Miracle-dz/UniFAR-FTUs huggingface dataset:
A Modified Tiny Encryption Algorithm Using Key Rotation to Enhance Data Security for Internet of Things

The Tiny Encryption Algorithm (TEA) has been proven to be suitable for constrained devices because of its lightness. However, TEA suffers from equivalent key and related key attacks. This paper proposed a modification to TEA to improve its security by rotating its subkeys to every round function as the new key scheduling scheme. Also, the round function of TEA was also modified by shifting the keys before integrating to the functions. The modified TEA was benchmarked with the original TEA with avalanche effect and completeness test. The modified TEA avalanche effect is 54.4% against 47.2% for TEA, and its’ completeness test is 51.4% against 49% for TEA. The modified TEA was also tested with equivalent keys and produces different ciphertext. The tests showed that the modified TEA is more secure than the original TEA.
CrowdRE, User Feedback and GDPR: Towards Tackling GDPR Implications with Adequate Technical and Organizational Measures in an Effort-Minimal Way

In 2018, the General Data Protection Regulation (GDPR) came into force, imposing strict laws aimed to protect the privacy of natural persons in member states of the European Union. However, the implications of the GDPR with respect to gathering, storing, and analyzing online user feedback — which is an important source of information for Crowd-based Requirements Engineering (CrowdRE) — have not been assessed yet. User feedback has been found to contain personal data, so the GDPR applies. It may be used for CrowdRE if conditions regarding data storage and handling are met and if, when used commercially, the duty to inform is carried out and the data subjects' rights and freedoms are respected. This can be a burden on the application of CrowdRE and might even inhibit its adoption. We propose a heuristic-based solution to anonymize the most prevalent types of personal data while crawling user feedback so that the data processing is no longer subject to GDPR.
Survey of integrability of procedural modeling techniques for generating a complete city

This article presents an overview of integrability of procedural modeling techniques needed to create a complete virtual city with streets, roads, building lots, exteriors and interiors with arranged furniture. Techniques are distributed into four hierarchies: urban plan, buildings, interior and furniture. Each technique is analyzed from the aspect of control of space definition, style uniformity, automatic interaction with other hierarchies and ability to procedurally generate a result around existing content. Each paper presented in this survey contributes either as a new control feature that has a potential of integrating with other techniques of higher, lower or same level of hierarchy, or as a new important part for creating a complete procedural city from highest to lowest level of hierarchy. The paper is concluded with a discussion of strong links between each area in the chain and important challenges in procedural generation of a complete city.
Comparative Analysis and Control of Bidirectional DC-DC Converters

The bidirectional DC-DC converters (BDC) is extensively promoted for numerous applications. Dual-active-bridge (DAB) converter is preferred among all other BDC converters for medium and high power application. There are some key challenges of isolated boost based BDC converters. Isolated boost based BDC converters offer high voltage spike, high current stress, and additional conduction losses due to flowing the freewheeling current in the switches of the low-voltage-side bridge of DAB converter. The auxiliary clamping circuits have been required to mitigate freewheeling current. The BDC converter with dual-switch forward (DSF) snubber has been presented in this paper. The converter operation of the BDC converter has been discussed. The various auxiliary clamping circuits have been explained. The control algorithm of the BDC DSF snubber circuit has been conferred. The comparative analysis has been considered among all BDC converters with the auxiliary clamping circuits. The PSIM simulation tool has been chosen to verify the effectiveness of the converter in the closed-loop control of the converter. The simulation results show the effectiveness of the converter.
Analysis of the Status Quo of Basic Education in Poverty Areas in Yunnan Based on the Big Data

The precondition for targeted education poverty alleviation is to accurately identify the target audience of poverty alleviation and their status quo of education. Through the purposing data mining and comparative data analysis, this paper will analyse the status quo of primary education of children in poverty areas in Yunnan from the macro and micro levels, and raise reasonable doubts about the popular academic viewpoint, that is distance education narrowing the gap between urban and rural areas.
Unsupervised Anomaly Alerting for IoT-Gateway Monitoring using Adaptive Thresholds and Half-Space Trees

Through increasingly powerful hardware, the computational resources of IoT-Gateways are growing, enabling more sophisticated data analytics, service deployments and virtualisation capabilities. However, the difficulty of ensuring high reliability of IoT-Gateways and its deployed services increases along with the complexity of digital systems. Reliable operation of such gateways and devices therefore depends on automated methods for detecting abnormal behaviour as early as possible, in order to remediate the situation before the complete failure of a system component. We propose an unsupervised anomaly detection algorithm by extending the concept of Half-Space Trees through online adaptive thresholds for real-time computation. The anomaly detector consumes multidimensional time series data from an external monitoring component and is fixed in computational complexity to support real-time operation. In order to determine valuable hyperparameters, we propose a data stream and anomaly simulation system, providing options for pattern induced load simulations and different types of anomalies. Further, we evaluate the anomaly detection method on monitoring data originating from a deployment of the open source software Project Clearwater, a lightweight implementation of the IP-Multimedia Subsystem capable of running on VMs with limited resources. Results show the applicability of Half-Space Tree based anomaly detection with high detection rates (99.4%) and low number of false alarms (< 3%).
The effects of Qiliqiangxin capsule on cardiac function and the plasma arginine vasopressin of rats with chronic heart failure

Objective To investigate the effects of Qiliqiangxin capsule on the plasma arginine vasopressin(AVP) of rats with chronic heart failure(CHF). Methods The rats model of CHF was established by ligating the left anterior ascending artery,and then were randomly divided into different doses of Qiliqiangxin capsule treated groups(Q1,Q2 and Q3 group),furosemide treatment group(F group),CHF group(C group) and sham group(S group). Cardiac function of rats were detected at the end of 6th week with echocardiogram and hemodynamic parameters.The level of plasma AVP was determined by radioimmunology.Results Comparison with S group,the cardiac function decreased obviously in C group,with the level of plasma AVP was increased(P0.01 ). The different dose of Qiliqiangxin capsule treatment groups could improve cardiac function and hemodynamic indexes of animal model.The level of plasma AVP was considerable decreased than that in C group(P0.05). While,there was no significant differences between F group and C group in cardiac function,and the level of plasma AVP in F group was increased dramatically(P0.05). Conclusion It demonstrated that the Qiliqiangxin capsule could improve cardiac function of CHF rats,which partly contributes to attenuating the plasma AVP.
Medical Image Segmentation Based on Wavelet Transformation and Level set method

Segmentation methods have been the subject of much research because they lead to many practical applications. Medical imaging is particularly concerned: it is indeed based on images of the inside of a patient's body (ultrasounds, x-rays, …) on which it is desired to automatically identify the presence of abnormalities (for example the detection of micro-calcifications in a mammogram may reveal the presence of breast cancer. We can refer to for an overview of the possible applications of wavelets and segmentation problems in medical imaging); but image segmentation is also used in many other areas: shape tracking in video documents, detection of stellar objects in astronomical images, detection of fronts in satellite images for data assimilation in meteorology,……. In this paper, we study a New robust Level Set image segmentation method developed by Wavelet Transformation and Level set model. Proposed algorithm is verified for simulated images and applied for a medical image processing in the MATLAB environment.
FDCTCP: A Fast Data Center TCP

Datacenter applications frequently cause incast congestion, which degrades both flow completion times of short flows and throughput of long flows. Many congestion control schemes have been proposed to meet the datacenters' performance requirement. Data Center TCP (DCTCP), using Explicit Congestion Notification (ECN) to infer congestion, has been proposed as a TCP variant for current state-of-the-art datacenters and recently has been a standard of IETF. In datacenter networks, where round trip times are in hundreds of microseconds, accurate feedback and quick rate control are crucial to achieve both high utilization and low queuing delay. However, DCTCP loses performance due to its slow and cautious reaction to incast. In this paper, we improve DCTCP and propose a fast congestion control mechanism, called FDCTCP, which can quickly detect incast using ECN, back off according to the congestion gradient and restore previous sending rate once incast ends. Our simulations show that FDCTCP greatly improves performance under different buffer size and significantly reduces the flow completion times, especially, for small and medium size flows compared to DCTCP.
Novel Precoding Structures Design of Multiuser with SWIPT for MIMO Downlink Systems

The paper proposes the novel precoding design to achieve the simultaneous wireless information and power transfer (SWIPT) for multiuser MIMO communication systems. In the traditional SWIPT system, base station (BS) can transmit signals to the information decoding (ID) users and transfer powers to the energy harvesting (EH) users, which are the independent users. The paper is designed by the SWIPT for the same user that can involve the functions of ID and EH. Three different precoding structures are proposed for SWIPT, which contains the parallel separating structure, the serial joint structure, and the simplified joint structure. The joint block diagonalization (BD) algorithm is utilized to suppress the multiuser interferences and acquire the wireless power, which can achieve the maximum sum rate of the overall systems. Moreover, we propose a novel separable precoder and post-processor algorithms to provide the EH users with more energy and to aid ID users with maximum sum rate. Finally, the simulation results show the proposed joint structure with better performance in the MIMO SWIPT system.
Design and Characterization of low loss Single Mode Fiber for Terahertz Signal Transmission

In this paper, Zeonex based hexagonal photonic crystal fiber (PCF) is proposed to obtain low confinement loss and moderate effective material loss (EML) at terahertz frequency. We use the finite element method (FEM) with a perfectly matched layer (PML) boundary condition to investigate the modal properties of the PCF. Simulated results demonstrate that this structure transfers signal in single mode condition. Besides, excessive low confinement loss of 6.73×10-11 dB/cm, and EML of 0.1491 dB/cm have obtained at an operating frequency of 0.55 THz. In this paper, other crucial guiding parameters such as air-core power fraction, effective area, bending loss, and dispersion of the fiber have also discussed. This terahertz fiber can be a good candidate for several applications in the terahertz regime.
Effect of Antisolvent Method on the Performance of HOIP based Memristive Devices

This paper presents a hybrid organic inorganic perovskite based memristive device having a structure that is commonly used for solar cells. Toluene is used as antisolvent during perovskite layer coating and its effect on the memristive device performance is studied in this report. It has been found that the antisolvent improves the morphology of the perovskite film. With this method, we obtained non-reversible resistive switching in the device with an on/off ratio of 104. This device also shows a reversible resistance switching with a set voltage of 0.5 V and a reset voltage of -0.9 V, measured at a sweep rate of 1 mV/s. The fabricated memory device shows promising performance and could be used as a non-volatile memory device for low power consuming applications.
Novel Vision-Based Abnormal Behavior Localization of Pantograph-Catenary for High-Speed Trains

To ensure the safe operation of high-speed trains, catenary anomaly detection and alerting security have become an urgent problem to solve. In this paper, we propose a novel method for abnormal behavior localization of a pantograph-catenary for high-speed trains. First, a modified faster RCNN is proposed to detect the pantograph faults. By adjusting the parameters of the faster RCNN, the positional accuracy of the candidate box and accuracy of the algorithm are guaranteed. We perform the arc detection after detecting the pantograph head area. The detection accuracy is over 99%. The height of the pantograph center point is also obtained during detection. Then, the actual running mileage of the fault point is calculated. Experiments show that the method proposed in this paper is also applicable to various complex scenes and that this method can determine the fault localization in the shortest time, narrow the maintenance scope, and improve the overhaul efficiency.
A Study of Arousal Classification Based on EEG Signal and Support Vector Machine

The development of Brain-Computer Interface technology nowadays has spread out in a case of classifying emotions based on brain signal (EEG) in human. One of the emotion parameters being focused in this research is arousal with the range from low (uninterested) to high (excited). A total of 32 EEG signals were observed in this study, consisting of 20 signals representing excited conditions and the other 12 being uninterested. This study was applied Principal Component Analysis (PCA) as feature extraction from both EEG signal groups. Then, statistical calculations are applied to reduce the dimensions of features. The support vector machine (SVM) algorithm was used for classification. The results of this preliminary study obtained the highest accuracy of 60% with PCA, entropy, and kurtosis as features.
Experimental study on effect of electro-heated stone needle on local skin blood perfusion of dorsum hand

[Objective] To observe the effect of electro-heated stone needle on the blood perfusion of dorsum of hand and to investigate the mechanism of the therapy. [Methods] Stimulation the third and 4th interosseous space of metacarpus of right hand by the 45℃ stone needle was performed and then the change of blood perfusion in the area of dorsum of hand and periumbilicus was observed with laser Doppler blood perfusion imaging system. [Results] After stimulation,the blood perfusion of right hand increased markedly (compared with pre-stimulation,P0.01),and the attenuation of the increased blood perfusion was not noted within 30 minutes after stimulation. On the other hand,there was not significant change of the blood perfusion in periumbilicus area within 30 minutes after stimulation. [Conclusion] Electro-heated stone needle therapy can increase skin local blood perfusion of dorsum of hand without any effect on the periumbilicus area.
Design and Implementation of Current Harmonic Filter

This article describes a design and implementation of Current Harmonic Filter (CHF) to achieve quality of power. The CHF system encompasses the DC-AC power converter, dc-link capacitor, interface inductor and Digital Signal Processor (DSP) controller. The power converter has developed through three-phase, three-wire based two-level Voltage Source Converter (VSC) topology. The control unit is deduced using Synchronous Reference Frame (SRF) method for reference current extraction and PWM-Space Vector Modulation (SVM) technique to generate switching gate pulses to drive the VSI. The entire control algorithm is coded in assembly language and executed through TMS320F240 DSP for 10 kVAR current harmonic filter. The experimental results captured the Total Harmonic Distortion (THD) of the source current, which is less than 5% under non-linear load.
DT-Track: Using DNS-Timing Side Channel for Mobile User Tracking

Targeted advertising is a form of online advertising that is directed towards audiences with certain traits. User tracking is useful to provide tailored web content or online advertisement. However, in the case without user online identities, targeted advertising becomes difficult. The challenge gets even higher in a mobile environment as the mobile user roams from one location to another location. In this paper, we propose a third-party web tracking scheme, named DT-Track, which can stealthily track users via the proposed side channel on DNS. The side channel is built on top of the cache existence of DNS records, which are commonly used.
The Crumple Zone Quality Enhancement of Electric Cars Bumper Fascia using a Carbon Fiber Reinforced Vinyl Ester – Microsphere Composites

The main issues addressed in this paper are energy absorption ability, deformation, and weight of composite material for electric car bumper fascia are. Carbon fiber Reinforcement Vinyl ester with Microsphere (CRVeM) material and Mild steel S45C are the main material-focus on this research. The use of CRVeM as fascia bumper material increases the quantity of energy absorption before material permanently damaged without adding significant mass for the bumper component and also has a good deformation ability for pedestrian safety during low-speed collisions rather than Mild steel S45C that is being used by LIPI electric car as primary front bumper material. Flexural test and thin-walled tube crash simulation was performed to define the mechanical properties and behavior of each material and from ABAQUS UNIFIED FEA simulation we came to a certain point of conclusion that CRVeM material has a better deformation than Mild steel S45C material with 24.4% for strain from the original length which is positive for pedestrian safety and low-speed crash such as car accident in a parking lot.
Deep Ranking-Based Sound Source Localization

Sound source localization is a cumbersome task in challenging reverberation conditions. Recently, there is a growing interest in developing learning-based localization methods. In this approach, acoustic features are extracted from the measured signals and then given as input to a model that maps them to the corresponding source positions. Typically, a massive dataset of labeled samples from known positions is required to train such models.Here, we present a novel weakly-supervised deep-learning localization method that exploits only a few labeled (anchor) samples with known positions, together with a larger set of unlabeled samples, for which we only know their relative physical ordering. We design an architecture that uses a stochastic combination of triplet-ranking loss for the unlabeled samples and physical loss for the anchor samples, to learn a nonlinear deep embedding that maps acoustic features to an azimuth angle of the source. The combined loss can be optimized effectively using standard gradient-based approach.Evaluating the proposed approach on simulated data, we demonstrate its significant improvement over two previous learning-based approaches for various reverberation levels, while maintaining consistent performance with varying sizes of labeled data.
Detection of Botnet traffic by using Neuro-fuzzy based Intrusion Detection

The attacks on various networks by intruders is on the rise and one of the most common model for launching attacks is by botnets. It has become very difficult for network administrators to detect and eradicate the bots in their network. Machine learning algorithms are increasingly being used for solving many classification problems including security systems for cloud. In this paper, we propose a new algorithm for the detection of botnet traffic by the use of neuro-fuzzy classification techniques. The dataset for the experimentation purpose was created by setting up an application on Eucalyptus cloud and attacking the application using various open source botnet simulation tools. The system achieved an accuracy of 94.78% with 15,000 instances and 56 attributes. The false positives of the system are considerably reduced when it is compared with the other related systems because of the introduction of the fuzzy rules into the system.
An Em Method for Multichannel Toa and Doa Estimation of Acoustic Echoes

The time-of-arrivals (TOAs) of acoustic echoes is a prerequisite in, e.g., room geometry estimation and localization of acoustic reflectors, which can be an enabling technology for autonomous robots and drones. However, solving these problems alone using TOAs introduces the difficult problem of echolabeling. Moreover, it is typically suggested to estimate the TOAs by estimating the room impulse response, and finding the peaks of it, but this approach is vulnerable against noise (e.g., ego noise). We therefore propose an expectation-maximization (EM) method for estimating both the TOAs and direction-of-arrivals (DOAs) of acoustic echoes using a loudspeaker and a uniform circular array (UCA). Our results show that this approach is more robust against noise compared to the traditional peak finding approach. Moreover, they show that the TOA and DOA information can be combined to estimate wall positions directly without considering echolabeling.
High Gain, Low Dark Current Al0.8In0.2As0.23Sb0.77 Avalanche Photodiodes

We report Al<sub>0.8</sub>In<sub>0.2</sub>As<sub>0.23</sub>Sb<sub>0.77</sub> avalanche photodiodes with high gain (<inline-formula> <tex-math notation="LaTeX">$M>1300$ </tex-math></inline-formula>) and low dark current at room temperature. Impact ionization coefficients for this material system are also extracted, indicating electron-dominant impact ionization. Low avalanche breakdown temperature dependence is demonstrated.
Ultra High Efficient 2x1 Graphene Patch Antenna Arrays for Single and Dual Band Operation

Graphene has opened the floodgate for a plethora of new applications in the field of communication due to its outstanding electrical and optical properties. In this paper, three types of Graphene antenna arrays, i.e. rectangular, circular and triangular are designed to operate around 3THz on a silicon (∈r = 11.9) substrate. A single band to dual band operation is achieved for all three types of Graphene antenna arrays at THz frequency range by changing the height of the silicon substrate, which has not been reported before. In comparison to rectangular and circular antenna arrays, triangular antenna array exhibits better performance in terms of S11, VSWR, BW and Radiation Efficiency with an S11 of - 39.44dB, VSWR of 1.024, BW of 103.4GHz and a staggering efficiency of 99.11%, which is the highest Radiation Efficiency, reported so far for Graphene antenna array application.