Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Testing of a Practical Smart Walking Cane for the Visually Impaired

A visually-impaired person, including the completely blind, normally uses a guiding stick for assistance while walking around and performing the daily tasks. The normal non-smart stick is limited to the little information gathered through its tip by touching the encountered objects. In this paper, we present a smart blind cane design that helps the visually-impaired users cope with their daily tasks and make their lives easier. We have added smartness to a light-weight stick by applying several technologies, including the ultrasound sensor that detects barriers of various shapes and types, the GPS/GSM technology that helps the users locate places and move from one place to another with the aid of a communication system, and the speech recognition technology that facilitates interactive communication between the user and the cane. Our practical tests show that the user is able to make speech commands to the stick that can subsequently call a pre-saved phone number, in addition to the effective ability of avoiding obstacles. Moreover, the smart stick can be programmed so that a pre-authorized person can call the stick and determine its GPS location for safety purposes.
A Meta Language for Cyber-Physical Systems and Threats: Application on Autonomous Vehicle

One of the main challenges in the development process of secure systems is how to detect as early as possible the system's vulnerabilities and weaknesses, and also how to quantify the severity of attacks through them. In this paper, we rely on the concept of attack surfaces to implement a secure cyber physical system in Java. Attack surfaces can be sometimes detected automatically, regarding the used language, by matching them against known attacks still is a step apart. Further, systems and attacks are not usually modeled with compatible formalism. This paper develops a modeling framework that automates the whole process by generating attacks for cyber physical systems. First, we formalize a system using UML class and activity diagrams. Further, we use UML to develop a meta language for cyber physical systems, cyber attacks, and cyber counter measures. The framework instantiates the dependent-application diagrams for the domain/application in test, searches for the existing attack surfaces; then it generates the possible attacks that might exploit the found vulnerabilities/weaknesses. Further the proposed framework generates the proper java code for the composition counter measures, attacks, and CPS models.
Prediction of the Multistage Throttle Orifice Plate Flow Characteristics based on Computational Fluid Dynamics and Neural Network Model

The multistage throttle orifice plate is a fluid pressure reducing device in the pipeline, its depressurization effect is affected by different parameters, such as the position and diameter of the holes in the throttle orifice plates, the distance between the throttle orifice plates. A numerical computational resource is required to achieve the flow characteristic with different parameters by computational fluid dynamics (CFD). Based on the neural network model of CFD simulation, the prediction of flow characteristic of multi-layer throttle orifice plate is realized in this paper. In the procedure, an automatic CFD simulation procedure of multilayer throttle orifice plate is constructed. Through the Latin Hypercube Designs (LHD) method, the parametric geometric model is generated. Then the flow rate of throttle orifice plate under different parameters are achieved under adaptive mesh generation technology and CFD simulation. The relationship between geometric parameters and the flow rate of throttle orifice plate is studied by multi-layer back-propagation neural network algorithm, and the flow characteristic predictive model is established. Compared with CFD simulation results, flow rate predicted by the predictive model and the maximum predictive error is 0.5%.
Detection Performance Analysis for Wideband Cognitive Radio Network : A Compressive Sensing Approach

Compressive Sensing (CS) has added a great advantage in signal processing because it requires significant computation through which a Cognitive Radio (CR) user can find an opportunity in the wideband spectrum. In this paper, CS has been presented which estimates a notable part of the wideband spectrum instead of recovering the whole wideband spectrum. Some spectrum sensing approaches have been presented through which CS will be accomplished under cooperative CR network and it will be compared with the non-cooperative case in terms of Receiver Operating Characteristics (ROC). In the analysis, the fading effect of the channel has been considered and investigated under Rayleigh and Nakagami channel. At the end, the most appropriate arrangement for CS under cooperative CR network has been discovered through step by step comparative analysis.
Non-uniform polarization profiles in P(VDF-TrFE) copolymer films after cyclical poling

Poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE)) copolymers, probably the most often used electro-active polymers, are rendered ferro-, pyro-, and piezoelectric via poling under high electric fields. Uniform polarization profiles across the sample thickness are advantageous or even necessary for most device applications. Here, we attempted to obtain spatially uniform polarization profiles in commercial P(VDF-TrFE) copolymer films with 50/50, 72/28 and 75/25 mol% of VDF/TrFE by means of cyclical hysteresis poling. The polarization profiles were mapped with Piezoelectrically generated Pressure Steps (PPSs), and the resulting depth profiles were correlated with the corresponding hysteresis curves. In addition, Fourier-Transform Infrared (FTIR) spectroscopy was used to identify the β-phase fractions in the P(VDF-TrFE) compositions. 75/25 mol% copolymer samples show the most uniform polarization profiles and the highest remanent polarization of 70 mC/m2 (as seen from the hysteresis curves) - corresponding to the highest β-phase fraction in comparison (as observed in FTIR measurements).
Prediction of Cardiovascular Disease using Data Mining Technique

In this proposed work, we have made an analysis of cardiovascular heart disease for the patients of all age groups using data mining techniques. The preprocessed dataset consists of all the accessible 16 attributes (including class) which have been used in 299 patient records, taken from UCI Machine Learning Repository. We have taken some of the medicinal attributes such as ‘dig, prop, nitr, fast grume sugar’ etc. It can prognosticate the likelihood of sick person having cardiovascular sickness. We have scrutinized three data mining classification technique- the naïve Bayes, random tree and REPTree algorithms for prediction of cardiovascular disease. Our analysis shows that the classification model random tree prognosticates cardiovascular sickness with higher veracious outcome.
Planning of 5G Millimeterwave Wireless Access Network for Dense Urban Area

Network planning is an important step in the design of wireless networks, especially for 5 generation (5G). 5G networks must provide good service quality, high data rate and capacity. Therefore, 5G networks must be plan efficiently to deal with the increase of the data traffic. So, 5G wireless networks requires high grade of heterogeneity of small cell base stations, micro-cell base stations and macro cell base stations. In this paper, 5G wireless access network is planned for urban area in Ibb city, Yemen. The band 28 GHz of millimeter wave (mm-Wave) is used in this paper. Simulation results show that we need 223 micro cells to provide an acceptable services to 186532 subscribers in the covered urban area of Ibb city to satisfy densification network. The results also show that, the maximum achievable downlink and uplink throughput are 6.5 Gbps and 3.2 Gbps, respectively.
Cloud and Edge Multicast Beamforming for Cache-Enabled Ultra-Dense Networks

For the cache-enabled ultra-dense networks, edge caching is a promising technique for realizing low-latency transmission. In this paper, we study cache-enabled ultra-dense networks with the wireless fronthaul, in which edge nodes (ENs) have the capability of caching and signal processing. Under such a setup, by exploiting the feature that users requesting the same content form a multicast group and can be served by a cluster of ENs, we first formulate a problem to optimize the cloud and edge multicast beamforming design for maximizing the minimum rate among the user groups. Due to the coupling of transmit and receive beamforming and the non-convex constraints of delivery rate, the formulated problem is difficult to be directly solved. To this end, we propose to use the weighted sum mean-square error minimization approaches and certain transformation techniques to convert the original problem into a convex one. An optimal solution is then obtained by using bisection search and second order cone (SOC) transformation. The results indicate that the performance of the proposed precoding scheme with wireless frothauling will close to that of the wired fronthauling.
Influence Maximization Problem in Social Networks: An Overview

Social networks have attracted a great deal of attention and have in fact important information vectors that have changed the way we produce, consume and diffuse information. Social networks' analysis has been of great interest and has encompassed different research areas including community detection, the discovery of web services from social networks, information diffusion, detection of infuential nodes. The process of detecting influential nodes in social networks is often khown as Influence Maximization (IM) problem, it deals with finding a small subset of nodes that spread maximum influence in the network. It has been proved that it has many applications such as the propagation of opinions, the study of the acceptance of political blogs or the study of the degree of adhesion of an actor to a product in marketing (web marketing). A such maximization requieres the presence of a diffusion model that controls information propagation within active individuals. This paper aims to provide a survey on the influence maximization problem and focuses on two aspects, influence diffusion models and proposed approaches for influential nodes detection. We start by describing formally the IM problem, then we will provide the state-of-the-art of both diffusion models and influence maximization algorithms.
Global transcriptomic study of circRNAs expression profile in sorafenib resistant hepatocellular carcinoma cells

The anti-angiogenic drugs represented by sorafenib over the years have always been the first-line treatment of hepatocellular carcinoma (HCC), but the drug resistance has always been a "bottleneck" in curative effect. Recently, aberrant expression of circular RNA (circRNA) is considered to play a crucial role in many types of cancers. However, the genome-wide expression pattern of circRNAs in sorafenib-resistant HCC cells remains unknown. Herein, we identified 1717 differentially expressed circRNAs with 559 up-regulated and 1158 down-regulated (fold change > 2, P < 0.05) in sorafenib-resistant (HUH7-S) HCC cells along with 582 differentially expressed circRNAs with 272 up-regulated and 310 down-regulated (fold change > 2, P < 0.05) in sorafenib-resistant (HepG2-S) HCC cells, compared to parental sorafenib-sensitive (HUH7, HepG2) HCC cells by high-throughput sequencing. In addition, GO (Gene Ontology) term enrichment analysis results revealed an enrichment for binding and catalytic activity and for biological regulation of metabolic processes in both the Huh7-S and HepG2-S cell lines compared to parental cell lines. Moreover, KEGG (Kyoto Encyclopedia of Genes and Genomes) Pathway analysis of the differentially expressed genes were significantly related to pathways in cancer. Among them, hsa_circ_0006294 and hsa_circ_0035944 expression were consistently down-regulated in resistant HCC cells. Taken together, our data demonstrate, using a global transcriptomic network, that the circRNA expression profile is significantly altered in sorafenib-resistant HCC cells and that the differentially expressed circRNAs may play important functions in HCC sorafenib resistance and HCC progression.
Collaborative Whitelist Packet Filtering Driven by Smart Contract Forum

The massive spread of harmful content on the internet is hard to filter. Meanwhile, blacklist content filtering cannot keep up with the rapid growth of content creations. As a result, an extra protection layer is required to provide a safe internet for children. However, implementing a network or application firewall requires an expert’s knowledge and complicated maintenance. In this paper, we proposed a framework to automate internet protection by using whitelist packet filtering. We use the blockchain smart contract as the secure collaboration media to determine the filtering rules. Meanwhile, the SDN controller automates the packet filtering by installing the determined forwarding rules into the network switches. We evaluate the whitelist packet filtering by using Mininet for the network emulation and Ethereum Rinkeby networks for the smart contract implementation. The result shows that the proposed whitelist system can filter the packet without incurring significant latency. It supports fast content update with a maximum speed of ≈ 1200 valid contents per-minute by using a three-votes verification system.
Integration of Dual-Arm Manipulation in a Passivity Based Whole-Body Controller for Torque-Controlled Humanoid Robots

This work presents an extension of balance control for torque-controlled humanoid robots. Within a non-strict task hierarchy, the controller allows the robot to use the feet end-effectors to balance, while the remaining hand end-effectors can be used to perform Dual-Arm manipulation. The controller generates a passive and compliance behaviour to regulate the location of the centre of mass (CoM), the orientation of the hip and the poses of each end-effector assigned to the task of interaction (in this case bi-manipulation). Then, an appropriate wrench (force and torque) is applied to each of the end-effectors employed for the task to achieve this purpose. Now, in this new controller, the essential requirement focuses on the fact that the desired wrench in the CoM is computed through the sum of the balancing and bi-manipulation wrenches. The bi-manipulation wrenches are obtained through a new dynamic model that allows executing tasks of approaching the grip and manipulation of large objects compliantly. On the other hand, the feedback controller has been maintained but in combination with a bi-manipulation-oriented feedforward control to improve the performance in the object trajectory tracking. This controller is tested in different experiments with the robot TORO.
A Control Approach for the Variable-Height Inverted Pendulum Based on Sliding Mode Control With Input Saturation

Maintaining the balance when a robot is pushed forward is fundamental for legged robots. An essential topic in the literature is capture point; it is the place where the robot can step to in order to recover from the push. In this work, we study the Variable-Height Inverted Pendulum (VHIP) as the model for a pushed robot. We found all of the points that are allowed to be a capture point for given initial velocities of the center of mass and actuator limitations. We also develop a controller to reach a capture point using the reaction force to the ground as input variable. We pay attention to the unilateral contact and the maximum-value of a function of the reaction force. First, we obtain the necessary conditions that must be satisfied to be able to achieve balance by providing a decomposition of the VHIP into a new Divergent Component of Motion and a Convergent Component of Motion. Then we present two control laws to stabilize the system and we show that the region of attraction is equivalent to the region of necessary condition for balance. Finally, we briefly discuss the physical places where balance can be achieved.
Crocus: Enabling Computing Resource Orchestration for Inline Cluster-Wide Deduplication on Scalable Storage Systems

Inline deduplication dramatically improves storage space utilization. However, it degrades I/O throughput due to compute-intensive deduplication operations such as chunking, fingerprinting or hashing of chunk content, and redundant lookup I/Os over the network in the I/O path. In particular, the fingerprint or hash generation of content contributes largely to the degraded I/O throughput and is computationally expensive. In this article, we propose Crocus, a framework that enables compute resource orchestration to enhance cluster-wide deduplication performance. In particular, Crocus takes into account all compute resources such as local and remote {CPU, GPU} by managing decentralized compute pools. An opportunistic Load-Aware Fingerprint Scheduler (LAFS), distributes and offloads compute-intensive deduplication operations in a load-aware fashion to compute pools. Crocus is highly generic and can be adopted in both inline and offline deduplication with different storage tier configurations. We implemented Crocus in Ceph scale-out storage system. Our extensive evaluation shows that Crocus reduces the fingerprinting overhead by 86 percent with 4KB chunk size compared to Ceph with baseline deduplication while maintaining high disk-space savings. Our proposed LAFS scheduler, when tested in different internal and external contention scenarios also showed 54 percent improvement over a fixed or static scheduling approach.
“The Effect of Postural Education on Decreasing the Severity of Neck Pain in Female School Teachers: A Prospective Cohort Study” -

BACKGROUND: Musculoskeletal Disorders includes a wide range of inflammatory and degenerative conditions affecting the muscles, ligaments, tendons, nerves, bones and joints and it can occur from a single or cumulative trauma. Pain and physical disability brought about by MSD affects social functioning and mental health, further diminishing the teacher’s quality of life . A systematic review published in biomed central shows the prevalence of work related musculoskeletal disorders to be 39 % - 95 % in school teachers. Neck pain is reported to be 7th most prevalent pain site which is 68.9 % prevalent in school teacher. OBJECTIVES: The objective of the study was to find out the effect of postural education on decreasing the severity of neck pain in female school teachers. METHODS: 180 female primary and secondary school teachers aged 25 – 35years were conveniently selected for the study. Baseline survey: Teachers were asked to note down their neck pain using NPRS & NDI. Postural education programme : teachers received a lecture based on ergonomic training and occupational health education. Follow up survey : After 3months teachers were asked to note down their level of neck pain using NPRS & NDI after following the protocol. There were 20 drop outs in the study. RESULTS: There was a significant reduction in mean values of NPRS in baseline and follow up 25.44 – 17.6 respectively also NDI mean values 25.11 - 21.16 baseline and follow up respectively. After the intervention, teachers found the postural education programme to be effective in reducing the neck pain. CONCLUSION: Interventions based on occupational health education lectures, on-site ergonomics training, publicity brochures and posters showed a positive effect on prevention and control of the occurrence of work-related musculoskeletal disorders in teachers. KEYWORDS: Neck pain, Work related musculoskeletal disorders, Postural education.
Kinect Based Suspicious Posture Recognition for Real-Time Home Security Applications

Suspicious posture recognition is a paramount task with numerous applications in everyday life. We explore one such application in real-time home security using the Microsoft Kinect depth camera. We propose a novel method where the remote device itself detects the suspicious activity. The server is alerted by the remote device in case of a suspicious activity which further alerts the home owners immediately. We show that our method, works in real-time, is robust towards changing lighting conditions and the computations happen on the remote device itself which makes it suitable for real-time home security.
A Comparative Study Of Co-Occurrence Strategies for Building A Cross-Domain Sentiment Thesaurus

With the evolution of user-based web content, people naturally and freely share their opinion in numerous domains. However, this would result in a massive cost to label training data for many domains and prevent us from taking advantage of the shared information across-domains. As a result, cross-domain sentiment analysis is a challenging NLP task due to feature and polarity divergence. To build a sentiment sensitive thesaurus that to group different features that express the same sentiments for cross-domain sentiment classification, different co-occurrence measures are used. This paper presents a comparative study covering different co-occurrence methods for building a cross-domain sentiment thesaurus. This work also defines a Bidirectional Conditional Probability (BCP) to handle the unsymmetrical co-occurrence problem. Two machine learning classifiers (Naïve Bayes (NB) and Support Vector Machine (SVM)) and three feature selection methods (Information gain, Odd ratio, Chi-square) are used to evaluate the proposed model. Experimental results show that BCP results outperform four baseline co-occurrence calculation methods (PMI, PMI-square, EMI, and G-means) in the task of cross-domain sentiment analysis.
A Robot Design Method for Weight Saving Aimed at Dynamic Motions: Design of Humanoid JAXON3-P and Realization of Jump Motions

This paper proposes a design method of robots with high specific stiffness for dynamic jumping motions. In the proposed method, we search for high stiffness mechanical structures in a wide design solution space consisting of joint structural parameters as well as frame shape parameters. Particularly in the case of rotary joints driven by linear actuators, we resolve joint moments into actuator's tensile forces and frame's compressive forces and reduce loads exerted on a frame. Though this effect is already known, our method is novel in terms of utilizing this effect for designing robot structures systematically and for saving robot weights. In addition, we introduce a set of the wrenches which would be exerted on a frame (the Frame Load Region) and evaluate the lightness of several robots' structures by using the Frame Load Region. As a resultant of the proposed method, we developed a new life-size humanoid robot prototype JAXON3-P. Then we demonstrate the high motion performance of JAXON3-P and the effectiveness of the proposed design method through jumping motion experiments.