene generation requires an understanding of natural language as well as a rendering of 3D objects. The text is parsed and knowledge is extracted from it. This knowledge includes the identification of objects and their spatial relationship. Properties of objects are also extracted from the sentence. Spatial knowledge helps in the placement of the 3D objects in the scene space. 3D objects dataset is used to render the identified objects in the scene. The graphical view generated can be used by dyslexic children who have difficulty in reading and interpreting the text. Dyslexia is a learning disability but it is not indicative of their intellect. They also have extremely good visualization ability which could help them in apprehending their reading. This paper represents a text to 3D scene generation system which requires minimum physical interaction and might help dyslexic students to comprehend text.
Fault recognition of electric servo steering gear based on long and short-term memory neural network

In order to recognize different kinds of faults of helicopters’ three types of electric servos, this paper proposes a fault state recognition algorithm of electric steering gears based on long short-term memory(LSTM) neural network. Firstly, the original three types of electric servo data are preprocessed, the data set is transformed into a supervised learning problem, and the input variables are normalized. Secondly, different optimization algorithms are introduced to the LSTM neural network model to optimize the parameters. Finally, the number of different hidden layer neural network and the time step are set for comparison experiments, and the optimal neural network configuration is selected from them. The test results show that this model can effectively identify single and multiple faults. The training results show that the model can effectively identify single and multiple faults, and the recognition rate of pitch and left roll is high and has good practicability.