Miracle-dz/UniFAR-FTUs huggingface dataset:
Amazon, Google and Microsoft Solutions for IoT: Architectures and a Performance Comparison

Internet of Things (IoT) aims to connect the real world made up of devices, sensors and actuators to the virtual world of Internet in order to interconnect devices with each other generating information from the gathered data. Devices, in general, have limited computational power and limited storage capacity. Cloud Computing (CC) has virtually unlimited capacity in terms of storage and computing power, and is based on sharing resources. Therefore, the integration between IoT and CC seems to be one of the most promising solutions. In fact, many of the biggest companies that offer Cloud Services are focusing on the IoT world to offer services also in this direction to their users. In this paper we compare the three main Cloud Platforms (Amazon Web Services, Google Cloud Platform and Microsoft Azure) regarding to the services made available for the IoT. After describing the typical architecture of an IoT application, we map the Cloud-IoT Platforms services with this architecture analyzing the key points for each platform. At the same time, in order to conduct a comparative analysis of performance, we focus on a service made available by all platforms (MQTT middleware) building the reference scenarios and the metrics to be taken into account. Finally, we provide an overview of platform costs based on different loads. The aim is not to declare a winner, but to provide a useful tool to developers to make an informed choice of a platform depending on the use case.
Au nanoparticle controlled luminescence emission of single NaYF4:Eu3+ particle

Highly dispersed and uniform α-NaYF4 micron flowers with about 500nm size was synthesized by a simple wet-chemical at a low temperature, then NaYF4:Eu3+@Au hybrid structures with various amount Au nanoparticles (Au NPs) are prepared and single NaYF4:Eu3+@Au hybrid particle is taken to investigate the influence of noble metal nanoparticle on the luminescence emission and present corresponding mechanism. It is found that luminescence emissions of NaYF4:Eu3+ was quenched by introducing Au nanoparticles, and with increase of Au nanoparticles, the fluorescence quenching was more and more serous while emission intensity ratio of electric dipole to magnetic dipole transition of Eu3+ gradually become larger.
Computation Offloading Management in Vehicular Edge Network under Imperfect CSI

Recently, image recognition and video processing play important roles in the rapidly expanding field of autonomous driving. However, the computing capability of vehicles cannot meet the latency requirement of these tasks. Mobile Edge Computing (MEC) is envisioned as an effective paradigm to augment the computing capability of vehicles for dealing with computationally intensive tasks. And the imperfect channel state information (CSI) due to the high mobility of vehicular environment need to be properly accounted for when designing offloading strategy for vehicular network. In this paper, we formulate a problem to minimize the cost of computation and communication under imperfect CSI considering the processing delay, return delay, priority of tasks and energy consumption. The problem can be solved as a modified graph matching problem and we optimize the offload strategy. A computation offloading management (COM) algorithm is proposed to solve this optimization problem. We focus on minimizing the overall overhead while guaranteeing the reliability of each vehicle-to-vehicle (V2V) communication link. Numerical results demonstrate that our proposed algorithm can reduce total overhead and guarantee low outage probability.
Superregeneration Revisited: From Principles to Current Applications

Wireless communications play a central role in our modern connected lives; at the same time, they constitute a very broad and deep area of research. The elements that make wireless communications possible are a transmitter, which sends information through electromagnetic waves; a medium that is able to transport these waves; and, finally, a receiver, which extracts the information from the-usually very small-amount of energy it is able to collect from the medium.
on the Use of Class Activation Map for Land Cover Mapping

In a supervised classification of a remote sensing image, a ground survey is needed to collect sufficient training data to train a classifier. The ground survey is expensive and time consuming. Thus, the idea of the class activation map (CAM) is proposed for land cover mapping in this paper. Here, instead of training with ground data where the underlying class label of each training pixels must be identified, our goal is to classify every pixel in an image with a training set, where a training sample is the association between an image and their class composition. The identification of class composition with an image is an easier task to perform, since human perception can accurately detect the composition of objects. The CAM is a collection of “heatmap” images associated with different combinations of land cover classes, where the high value indicates a high probability that a pixel belongs to that class. Next, we label a pixel to the class where the corresponding CAM is maximum.
The limits of infinity

Two additional topics of interest with limits are limits as x → ±∞ and limits where f(x) → ±∞. Before we can properly discuss the notion of infinite limits, we will need to begin with a discussion on the concept of infinity. We begin by emphasizing that ∞ and −∞ are not a numbers; they are symbols that we use for convenience to represent very specific concepts. Since ∞ and −∞ are not numbers, performing arithmetic operations with them is nonsensical. The following argument is an attempt to illustrate this:
A Distributed Surveillance Camera Network Architecture for Public Security Applications in Metropolitan Area

Traditional star-topology based surveillance camera networks are being replaced all over the world with IP networks containing high resolution digital cameras. This new structure can support thousands of cameras and offers higher image quality and faster image capture rates which implies huge amounts of visual data to compress, transmit, uncompress, analyze, store, index, search, summarize and archive. In this environment, efficient handling of visual data is not a trivial task due to its enormous volume and thus, there is a need for overarching system architecture. In this paper, we present a highly scalable distributed system architecture specifically targeted at metropolitan area surveillance applications for public security. The proposed architecture has the potential of supporting a large-scale surveillance network with network-wide tracking and targethandover capabilities and includes provisions for automated annotation of video content and content-based video search.
First-Principles Modeling for DNA Bases via Z-shaped Graphene Nanoribbon with a Nanogap

DNA sequencing is a significant technique to detect genetic illnesses and various diseases. Quick, accurate, and low cost DNA sequencing approach would revolutionize medicine. In this paper, a two-terminal z-shaped sensor with a nanogap is designed and studied to detect the DNA sequence. The z-shaped sensor is made of two metallic zigzag graphene nanoribbon (ZGNR), a semiconducting channel made of armchair graphene nanoribbon (AGNR), and a nanogap in the middle of the channel whose edge carbon atoms are passivated by either hydrogen or nitrogen. Placing a DNA base into the nanogap impacts the charge density of the sensor leading to unique signature for each of the four DNA bases. The z-shaped sensor performance was studied by non-equilibrium Green’s function combined with density functional theory (NEGF+DFT). The transverse current and the transmission spectrum of the DNA bases within the nanogap are investigated with variation in the base orientation. The proposed sensor is highly useful for real application of quick, low-cost, and accurate DNA detection.
Urinary tract infections in the menopausal period: optimal management

Zakazenia ukladu moczowego są jednymi z najczestszych chorob infekcyjnych u kobiet. Szczegolnie czesto obserwuje sie je w dwoch okresach zycia: u mlodych, aktywnych seksualnie kobiet oraz w okresie pomenopauzalnym. Istnieje wiele zmieniających sie wraz z wiekiem przyczyn powodujących niepowiklane zapalenie pecherza moczowego. W okresie menopauzy takimi dobrze znanymi czynnikami są: zaleganie moczu w pecherzu po mikcji, zmniejszony strumien moczu, nietrzymanie moczu, zaburzenia funkcji dna miednicy wraz z zaburzeniami statyki narządu rodnego. W tym okresie zycia kobiety obserwuje sie nagle zmniejszenie stezenia estrogenow, co moze stanowic wskazowke dotyczącą kierunku leczenia. Czynniki behawioralne rowniez powinny byc brane pod uwage jako przyczyny zachorowania. Artykul stanowi przegląd biezącego piśmiennictwa dotyczącego infekcji ukladu moczowego u kobiet po menopauzie. Przegląd piśmiennictwa przedmiotu z ostatnich lat sklania do sformulowania nastepujących wnioskow: • Escherichia coli stanowi glowny patogen odpowiedzialny za infekcje ukladu moczowego u kobiet niezaleznie od ich statusu hormonalnego. • Do leczenia pierwszego rzutu niepowiklanych infekcji ukladu moczowego najcześciej rekomenduje sie fosfomycyne, nitrofurantoine, cyprofloksacyne i amoksycyline z kwasem klawulanowym. Krotkotrwala terapia jest lepiej tolerowana przez chore niz leczenie dlugoterminowe, a w wielu przypadkach jest porownywalnie skuteczna. • Systemowa terapia hormonalna nie stanowi skutecznej profilaktyki zakazen ukladu moczowego. • Bezobjawowa bakteriuria u kobiet w okresie menopauzy nie wymaga leczenia. • Hamowanie przylegania bakterii do komorek nablonka ukladu moczowego oraz zapobieganie tworzenia biofilmu stanowią kluczowe mechanizmy dzialania lekow antyuroseptycznych – szczegolnie w kontekście ryzyka nawrotow infekcji ukladu moczowego. Slowa kluczowe: menopauza, infekcje ukladu moczowego, leczenie, zapobieganie.
Research on Model Predictive Control Method for Multi-paralleled DC-DC Converters

With the continuous increase of battery capacity in the power battery charging and discharging system(PBCDS), the charging and discharging equipment of power battery also needs to output large power or energy, so the multi-DC-DC parallel-connected structure on the battery side becomes the first choice. In addition, considering the traditional PI control method have a complex parameter adjustment process and the complexity of parameter adjustment increases sharply with the parallel-connected of multi-DC-DC, but also it cannot meet the special requirements of high dynamic response speed and non-overshoot in the power battery charging and discharging process(PBCDP). Therefore, this paper innovatively proposed a model predictive control method for the parallel-connected system with n DC-DC converters, which does not require complicated parameter tuning, but also achieves the special requirements of high dynamic response speed and non-overshoot in the PBCDP. The method has strong universality and high flexibility, and can be applied to power battery charge and discharge conditions with any level of power. Finally, the simulation is conducted to validate the feasibility and correctness of the proposed MPC control method.
Predictive Current Trajectory Control for PMSM at Voltage Limit

This paper presents a fast predictive current trajectory strategy for permanent magnet synchronous motors (PMSMs) at voltage limit. The current hexagon obtained from the voltage hexagon of the inverter represents the region that the currents can reach in the next switching periond. The nearest avaliable current point to the reference is solved by geometrical method on the current plane. The output of the proposed algorithm is divided into four cases according to the position of the current points. The algorithm combines FCS-MPC and DPCC, has the merits of both method and also the fast dynamic at voltage limits. In order to increase the robustness against the parameter variations, moving horizon estimator is utilized. The rotor flux is eliminated in the algorithm and the voltage errors caused by resistance and inductance mismatches are compensated by the estimator. Several experiments are performed with DPCC, FCS-MPC and the predictive current trajectory control method. These comparisons validate the effectiveness of the proposed method.
IIRank: A Novel Algorithm for Identifying Influencers in Micro-Blog Social Networks

In this paper, we analyze the influence of microblogger and put forward new concepts of sources, such as the positive micro-blog source, the negative micro-blog source, and the neutral source in micro-blog field based on the concepts of sources in electromagnetic field theory. Then, we propose a novel Individual Influence Ranking algorithm called IIRank. IIRank first calculates the micro-blog flux by the way of calculating the magnetic flux to assess users' behaviors. It then calculates the micro-blog flux density with the micro-blog flux to rank the micro-blogger's influence. We have implemented the algorithm to handle the real-world Sina Weibo data. Experimental results show that the proposed method significantly improves the assessment preciseness over the popular and famous PageRank algorithm.
An Efficient MQ-Based Signature in the QROM

At PKC 2018, Chen et al. proposed SOFIA, the first MQ-based digital signature scheme secure in the quantum random oracle model (QROM). SOFIA is constructed by applying an extended version of the Unruh transform (EUROCRYPT 2015) to the MQ-based 5-pass identification scheme (IDS) proposed by Sakumoto et al. (CRYPTO 2011). In this paper, we propose an MQ-based 3-pass IDS with impersonation probability of 1/2 and apply the original version of the Unruh transform to it to obtain a more efficient MQ-based digital signature scheme secure in the QROM. The signature size with our digital signature scheme decreases by about 30% compared with SOFIA.
Trajectory Planning and Tracking for Autonomous Vehicle Considering Human Driver Personality

The rapid development of autonomous driving technology has made it possible for autonomous vehicles to enter a wide range of people's daily lives. On the basis of realizing automatic driving, it is necessary to improve the comfort of autonomous driving in the future to meet the requirement of different people. In this paper, we presented trajectory planning and tracking control for autonomous vehicle. Then, based on the trajectory characteristics of the human driver's actual driving, the driver's personalized trajectory is planned. The simulation shows that the personalized autonomy can be achieved.
Review on fiber optic sensing technologies applicable for hypersonic wind tunnel experiments

Hypersonic wind tunnel experiment technologies are involved to many subjects such as aerodynamic forces, aerothermodynamics, thermal protection of aircraft structures, heat-fluid-solid coupling, hypersonic boundary layer, airbreathing propulsion system and light-weighted and high-strength material. In comparison with traditional electromechanical or electronic sensors, the fiber optic sensors have relatively high potential to work in hypersonic wind tunnel. This article has classified and summarized the research status and the representative achievement on the fiber optic sensing technologies, giving special attention to the summary of research status on the popular Fabry-Perot interferometric, fiber Bragg gratings and (quasi) distributed fiber optic sensors working in hypersonic wind tunnel environment, and discussed the current problems in special optical fiber sensing technologies.
An Electronic Equipment for Automatic Detection of Mycobacteria in MGIT Cultures Based on Digital Image Processing

In this work we propose an automated electronic equipment oriented to the detection of mycobacteria by means of the analysis of fluorescence in MGIT tube cultures using digital image processing. The equipment aims to improve detection efficiency, since this procedure is mostly performed by visual inspection and has low reliability due to subjectivity. Part of the proposed system acts as an incubator for the growth of mycobacteria, which will maintain a temperature of 37°C±1°C. It also has a mobile camera for the acquisition of images of each tube in the enclosure, as well as an algorithm implemented in a single-board computer. The algorithm detects if a tube emits fluorescence, which is an indicator of the presence of mycobacteria in the broth. The steps of the algorithm involve transforming the RGB images to the HSV color model, filtering and classification by K-Nearest Neighbor. Equipment validation was made from a set of samples processed by a medically certified and approved professional electronic equipment. The results were compared with those obtained by the BD Bactec 960 MGIT equipment achieving a Cohen Kappa coefficient of 0.9355 in the evaluation of 40 samples selected by the specialist.
DaPanda: Detecting Aggressive Push Notifications in Android Apps

Mobile push notifications have been widely used in mobile platforms to deliver all sorts of information to app users. Although it offers great convenience for both app developers and mobile users, this feature was frequently reported to serve malicious and aggressive purposes, such as delivering annoying push notification advertisement. However, to the best of our knowledge, this problem has not been studied by our research community so far. To fill the void, this paper presents the first study to detect aggressive push notifications and further characterize them in the global mobile app ecosystem on a large scale. To this end, we first provide a taxonomy of mobile push notifications and identify the aggressive ones using a crowdsourcing-based method. Then we propose sc DaPanda, a novel hybrid approach, aiming at automatically detecting aggressive push notifications in Android apps. sc DaPanda leverages a guided testing approach to systematically trigger and record push notifications. By instrumenting the Android framework, sc DaPanda further collects all notification-relevant runtime information to flag the aggressive ones. Our experimental results show that sc DaPanda is capable of detecting different types of aggressive push notifications effectively in an automated way. By applying sc DaPanda to 20,000 Android apps from different app markets, it yields over 1,000 aggressive notifications, which have been further confirmed as true positives. Our in-depth analysis further reveals that aggressive notifications are prevalent across different markets and could be manifested in all the phases in the lifecycle of push notifications. It is hence urgent for our community to take actions to detect and mitigate apps involving aggressive push notifications.
Yen’s Algorithm-Based Charging Facility Planning Considering Congestion in Coupled Transportation and Power Systems

To promote the penetration of electric vehicles (EVs), a charging facility (CF) planning model based on Yen’s algorithm is proposed for coupled transportation and distribution systems (DSs) considering traffic congestion. This model not only takes into account the influence of new CFs on the power system but also considers the impact of CF locations on traffic flow distribution and congestion level in the transportation system (TS). Yen’s algorithm is innovatively employed to offer multiple possible choices for EV drivers’ route selection considering CF locations determined in the traffic flow assignment model. Overall, the total cost of both distribution and TSs is minimized to obtain the optimal CF planning results. For the DS, generation cost, energy loss, and penalty cost for voltage deviation are included. For the TS, the main objective is to ensure EVs can reach their destinations at the lowest cost, while the travel time due to different path selections and the delay time caused by congestion can be minimized. Finally, a comprehensive case study on the integrated IEEE 30-bus and a 25-node TS is conducted to validate our approach.
Analysis of internal social media for in-house job training aimed at improving the efficiency of human-resource development

Most Japanese companies have their own in-house training systems. However, only a few companies have systems to fully verify the training effectiveness. Furthermore, an increasing number of companies are using social media for both internal communications and in-house training discussions. Therefore, by analyzing this accumulated data in social media, it is possible to verify the effects of in-house training and career education. This research is a joint study with a company that develops internal social-media system for in-house training. We analyze the accumulated data in a practical system by using natural language processing. This research aims to visualize both training proposals tailored to each individual and the characteristics of each trainee from the analysis results. It also aims to improve the effectiveness and the efficiency of in-house training systems.
Short-Sale Constraints and the Pricing of Mutual Funds

The literature proposes that, when combined, difference in opinions and short-sale constraints could lead to asset overpricing. We argue that the same intuition applies to the pricing of mutual fund skills, because investors certainly cannot short bad mutual funds. When investors have different opinions on managerial skills, managers could charge a fee that is higher than the value (α) that they can deliver, which allow them to retain only the most optimistic capitals. This extends the Berk and Green (2004) model, and can help explain a list of stylized observations and puzzles in the mutual fund industry, including the underperformance of active funds, the existence of flow convexity, and the negative correlation between gross-of-fee α and fees. 1 NUS Business School, 15 Kent Ridge Drive, Singapore, 119245; E-mail: chengsi@nus.edu. sg 2 INSEAD, Boulevard de Constance, 77305 Fontainebleau Cedex, France; E-mail: massimo.massa@insead.edu. 3 INSEAD and CKGSB, 1 Ayer Rajah Avenue, Singapore, 138676, Email: hong.zhang@insead.edu
A Novel High Gain DC-DC Converter Employing Z-Source Network for PV Applications

This paper presents a novel DC-DC converter controlled by a single switch for photovoltaic applications. The proposed converter integrates an Z-source network with a Boost -Self lift Cuk converter. The output voltage of a single photovoltaic panel is limited and it necessitates the use of DC-DC converters with high voltage gain. By using the proposed topology, it is possible to step up the output voltage of a PV panel and it offers high output gain compared to that of existing Boost Self-lift Cuk converter. Modes of operation of the proposed converter are presented. A MATLAB/Simulink model is developed and to validate the circuit,simulation results are included.
Implementation of MPPT for Flexible Solar Cells embedded on Unmanned Aerial Vehicles

This paper presents a Maximum Power Point Tracking (MPPT)method for a flexible organic polymer solar cell (FOPSC) under varying shading condition. FOPSC was fabricated using a composite of three conjugated polymers namely PFO, PEO-at-co-MEH-PPV, and MEH-PPV as active layer, CNT/rGO composite as counter electrode (CE), substrate made of Poly-Ethylene Terephthalate (PET). The fabricated OPSC showed around 0.69 as fill factor (FF), a 0.67 V of voltage at open circuit condition(Voc), a 6.37% of power conversion efficiency (PCE, $\eta$) of and a 13.69 mA/cm2 as its current density (Jsc) at short circuit condition. The PCE of OPSC was comparable to that of OPSC with Pt CE ($\eta =$7.82%). Four OPSC strips where connected in series, aground-based UAV model and different shading conditions were recreated and the power to voltage relationships were obtained. Based on the experimental data obtained, a MPPT techniques was developed using second order derivative of output voltage with respect to duty cycle ratio (D2VOC). The buck boost converter (BBC) with a PWM controlled using a microcontroller was utilized to implement the D2VOC based MPPT.