Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast 3D Beamforming Technique for Millimeter-Wave Cellular Systems With Uniform Planar Arrays

The beam search protocol in cellular systems requires a significant amount of search time and network resources in order to select a serving base station with the optimal beam pair. In 3D beamforming, the processing time increases significantly because the azimuth and elevation angles need to be considered during beam search. In this paper, we propose a fast 3D beamforming technique for millimeter wave (mmWave) cellular systems with a uniform planar array (UPA). In the proposed technique, the beam search time is reduced significantly by decomposing a UPA into a set of horizontal/vertical uniform linear arrays (ULAs), from which the optimal beam direction in azimuth/elevation angle is obtained. Two types of signals, Zadoff–Chu sequence and linear frequency modulated waveform are used for designing the beam search preamble (BSP), which allows a mobile user to distinguish beams in multi-cell multi-beam environments. The strengths and weaknesses of the two proposed BSPs are analyzed after performing simulation using a simple mmWave cellular system model with UPA. Furthermore, it is demonstrated that the proposed technique significantly reduces the beam search time, i.e., number of beam scans, as compared with the conventional technique.
Real-Time Visual-Inertial SLAM with Point-Line Feature using Improved EDLines Algorithm

Many traditional visual-inertial SLAM systems rely on point feature method in front-end odometer module. However, point features may perform bad under blurred images or environments with weak textures. This issue can be solved via introducing line features, due to existing structed features such as line segments usually in artificial structured environments. But many published visual-inertial SLAM systems based on point-line features have poor performance in real-time. This paper proposes a point-line feature based visual-inertial SLAM system by developing an improved EDLines algorithm. We improved the EDLines algorithm by calculating image gradient threshold on different images to extract more efficient line segments in less time. The proposed system is evaluated on public datasets EuRoC, and is compared with the state-of-art SLAM systems including VINS-Mono and PL-VIO. Experiments show that the proposed system can improve the accuracy while ensuring real-time performance.
Design and Adoption of Bring Your Own Device (BYOD) in Smart Classroom

Ubiquitous computing provides the powerful support to information exchange. Mobile devices have been the mainstream Internet access tools. They are portable and used as both the private purposes and business purposes. Personal mobile devices have been used in workplaces, which is called Bring Your Own Devices (BYOD). BYOD is also used in education. In this paper, we discussed on the new teaching / learning mode based on BYOD and provided a system design to support using BYOD in primary school. We also shared our experiences in the construction and showed the effect.
Comprehensive Survey of Event Detection Techniques in Social Media Streams

In the current years, the reception of net based more life stages are increased, for instance, Twitter, Facebook and their utilization as a component of the regular day to day existence of billions of people round the world. Given the habit of individuals to use these platforms to share thoughts, daily activities and experiences it's not stunning that the quantity of user generated content has reached unprecedented levels, with a considerable a part of that content being associated with real-world events.Event detection on social networking sites is crucial and important task in order to handle the emerging situations and close monitoring of the events. One of the major concern is to tackle the crisis like situations arising through this events. One of the way to control such activities is to detect the hot events on social networking sites as and when arises. Various detection models and techniques are available to detect events. This research focuses on surveying the various such detection models and techniques like Graph based algorithm, Multilayered inverted lists, CBOW model and Skip gram model, Incremental temporal topic model, Hypertext-Induced Topic Search (HITS) based Topic-Decision method (TD-HITS) algorithms, Multi-assignment graph partitioning algorithm. and comparing the performance of these models and algorithms in terms of their average accuracy. It is found that Hypertext-Induced Topic Search (HITS) based Topic-Decision method (TD-HITS) method gives the highest average accuracy and hence performs the best.This paper cover a detailed study of methods for event detection from Social Media that occurs over area and time. This paper highlight numerous event detection techniques and their limitations.
Architecture of a Cloud-based Fault-Tolerant Control Platform for improving the QoS of Social Multimedia Applications on SD-WAN

Social media application are becoming multimedia centric with live and stored video, audio, augmented reality, haptic, etc. emerging as the main categories of traffic. Their QoS requirements are more stringent than their legacy counterparts. At the carrier level, Software Defined – Wide Area Network (SD-WAN) is one of the promising technologies for transporting these multimedia traffic. A SD-WAN will typically have a mesh of centralized controllers managing the networking infrastructure. Reliable operations of these controllers are a key requirement for the successful operation of the WAN. Controller failure will prevent the forwarding switches from communicating with the controller. This will prevent the switches from forwarding any new traffic, as well as flow entries from existing traffic will also time out after a period bringing the network to a standstill. Rebooting a controller or starting a new one will introduce delays degrading the QoS. This research presents an architecture for handling controller failure via transparent migration of the controller load in a semi-meshed controller environment. The architecture includes a real time cloud-based centralized storage of the flow states north of the controllers and a virtualized connection management unit at the south. The results demonstrate that the proposed model can transparently handle controller failure without affecting the QoS.
Uplink NOMA in Body Area Networks With Simple Node Pairing Strategies

In body area networks (BANs), a node placed near the hub has a significant signal strength advantage. This issue, known as near-far problem, indicates that a near node may serve as a relay for a far node. Currently, the established orthogonal multiple access (OMA) requires the allocation of a specific resource block to a single node. In contrast, the emerging non-orthogonal multiple access (NOMA) allows simultaneous transmissions and uses successive interference cancellation (SIC) to recover the signals. For the first time in the literature, we introduce NOMA in BANs, to allow simultaneous transmissions from two nodes at a time, with distinguishable power levels. The crucial part of this technique is the dynamic pairing of the nodes by the hub. First, we review the fundamentals of uplink NOMA and we propose an access protocol in compliance with IEEE 802.15. 6-2012, which combines random OMA with scheduled NOMA. Next, we propose three node pairing strategies, namely a random, a correlative and a conditional one, to meet the requirements of several applications. These strategies are evaluated with packet level simulations in OMNeT++. Our results show that the proposed scheme outperforms the basic OMA scheme at high packet rates and provides a feasible direction for novel relay-based applications.
Curriculum, Teaching and Learning, and Assessments for Introductory Programming Course

Learning to program involves acquisition of various skills including problem solving, fundamental design techniques as well as critical thinking. Generally, most of the novice programmers struggle to develop all these important skill. The research community has addressed the problem in many different ways while involving improvisations in curriculum, pedagogical methods, cognitive aspects, supporting tools, and in designing assessments. This research aims to analyze and synthesize the existing literature in the aforementioned areas. Research articles pertaining to the area of Introductory Programming Courses (IPC) have been found using appropriate search queries, while nearly 60 research articles, published in last ten years, have been carefully selected by employing a systematic filtering process. The scope of this work only covers the research conducted for IPC in higher education. Main findings of this study show that “solution proposal” and “evaluation research” have been reported as two main research types adopted by these studies. Moreover, pedagogy, language choice and students’ performance analysis are the most frequently addressed aspects of IPC; whereas, curriculum contents, assessment design, and teaching/learning through tools have appeared as less addressed aspects of IPC. Furthermore, a taxonomy of IPC has been presented based on the studied literature. Lastly, general considerations and future research directions have been presented for the practitioners and researchers in this area.
RFID Characteristics and Its role in 5G Communication

Radio Frequency (RF) waves are the part of electromagnetic radiation and best known for their use in communication domain such as mobile phones, television etc. As technology advanced and created a device called RFID (Radio Frequency Identification) which uses tags to identify and track the targeted object. Tracking allows better coordination and control in the production cycle. Keeping the track of an object is challenging and can successfully be handled by using RFID. RFID which works according to IoT based methodology is economical compared to other tracking devices. At present, RFID is visualized as the worthy replacement for barcodes. RFID chips find its use in large organization such as defense sector to small businesses. Recent years there has been an internet revolution, industries and consumers demand for high and constant speed, having less lag time that allow them to compile, compute and share the data in less time. 5G is welcomed as a new intelligence than a cellular technology which is a total shift from the older LTE. RFID will play a key role in taking 5G to the expected level in the areas of IoT, blockchain etc. This paper have summarized the evolution of RFID followed by detailed description of RFID and its characteristics. Then, a few comparisons on different parameters of RFID technologies are also highlighted. Finally, the role of RFID in 5G communication is described.
Three Approaches to the Design of a Golden Online Course on Data Structure

The problem of Attention Deficit Disorder is more noticeable in online teaching than in face-to-face teaching. Facing the new requests of constructing Golden Course and based on the analysis of the relationship between Golden Course and Attention Deficit Disorder, the paper takes the national-level MOOC, Data structure, as an example and explores three approaches to solve the problem of Attention Deficit Disorder from the perspective of teaching content organization and implementation. These three approaches are also the core strategies for Golden Course design. The main content is as follows. First, establish the levels of learning objectives under the guidance of BLOOM model, and optimize the design of learning objectives with Mager method, so that students can obtain specific information, find correct learning direction, and avoid lack of attention. Second, use concept map to select and divide learning content, highlighting the importance and relevance of learning content, and ensure that the content is explained within about 10 minutes. Although the time is fragmented, the content is not fragmented. Third, the BOPPPS model is used to organize the process of course implementation and introduce the learning content under the guidance of questions, so as to ensure that the internal logic of the course is compact and effective, and students' interest in learning can be enhanced. Practice shows that the curriculum design strategy which combines the three approaches mentioned above can effectively solve the problem of Attention Deficit Disorder. The course, Data Structure, constructed with three mentioned approaches, was selected as one of the national-level MOOCs in January 2019, which has been running for 4 years on the net for 7 semesters, with a course rating score of 4.8 points out of 5 points, and taken by more than 70,000 learners.
An Improved Feature Set for Hyperspectral Image Classification: Harmonic Analysis Optimized by Multiscale Guided Filter

Effective features derived from an original hyperspectral image (HSI) are quite important to improve the classification performance. An improved feature set, namely HGFM, is constructed by integrating harmonic analysis (HA) optimized by a multiscale guided filter (GF) with morphological operation for HSI classification. To establish HGFM, HA is first adopted to convert the HSI from spectral space to the frequency domain represented by amplitude, phase, and residual. With the first component of minimum noise fraction obtained from the original HSI as the guidance image, the harmonic components are then processed by the multiscale GF. Finally, the obtained results are then operated via morphological opening by reconstruction and closing by reconstruction to generate an improved feature set for classification. The HGFM features are input to an ensemble learning (EL) based on classification framework, in which EL plays an auxiliary role to enhance the classification stability and reliability. Three commonly used HSIs are used for experiments, and different feature sets are evaluated by comparing EL and rotation forest, support vector machine optimized by particle swarm optimization, random forest, and others. Compared with benchmark feature sets, the proposed HGFM feature set can better depict the details of objects easily, and the experimental results confirm the effectiveness in terms of classification accuracy and generalization ability.
Poster: Distributed and Privacy Preserving Routing of Connected Vehicles to Minimize Congestion

The existing commercial and research based approaches of calculating routes for vehicles suffer from one or more of the following two limitations: they are not privacy preserving and they require expensive infrastructure such as road side units (RSUs). To address these limitations, we propose a distributed and privacy preserving routing protocol, namely DPR, which the connected vehicles collaboratively execute to calculate fast routes to their destinations while preserving vehicle privacy. Our results show that DPR reduces the average travel time of vehicles by up to 42%.
Moving a step forward in the quest for Deterministic Networks (DetNet)

Recent years witnessed a fast-growing demand, in the context of industrial use-cases, for the so-called Deterministic Networks (DetNet). IEEE 802.1 TSN architecture provides linklayer services and IETF DetNet provides network-layer services for deterministic and reliable forwarding. In such a context, in the first part of this paper, we tackle the problem of misbehaving flows and propose a novel queuing and scheduling mechanism, based on Push-In-First-Out (PIFO) queues. Differently from the original DetNet/TSN specifications, our solution is able to guarantee performance of priority flows in spite of misbehaving flows. In the second part of this paper, we present our simulator DeNS:DetNet Simulator, based on OMNET++ and NeSTiNG, providing building blocks for link-layer TSN and network-layer DetNet. Existing simulators have important limitations that do not allow simulating the full DetNeyTSN protocol stack. We overcome these limitations, making easy DetNet/TSN evaluations possible. Our simulations clearly show that our solution is able to satisfy constraints of deterministic networks, namely, guarantee zero packet loss and low latency, while at the same time allowing best-effort flows to co-exist. Furthermore, we show how our newly-proposed queuing and scheduling solution successfully limits the impact of misbehaving flows.
Spin-Transfer Torque Magnetic Tunnel Junction for Single-Event Effects Mitigation in IC Design

For embedded systems in harsh environments, a radiation robust circuit design is still an open challenge. As complementary–metal–oxide semiconductor (CMOS) processes get denser and smaller, their immunity toward particle strikes decreases drastically. Due to its good radiation effects tolerance and its inherent nonvolatility, spin-transfer torque magnetic tunnel junction (STT-MTJ) is considered a promising candidate for high-reliability electronics. Nevertheless, when integrated in a CMOS circuit, these magnetic devices could still be affected by upsets. To decrease the probability of this occurrence, a radiation robust setup is used to calibrate a physics-based 20-nm MTJ compact model, integrated in a 28-nm Fully Depleted Silicon On Insulator (FD-SOI) technology. Thus, a radiation hardening by design (RHBD) solution is presented, where a nonvolatile sequential block enables one to mitigate the single-event effects (SEEs).
Peripheral Analgesic and Anti-diarrheal Activities of Leaf of Syzygium cumini (L.) Skeel

Syzygium cumini has been used in folk medicine to treat many diseases. To establish the potential medicinal value of leaves of S. cumini, the current study was carried out to assess the peripheral analgesic and anti-diarrheal activities in mice model. The crude methanol extract and its petroleum ether and chloroform soluble fraction were administered to the experimental mice at a dose of 200- and 400- mg/kg b.w. (denoted as CME1, CME2, PESF1, PESF2, CLSF1 and CLSF2 respectively) using acetic acid induced writhing method and castrol oil induced anti-diarrheal assay protocol. The extract and its Kupchan fractions exhibited significant (p < 0.001) reduction of writhing response in a dose dependent manner. In the acetic acid-induced writhing test, the activity decreased in the order diclofenac (75.33%) > PESF2 (70.33%) > CME2 (67.00%) > PESF1 (64.00%) > CLSF2 (61.33%) > CME1 (56.67%) >CLSF1 (48.67%). All the fractions significantly (p < 0.001) attenuated anti-diarrheal effect in a dose dependent manner with the highest activity observed by CME2 (47.73%) as compared to standard lopeiramide (54.55%). The results of our study, being reported for the first time, provide reasonable indication that the methanol extract of S. cumini leaf and its different fractions possess peripheral analgesic and antidiarrheal activities. Bangladesh Pharmaceutical Journal 22(1): 13-17, 2019
Speed Limit Camera Monitoring/Tracking System Using SaaS Cloud Computing Module and GPS

The number of accidents is rising daily along with the expanding driver and passenger safety concerns. The countries that have successfully reduced road traffic risk have embraced a ’systems approach’ to road safety. Speed is at the core of the road safety problem. There is a strong relationship between speed and both the number of crashes and the severity of the consequences of a crash. This paper suggests a solution to increase safety with a speed limit camera monitoring/tracking system using Global Positioning System (GPS) and cloud computing with the Software-as-a-Service (SaaS) module which provides useful information about roads. Critical information like driver position is collected by the GPS build-in the device for Android or iOS systems, then this information is sent to a cloud server where it is kept over the Internet. This system provides precise location services of the driver, driving speed, road allowed speed and speed limit camera position all to provide the driver with a street guide to improve speed limit enforcement aiding in road safety and preventing more accidents. The proposed system was tested by implementing it by many drivers at Duhok and Zakho provinces using the System Usability Scale (SUS) method with the subscription of 30 potential system users. Results of the SUS showed a relatively high rate of user satisfaction at around 75.58%.
Automatically Configuring the IP Addresses for Mobile Network in Collaborative Network

Collaborative network deploys devices with multiple interface on moving objects to combine the operator's networks to transmit user data in parallel which can achieve bandwidth aggregation and provide stable network access services for users. Before the collaborative network can work normally, it is necessary to configure IP addresses for each interface of network devices in different geographical locations. Existing configuration protocols can only realize the automatic configuration of the IP address of single interface devices in the same network segment. If the network devices are configured manually, the complex and error-prone manual configuration hinders the deployment of the collaborative network. In this paper, we propose an automatic IP address configuration mechanism that can complete the IP address request across network segments and the automatic configuration of the IP addresses of multiple interface devices in the network. The simulation results show that the proposed mechanism can complete the automatic configuration of IP addresses in the mobile network in a short period of time and is well adapted to complex mobile environment.
Location and group size influence decisions in simulated intergroup encounters in banded mongooses

In social species that cooperatively defend territories the decision to retreat or attack in contests between groups is likely to depend on ecological and social factors. Previous studies have emphasized the importance of the encounter location or the size of competing groups on the outcome. In addition, the identity of the intruder, whether familiar or stranger, may also play a role. To test whether the same factors affect the resident group's decisions already at the beginning of contests, we simulated intergroup encounters in banded mongooses (Mungos mungo). When spotting rival groups banded mongooses emit "screeching calls" which lead group members to bunch up. With playbacks of these calls, we tested how the groups' response was affected by the following factors: 1) the location of the playback in relation to their territory (exclusive use vs. overlap); 2) the number of resident individuals; and 3) the origin of calls (neighbor vs. stranger) used. Subjects were more likely to approach the loudspeakers and arrive within 1 m of the speakers in the exclusive use zone than in the overlap zone. Moreover, larger groups tended to be more likely to move toward the loudspeakers and were also more likely to arrive there. The origin of calls used in the playbacks did not affect the groups' responses. These findings exemplify the importance of the combined effect of location and group size on group decisions during impending intergroup contest. Copyright 2011, Oxford University Press.