Miracle-dz/UniFAR-FTUs huggingface dataset:
Proposing Model for Security of IoT Devices in Smart Logistics: A Review

The information technology’s new revolution is Internet of Things (IoT), where physical world is connected to the internet. IoT applications are diversified such as smart health, smart industry, smart homes and most importantly smart logistics for perishable items conservation. Although IoT devices have revolutionized world but due to their constrained nature they are at the cost of a greater risk of personal data loss, security breaches and misuse. In this research, a review is presented for proposing two state of the art modules i.e. communication model of smart logistics and security of IoT devices in Smart Logistics. As the smart logistics have perishable items i.e. fruits, vegetables, meat, medicine, chemicals, and cosmetics etc. which are sensitive to temperature, humidity and pressure etc. If the sensors monitoring these items have been handled abnormally due to security attacks, it will give huge loss. Therefore, security of smart logistics is of paramount importance in this research. In order to expedite research in this emergent area of IoT, in this research paper a brief review on progress of IoT in smart logistics, and its security has been presented.
Wearables and the Internet of Things (IoT), Applications, Opportunities, and Challenges: A Survey

Smart wearables collect and analyze data, and in some scenarios make a smart decision and provide a response to the user and are finding more and more applications in our daily life. In this paper, we comprehensively survey the most recent and important research works conducted in the area of wearable Internet of Things (IoT) and classify the wearables into four major clusters: (i) health, (ii) sports and daily activity, (iii) tracking and localization, and (iv) safety. The fundamental differences of the algorithms associated within each cluster are grouped and analyzed and the research challenges and open issues in each cluster are discussed. This survey reveals that although Cellular IoT (CIoT) has many advantages and can bring enormous applications to IoT wearables, it has been rarely studied by the researchers. This article also addresses the opportunities and challenges related to implementing CIoT-enabled wearables.
Internet of Medical Things (IoMT) - An overview

Internet of Things (IoT) plays a vital role in the field of healthcare. The development of smart sensors, smart devices, advanced lightweight communication protocols made the possibility of interconnecting medical things to monitor biomedical signals and diagnose the diseases of patients without human intervention and termed as Internet of Medical Things (IoMT). This paper portrays an overview of Internet of Medical Things based remote healthcare, tracking ingestible sensors, mobile health, smart hospitals, enhanced chronic disease treatment.
On the strategies for Risk Aware Cloud and Fog Broker Arbitrage Mechanisms

Cloud and Fog computing has emerged as two powerful ways of doing computing where cloud computing is towards the server/network-centric and fog cmputing towards the edge and intermidiate network centric. In this paper, we propose a Cloud and Fog Broker Arbitrage mechanism to connect various Cloud Service Providers (CSPs), Fog Service Providers (FSPs) and users wherein user utility is modeled using Von Neumann Morgenstern utility theorem (VNM-UT). This utility function is used to select appropriate FSP/CSP for their task execution. It considers various parameters including user’s risk nature, price, reputation of FSPs and CSPs etc for the decision making. A unique contribution in this work is the decision making done by the brokers on the computation resources selection which can either be in the cloud or in the fog. We have also looked at dynamic pricing strategies for the CSPs and FSPs to adapt their prices based on current market conditions.
A Deep Learning Based Intrusion Detection System on GPUs

In recent years, almost all the real-world operations are transferred to cyber world and these market computers connect with each other via Internet. As a result of this, there is an increasing number of security breaches of the networks, whose admins cannot protect their networks from the all types of attacks. Although most of these attacks can be prevented with the use of firewalls, encryption mechanisms, access controls and some password protections mechanisms; due to the emergence of new type of attacks, a dynamic intrusion detection mechanism is always needed in the information security market. To enable the dynamicity of the Intrusion Detection System (IDS), it should be updated by using a modern learning mechanism. Neural Network approach is one of the mostly preferred algorithms for training the system. However, with the increasing power of parallel computing and use of big data for training, as a new concept, deep learning has been used in many of the modern real-world problems. Therefore, in this paper, we have proposed an IDS system which uses GPU powered Deep Learning Algorithms. The experimental results are collected on mostly preferred dataset KDD99 and it showed that use of GPU speed up training time up to 6.48 times depending on the number of the hidden layers and nodes in them. Additionally, we compare the different optimizers to enlighten the researcher to select the best one for their ongoing or future research.
Impulse Response for Full Wave PEEC Models avoiding late time instability

Late time instability is a key issue for obtaining time domain solutions using Computational Electromagnetic (CEM) full-wave techniques. However, impulse inputs lead to a convenient way to cascade time domain solutions for many problems. In this paper we show that stable impulse response solutions can be obtained for full-wave PEEC (Partial Element Equivalent Circuit) models which include retarded partial elements. The conventional time stepping technique is replaced by using the so called NILT (Numerical Inverse Laplace Transform) technique. We show that the late time unstable poles in the EM formulation are not excited by the NILT based solution.
Lifetime Enhancement for RRAM-based Computing-In-Memory Engine Considering Aging and Thermal Effects

RRAM-based computing-in-memory engines provide a promising platform to accelerate deep neural networks. The programming process imposes high voltages onto the RRAM cells and thus degrades their valid conductance ranges from the fresh state, an effect called aging. Consequently, the expected conductances of RRAM cells corresponding to the weights after training may fall outside of the valid ranges, potentially leading to a significant accuracy degradation. In addition, an uneven temperature distribution due to different conductances accelerates the aging effect further. Moreover, the uneven temperatures can cause accuracy discrepancy between the tuning process and inference, thus reducing the lifetime of such accelerators even further. In this paper, we propose to counter aging and thermal effects by distributing aging stress and high-temperature RRAM cells evenly, during both software training and hardware mapping, to extend the lifetime of computing-in-memory engines. Experimental results demonstrate lifetime enhancement up to 453 times while maintaining the classification accuracy.
Audio and Video Mixing Method to Enhance WebRTC

The WebRTC protocol can provide live streaming of peer-to-peer connections via JavaScript (JS) application programming interface (API) calls to a web browser. However, the protocol is restricted to a small number of peers because there is no simple way to mix real-time streams from multiple peers and then distribute the mixed stream to a large number of audiences. For example, it is necessary to mix audio and video streams from peers in a conversation and broadcast the real-time mixed stream to more than 10k audiences who only watch the video. It is also necessary to blend synchronous content (e.g., logos, music) to the live conversation stream. WebRTC does not currently provide a mechanism to easily support these cases. This paper proposes a method for the synchronized mixing of real-time audio/video streams from multiple peers while minimizing latency. This method enables the implementation of an online live conversation system that is able to mix live conversation streams from multiple peers and then rebroadcast the mixed stream to a large number of audiences.
Molecular Docking Study of Anti-Inflammatory Biomarkers in Sulawesi Propolis as Potent Inhibitors of Cyclooxygenase-2

NSAIDs seemingly arrived in their usage limitations as inflammatory drugs due to showing several side effects including gastrointestinal ulcerogenic activity and kidney dysfunction. Inflammatory response is known to be primarily controlled by Cyclooxygenase-2 (COX-2), thus suggesting it to be an important target for identifying novel inhibitor. Recently, Tetragonula biroi aff. stingless bee species from Sulawesi, Indonesia was known to have anti-inflammatory biomarkers, namely alpha-tocopherol succinate, xanthoxyletin, and deoxy-podophyllotoxin. Present study aims to discover new potent inhibitor of COX-2 from mentioned propolis by in silico approach. This experiment was used AutoDock Tools 1.5. 6 to prepare the structure of ligand and protein, AutoDock Vina to evaluate the binding affinity and LigPlot to visualize in 2-dimensional graphic of the binding pose. Docking studies amongst three candidates revealed that xanthoxyletin found to be the most potent inhibitor of COX-2 with binding affinity of -8.9 kcal/mol.
TIDAL-CAN: Differential Timing Based Intrusion Detection and Localization for Controller Area Network

Since the first reports on its lack of security, the Controller Area Network (CAN) was in focus for numerous research works. A specific area of research has employed physical layer characteristics that can be used to uniquely identify network nodes. But there are common downsides in existing approaches such as vulnerabilities in front of attacks involving node replacement or insertion or the inability to locate the intruder node within the network. In this work, we propose a new intrusion detection system for CAN which is based on monitoring the propagation time of the physical signals sent on the bus. Indeed, quite a number of recent works addressed the use of physical or timing characteristics to identify network nodes or to create covert channels. In our approach, by accounting for intrinsic delay characteristics of the bus and by monitoring the difference in signal arrival time at the two bus ends, we can identify nodes by location-related differential delays and provide relevant information for estimating the relative location of a transmitter node on the bus. The results of our experimental evaluation show that our approach provides very high identification rates and accurate localization in case of attacks from compromised nodes. The ability to detect attacks that replace an existing node or plug new adversarial nodes on the bus is also illustrated along with discussions on estimating sender location in these cases.
A Novel 3.3-kV Integrated ETO (IETO) With Single-Gate Controlling

In this article, a novel 3.3-kV integrated emitter turn-off thyristor (IETO) with single-gate controlling is proposed. Unlike the conventional emitter turn-off thyristor (ETO) using external MOSFETs, the IETO integrates the MOSFETs monolithically to switch ON and OFF. By featuring a P-layer beneath the trench of the carrier store trench bipolar transistor (CSTBT) to form self-biased pMOSs, the IETO clamps the potential of the P-layer, which shields the potential of the N-layer (carrier-stored layer), to reduce the saturation current. Due to the “self-clamping” effect, the high reverse voltage is sustained by the P-layer/N-drift junction, which makes the breakdown voltage (BV) independent of the dose of the N-layer. Then, the N-layer can be heavily doped to reduce <inline-formula> <tex-math notation="LaTeX">${V}_{\mathrm{\scriptscriptstyle ON}}$ </tex-math></inline-formula> without sacrificing the BV. TCAD simulation is compared with the CSTBT, which has the same controllability as the IETO and indicates that under the same level of BV, <inline-formula> <tex-math notation="LaTeX">${V}_{\mathrm{\scriptscriptstyle ON}}$ </tex-math></inline-formula> of the IETO is reduced by 0.12 V at <inline-formula> <tex-math notation="LaTeX">${E}_{\mathrm{\scriptscriptstyle OFF}} \approx 8.5$ </tex-math></inline-formula> mJ/cm<sup>2</sup>, and the <inline-formula> <tex-math notation="LaTeX">${E}_{\mathrm{\scriptscriptstyle OFF}}$ </tex-math></inline-formula> is 51.1% lower at <inline-formula> <tex-math notation="LaTeX">${V_{\mathrm{\scriptscriptstyle ON}}} \approx$ </tex-math></inline-formula> 1.45 V. Moreover, the saturation current density is also reduced by 12.2%.
Importance Calculation of Nodes in Complex Network Based on Improved TOPSIS

It is of great significance to discover and protect important nodes in complex networks. In order to evaluate the importance of nodes in complex networks scientifically and overcome the one-sided shortcomings of single judgment methods such as complex network topology, node removal and node constringency method, this paper propose a scientific method for evaluating node importance. Firstly, we seperately evaluate the network topology and evaluate the importance of nodes by destroying the network structure to calculate the following 4 kinds of index: the degree value, closeness centrality, betweenness centrality and the degree of network efficiency reduction after removing nodes. Secondly, using the improve TOPSIS (technique for order preference by similarity to an ideal solution) algorithm to fuse all index, calculate the relative approach degree and rank the importance of each node. Finally, evaluating the method using the "ARPA network" and "Italian network", the result of the experiment confirmed that this method is more accurate than the single node importance evaluation method and verified its feasibility and scientificity.
Elastic Properties of B, C, N-decorated on Planar Aluminene using Density Functional Theory

This study investigated the mechanical properties of boron, nitrogen and carbon doped planar aluminene using density functional theory which was implemented through the Vienna Ab Initio Simulation package (VASP). Computations used a generalized gradient approximation (GGA) and the Perdew-Burke-Ernzerhof (PBE) exchange correlation functional. A 3x3 supercell was constructed containing a monolayer of planar aluminene with a vacuum of 20 Å above the surface. Convergence tests showed a cut-off energy of 450 eV and gamma centered grid 8 by 8 by1 for brillouin zone sampling in the reciprocal space were enough for accurate calculations. Three possible sites of adorption on the aluminene were identified: top, bridge and hollow sites. Static calculations were performed to estimate the location of the decorations above the aluminene surface from 0.20 Å to 6.00 Å with a step size of 0.20 angstroms. All three decorations easily be adsorbed on the surface. Results showed all decorations can be adsorbed on the surface at all sites. The in-plane bulk modulus, cohesive energy, and in-plane stiffness tensor were then calculated for all three decorations and compared to that of pristine aluminene. The modulus and stiffness of nanomaterial improved when carbon and boron are adsorbed at the bridge site, and nitrogen at the hollow site. All 2D systems in this study have better elastic proeprties compared to bulk aluminum.
NFV/SDN Enabled Architecture for Efficient Adaptive Management of Renewable and Non-Renewable Energy

Ever-increasing energy consumption, the depletion of non-renewable resources, the climate impact associated with energy generation, and finite energy-production capacity are important concerns that drive the urgent creation of new solutions for energy management. In this regard, by leveraging the massive connectivity provided by emerging 5G communications, this paper proposes a long-term sustainable Demand-Response (DR) architecture for the efficient management of available energy consumption for Internet of Things (IoT) infrastructures. The proposal uses Network Functions Virtualization (NFV) and Software Defined Networking (SDN) technologies as enablers and promotes the primary use of energy from renewable sources. Associated with architecture, this paper presents a novel consumption model conditioned on availability and in which the consumers are part of the management process. To efficiently use the energy from renewable and non-renewable sources, several management strategies are herein proposed, such as prioritization of the energy supply and workload scheduling using time-shifting capabilities. The complexity of the proposal is analyzed in order to present an appropriate architectural framework. The energy management solution is modeled as an Integer Linear Programming (ILP) and, to verify the improvements in energy utilization, an algorithmic solution and its evaluation are presented. Finally, open research problems and application scenarios are discussed.
Super Field Plate Technique That Can Provide Charge Balance Effect for Lateral Power Devices Without Occupying Drift Region

The super junction has been the most important concept for the design of power devices. However, there are still two problems when the conventional super-junction techniques are applied on lateral power devices: a large portion of the drift region is occupied by a p-type region, and the super junction techniques are not suitable for the gallium nitride-based high electron mobility transistor (GaN-HEMT). To solve the problems, a super field plate (SuFP) technique is proposed as a charge balance principle. Our analyses proved that the SuFP can provide a charge balance effect for a lateral double diffused MOS (LDMOS) without occupying the drift region. As a result, the LDMOS with SuFP has a better performance than the LDMOS with other charge balance realization techniques. Moreover, as a kind of field plate, the SuFP is also suitable for GaN-HEMT. Thereby, the proposed SuFP technique overcomes the two problems in conventional super-junction techniques and is significant for lateral power devices.
A Novel Code-Aided Non-Orthogonal Multiple Access Technique in Downlink MIMO System

Conventional downlink non-orthogonal multiple access (NOMA) exploits the power domain for multiple access and applies successive interference cancellation (SIC) to mitigate intra-cluster interference. It requires sophisticated user terminals (UTs) clustering, moreover, imperfect SIC results in error propagation that severely degrades system performance. In this paper, a novel code-aided multiuser multiple-input multiple-output NOMA (MIMO-NOMA) framework for downlink transmission is developed. We propose a simple grouping algorithm that separate all UTs in a cell into several clusters, with cluster number less than or equal to the BS antenna array size. ZF-based multiuser beamforming is then employed to remove the inter-cluster interference. Computer simulation results verify that the proposed method outperforms the conventional schemes.
Quality Dimensions in Health Care Units in selected states of India An exploratory Study using SERVQUAL

The objective of this paper is to investigate the patients as customers, patient satisfaction and its determinants, measurement issues in health care units of India an exploratory approach. As the empirical study using five dimensions of SERQUAL in various cities covering three states of India Telangana, Chhattisgarh and Himachal Pradesh. A total of 120 responses from patients as customers and 45 responses from doctors. A seven point scale was used to investigate the results. The results reported are used by the health care units to refine, restructure to enhance quality management issues and for the future directions. This work helps in designing effective healthcare quality strategies in hospitals gap analysis has also been done. This report also identifies some discomfort in the patient services quality of the hospital for further improvements as an exploratory approach.
Breaking the Password Security Standards Using Offline Attacks and Public User Attributes

Password security standards based on the Shannon Entropy were made to ensure that users are protected from attacks. This research investigates the possibility of breaking the password security standards using offline attacks and public user attributes. The idea here is to reduce the keyspace by collecting a character set that is likely to be chosen as a password. Ten million compromised passwords were used to establish the Dictionary Character Set, while 1.4 billion compromised email accounts were used to establish the User-Attribute Character Set. Based on the experiments conducted, we proved that there is a high chance of breaking 8 – 10 character length passwords in a reasonable time. Dictionary and Attribute-Based attacks were proved to work in the wild based on cracking time and the number of compromised passwords in the datasets. Results show that it is possible to break the password standards using offline attacks and public user attributes in a reasonable time. A Machine Sensitive Key Based Password Strength Metric is then proposed based on the ratio of risk and safe probabilities of the password. The metric is based on the measurements gathered from the Brute Force, Dictionary and Attribute-Based Password Attacks.
A Comprehensive Review on Microgrid Architectures for Distributed Generation

In the recent years, there has been a growing interest in the concept of microgrids to integrate distributed generation systems like solar photovoltaic (PV) and wind to reduce greenhouse gas (GHG) emissions, to provide higher reliability for critical loads and to supply electricity in areas not served by existing grid infrastructure. A microgrid (MG) is a portion of the electrical system which views generation and associated loads as a subsystem, with the ability to operate both grid connected or islanded from grid, thus maintaining a high level of service and reliability. The existing grid infrastructure, the distributed energy resources to be integrated, as well as specific customer-oriented requirements will determine the best fitting architecture to constitute a microgrid. In this review, most common microgrids architectures based on AC, DC and hybrid AC/DC buses are analyzed. Furthermore, comparisons are made between different microgrid architectures. Positive and negative features of different architectures are given as a guide for further microgrid system studies.
Security Mechanisms Used in Microservices-Based Systems: A Systematic Mapping

Microservices is an architectural style that conceives systems as a modular, costumer, independent and scalable suite of services; it offers several advantages but its growing popularity has given rise to security challenges. Building secure systems is greatly helped by deploying existing security mechanisms, but current literature does not guide developers about which mechanisms are actually used by developers of microservicesbased systems. This article describes the design and results of a systematic mapping study to identify the security mechanisms used in microservices-based systems described in the literature. The study yielded 321 articles, of which 26 are primary studies. Key findings are that (i) the studies mention 18 security mechanisms; (ii) the most mentioned security mechanisms are authentication, authorization and credentials; and (iii) almost 2/3 of security mechanisms focus on stopping or mitigating attacks, but none on recovering from them. Additionally, it emerges that experiments and case studies are the most used empirical strategies in microservices security research. The clear identification of most-used security solutions will facilitate the reuse of existing architectural knowledge to address security problems in microservices-based systems.