Data Messages Research Articles

Khuluma: Using Participatory, Peer-Led and Digital Methods to Deliver Psychosocial Support to Young People Living With HIV in South Africa.

Khuluma is a psychosocial and peer-to-peer mHealth intervention that uses text messaging to facilitate support groups for adolescents living with HIV (ALWH) with the aim of contributing toward positive health outcomes. Although use of mobile technology in the form of mHealth interventions has proliferated recently in the field of health, published literature describing methods and processes of its application are limited. We present a set of methods and processes utilised to develop and pilot the Khuluma mHealth intervention amongst young people (15–20 years) in South Africa. We recruited and enrolled 52 adolescents (15–20-year olds) from four clinics in Pretoria and Cape Town to participate in a 6-month pilot of Khuluma. Participants were ALWH, aware of their status, on antiretroviral therapy for more than 12 months, and not suffering from severe depression. We conducted four pre and post intervention focus group discussions (FGDs) with a proportion of ALWH (n = 36) enrolled in the pilot study using participatory methods. Several processes were utilised to then implement this pilot study. These included engaging ALWH for minor study implementation modifications; forming virtual groups; activating the mHealth platform; facilitating and delivering the Khuluma intervention. The acceptability of the intervention was informed by follow-up focus group discussions and text message data. The initial participatory processes helped to tailor the intervention design to participants' needs. The peer-led facilitation of the groups allowed for the provision of sensitive psychosocial support that allowed young people to express themselves freely, develop a sense of self-worth, and interact more. The nature of the mobile technology also allowed participants to build friendships beyond their geographic area and interact with their peers in real time. Within the evolving context of COVID-19, establishing evidence-based processes and methods for intervention design and curation in virtual spaces is critical.

Impairments-aware time slot allocation model for energy-constrained multi-hop clustered IoT nodes considering TDMA and DSSS MAC protocols

The possibility of Internet of Things (IoT) is that a large number of live items (e.g., apparatuses) in the network are available, detected, and interconnected. In any case, the performance of IoT networks may be limited due to several impairments, most importantly, the energy-constrained IoT nodes. In fact, this limitation opens the door to many researchers where using network clustering has proven to be efficient energy saving mechanism. To the best of our knowledge, there are no prior research, in the field of multi-hop clustered IoT networks, which addressed the energy-constrained IoT nodes problem along with the delay in receiving data messages from devices, located far away from the remote users (or control center), in timely basis. Practically, it is significantly challenging to contemplate and clarify this issue. Consequently, in this paper, we make major amendments on the prior work, Improved Energy and Distance Based CH Selection with Balanced Objective Function (IEDB-CHS-BOF), and particularly propose a multi-hop routing (MR) protocol in which the IoT network is divided into a number of virtual sections with lengths held below the cross-over communication distance, thereby ensuring minimal energy depletion. Over those virtual sections, efficient forwarder and cluster head selection algorithms are further proposed. Interestingly, we propose a novel delay-, power-, and interference-aware time slot allocation model in which Time Division Multiple Access (TDMA) and Direct Sequence Spread Spectrum (DSSS) MAC protocols are operated. Furthermore, it is a good representation of the above-mentioned proposals. As a result, our protocols are referred to as MR-IEDB-CHS-TDMA and MR-IEDB-CHS-DSSS, respectively. To this end, numerous simulations have been conducted for evaluating the performance of the proposed protocols in the perspective of IoT network lifetime. In addition, sufficient comparisons have been conducted with the existing state-of-the-art protocols. In overall, the MR-IEDB-CHS-TDMA protocol keeps the IoT network functioning the longest.

Design of a secure file storage and access protocol for cloud-enabled Internet of Things environment

The so-called cloud-enabled Internet of Things (CIoT) systems interconnect numerous devices to render robust data storage, efficient analysis, and message exchange features. However, it confronts the confidentiality of data from the owner as the access control of data is performed by honest-but-curious service providers. Although the encryption strategy ensures data security, it has adverse data deliverance due to its inherent all-or-nothing decryption. Thus, a robust protocol is proposed to achieve data sharing among geographically dispersed physical devices and efficient access to cloud data for clients. The proposed protocol resists the chosen-ciphertext attack (CCA) based on the hardness of the Decisional Diffie–Hellman Inversion (DDHI) assumption. The comprehensive analysis and simulation results show that our protocol is efficient in computation, communication, and storage costs.

A Survey on Various Clustering Algorithms in WSN for Optimal Energy Utilisation

Wireless sensor networks comprise of an expansive number of distributed sensor gadgets, which are associated and composed through multi-hop steering. Because of the presence of related data and excess in measuring data, data messages can be joined and converged by performing data aggregation work in the steering procedure. To diminish energy utilization is a noteworthy enhancement target of data aggregation approaches, which can be accomplished by diminishing the mandatory correspondence load of steering. To improvise the network lifetime as much as possible in Wireless Sensor Networks (WSNs) the ways for data move are picked in a way that the aggregate energy used along the way is limited. To help high adaptability and better data aggregation, sensor nodes are routinely collected into disjoint, non-covering subsets called clusters. Clusters make various leveled WSNs which consolidate proficient use of constrained assets of sensor nodes and in this manner broadens network lifetime. The objective of this paper is to demonstrate a forefront survey on clustering calculations announced in the writing of WSNs. This paper presents different energy effective clustering calculations in WSNs. From the hypothetical level, an energy show is proposed to approve the advantages of data aggregation on energy utilization. The key parameters which may affect the aggregation execution are additionally examined.

Implementation of Local Area Network (LAN) & Build a Secure LAN System for BAEC Head Quarter

Network security is the process of taking physical and software preventative measures to protect the underlying networking infrastructure from unauthorized access, misuse, malfunction, modification, destruction, or improper disclosure, thereby creating a secure platform for computers, users, and programs to perform their permitted critical functions within a secure environment. A local area network (LAN) is a computer network within a small geographical area such as a home, school, computer laboratory, office building or group of buildings. A LAN is composed of inter-connected workstations and personal computers which are each capable of accessing and sharing data and devices, such as printers, scanners and data storage devices, anywhere on the LAN. LANs are characterized by higher communication and data transfer rates and the lack of any need for leased communication lines. A data network is an interconnected system of computers, peripherals and software over which data files and messages are sent and received. LAN is only one type of computer network. LAN define is Data com system allowing a number of independent devices to communicate directly with each other, within a moderately sized geographic area over a physical communications channel of moderate data rates. Fiber-optic communication is a method of transmitting information from one place to another by sending pulses of infrared light through an optical fiber. The light is a form of carrier wave that is modulated to carry information. Fiber is preferred over electrical cabling when high bandwidth, long distance, or immunity to electromagnetic interference is required. This type of communication can transmit voice, video, and telemetry through local area networks or across long distances. Optical fiber is used by many telecommunications companies to transmit telephone signals, Internet communication, and cable television signals. Researchers at Bell Labs have reached a record bandwidth distance product of over 100 petabit × kilometers per second using fiber optic communication. Communication between remote parties can be achieved through a process called Networking, involving the connection of computers, media and networking devices. When we talk about networks, we need to keep in mind three concepts, distributed processing, network criteria and network structure. The purpose of this Network is to design a Local Area Network (LAN) for a BAEC (Bangladesh Atomic Energy Commission) Head Quarter and implement security measures to protect network resources and system services. To do so, we will deal with the physical and logical design of a LAN. The goal of this Network is to examine of the Local Area Network set up for a BAEC HQ and build a secure LAN system. Keywords: LAN, Secure LAN, BTCL, UTP, RJ-45, Bandwidth, Wavelength, ISP, Firewall, BAEC

Fault Diagnosis of Power IoT System Based on Improved Q-KPCA-RF Using Message Data

As the power system develops from informatization to intelligence. Research on data services based on the Internet of Things (IoT) focuses more on application functions, but the research on the data quality of the IoT itself is insufficient. Long-term continuous operation of the big data IoT system has the risk of performance degradation or even partial fault, which leads to a decrease in the availability of collected data for intelligent analysis. In this article, based on the power IoT message data, the characteristics are established through a variety of improved detection methods, and then the abnormal data type is obtained through Q learning and fusion of the random forest (RF) identification features. Finally, the topology of the specific power user IoT system is combined with kernel principal component analysis (KPCA) + improved RF algorithm getting the abnormal location of the IoT. The results show that the research method has a significantly higher positioning accuracy (from 61% to 97%) than the traditional RF method, and the combination method has more advantages in parameter adjustment and classification accuracy than directly using a multilayer perceptron (MLP).

5G New Radio channel coding for messaging in Smart Grid

The integration of the fifth generation of mobile communications (5G) into the distribution network has the potential to empower Advanced Metering Infrastructure (AMI) and Phasor Measurement Unit (PMU) applications, thus further advancing the concept of Smart Grid (SG). This paper analyzes the compatibility of 5G-NR (New Radio) standard-recommended coding schemes: Low-Density Parity-Check (LDPC) and Polar coding with message formats for generalized AMI and PMU communication recommended by standards IEEE Std 1703 and IEEE Std C37.118.2, respectively. Two standard-defined examples of communication sessions have been considered to determine the required 5G-NR transmission channel and associated coding scheme to be used for AMI and PMU-specific messages. The corresponding simulations have been performed following the specifics and boundaries defined by communication standards for 5G, AMI, and PMUs. In the AMI use case, simulation results indicate LDPC code superiority leading to the recommendation to be used for all message formats. PMU use case results reveal the Polar code application benefits for command messaging and its potential to be used for data messaging instead of LDPC code, which would require future adjustments of PMU data message format and further research on latency issues.

The role of drivers’ social interactions in their driving behavior: Empirical evidence and implications for car-following and traffic flow

Models for describing the microscopic driving behavior rarely consider the “social effects” on drivers’ driving decisions. However, social effect can be generated due to interactions with surrounding vehicles and affect drivers’ driving behavior, e.g., the interactions result in imitating the behavior of peer drivers. Therefore, social environment and peer influence can impact the drivers’ instantaneous behavior and shift the individuals’ driving state. This study aims to explore empirical evidence for existence of a social effect, i.e., when a fast-moving vehicle passes a subject vehicle, does the driver mimic the behavior of passing vehicle? High-resolution Basic Safety Message data set (N = 151,380,578) from the Safety Pilot Model Deployment program in Ann Arbor, Michigan, is used to explore the issue. The data relates to positions, speeds, and accelerations of 63 host vehicles traveling in connected vehicles with detailed information on surrounding environment at a frequency of 10 Hz. Rigorous random parameter logit models are estimated to capture the heterogeneity among the observations and to explore if the correlates of social effect can vary both positively and negatively. Results show that subject drivers do mimic the behavior of passing vehicles –in 16 percent of passing events (N = 18,099 total passings occurred in freeways), subject vehicle drivers are observed to follow the passing vehicles accelerating. We found that only 1.2 percent of drivers normally sped up (10 km/hr in 10 s) during their trips, when they were not passed by other vehicles. However, if passed by a high speed vehicle the percentage of drivers who sped up is 16.0 percent. The speed change of at least 10 km/hr within 10 s duration is considered as accelerating threshold. Furthermore, the acceleration of subject vehicle is more likely if the speed of subject driver is higher and more surrounding vehicles are present. Interestingly, if the difference with passing vehicle speed is high, the likelihood of subject driver’s acceleration is lower, consistent with expectation that if such differences are too high, the subject driver may be minimally affected. The study provides new evidence that drivers’ social interactions can change traffic flow and implications of the study results are discussed.

Design and Implementation of the Informatization Management System for the Meteorological Station Network Basic Data

The basic data of the meteorological station network has such problems as inaccuracy, untimely review and inconsistency among operational systems. Aiming to solve these problems, we design an informatization management system for the meteorological station network through the WeChat enterprise. It employs the area verification and the altitude validation based on the digital elevation model, and it performs a regular comparison with the data from the China Integrated Meteorological Information Sharing System. This system realizes the dynamic management for the filling, submitting and reviewing of the station network basic data. It has functions such as intelligent verification of the input data of the station network, efficient and convenient data review, timely reminder message and flexible data service interface. Therefore, the system effectively improves the accuracy of the station network basic data and the review efficiency.

Object motion detection in home security system using the binary-image comparison method based on robot operating system 2 and Raspberry Pi

This study aims is to build a home security system based on object motion detection using the Robot Operating System 2 (ROS2) and the Raspberry Pi. ROS2 in this study was used to read and process the camera data and to control the buzzer sound. At the same time, the Raspberry Pi hardware functioned to run ROS2 using the Linux Ubuntu 18.04 operating system. The camera function to read the image and video data could be developed for the input device to control the home security systems based on object motion detection. The method used to detect an object motion was Binary-Image Comparison (BIC). This method works by comparing the value of the binary image object with the binary master and using it as a decision-making algorithm when the camera detected the object movement based on the object colors. The object colors that were detected in this study were red, yellow, green, and blue. Each object color was processed using the OpenCV library in the ROS2 node service. After that, all of the nodes communicated through topics to communicating and exchanging the message data. This study has successfully developed a prototype that can generate a buzzer sound warning to the user when the camera detected the object motion based on the object color.

A Distributed Congestion Control Strategy Using Harmonic Search Algorithm in Internet of Vehicles

Aiming at the diversified requirements of network application QoS (Quality of Service) in the terminal equipment of Internet of Vehicles, this paper proposes a distributed congestion control strategy based on harmony search algorithm and the Throughput Evaluation Priority Adjustment Model (TEPAM) to ensure real-time transmission of high-priority data messages related to security applications. Firstly, the channel usage rate is periodically detected and the congestion is judged; then, in order to minimize delay and delay jitter as the goal, harmony search algorithm is utilized to perform global search to obtain a better solution for the transmission range and transmission rate. Secondly, packet priority and the TEPAM are applied to indicate the sending right of each packet. The data message priority and throughput percentage factor are used to express the transmission weight of each data message. Besides, the real-time evaluation of path state in MPTCP is carried out by the batch estimation theory model, which realizes the on-demand dynamic adjustment of the network congestion time window. Finally, SUMO, MOVE, and NS2 tools are used to create a VANET-like environment to evaluate the performance of the proposed congestion control strategy. Experimental results show that the proposed method is superior to other three methods in the four indicators of average delay time, average transmission rate, number of retransmissions, and packet loss rate compared with other advanced methods.

Strengthening the Achilles’ Heel: An AUV-Aided Message Ferry Approach Against Dissemination Vulnerability in UASNs

Underwater acoustic sensor networks (UASNs) have attracted considerable attention due to the increasing demands on the Internet of Underwater Things. The monitored underwater data are disseminated by anchored nodes in UASNs through multihop transmissions. In the military applications, some underwater spy robots are probably dispatched by the enemy to invade the UASNs, and these underwater spy robots seek to steal the data messages disseminated by anchored nodes. In this article, the autonomous underwater vehicles (AUVs) are taken as the ferries for the data message dissemination of some vulnerable anchored nodes, so as to reduce the risk of data messages being stolen by the spy robots. To this end, an index dissemination vulnerability is first introduced to measure the risk of data messages being stolen around anchored nodes, and the network topology is specially investigated to ameliorate the dissemination vulnerabilities of anchored nodes. An AUV-aided message ferry approach (AMFA) is proposed for the UASNs invaded by underwater spy robots. In AMFA, the anchored nodes set the initial communication ranges according to a power law distribution, and then, the communication ranges of anchored nodes are updated to achieve the required topology connectivity. Especially, some AUVs are assigned to ferry the data messages of the anchored nodes with the largest dissemination vulnerabilities. The simulation results demonstrate the preferable performance of AMFA, i.e., AMFA ameliorates the dissemination vulnerabilities of anchored nodes considerably while the required topology connectivity can be guaranteed.

A Selective reliable communication to reduce broadcasting for cluster based VANET

Vehicular Ad hoc Network (VANET) is one of the subset of Mobile Ad hoc Network (MANET) and it is a self-organised system with a group of vehicles, which are capable of short-range communication using On Board Unit (OBU). This unit is comprised with the vehicles that are possible to communicate with the nearby vehicles. VANETs rely on heavy broadcast transmission due to sharing data (messages) between the nearby vehicles about the traffic, collision and so on. This redundant information spoils the nature of VANET that affects the inter-vehicular communication, rebroadcasting and information on collision. This message transmission increases largely as the number of vehicles increases. This problem is typically named as broadcast storm and it is relatively reduced through the proposed Selective Reliable Communication (SRC) Protocol. Through a reliable communication, packets are retransmitted to reduce a number of transmission in the network within the acceptable level of QoS. The proposed SRC protocol automatically detect the vehicle clusters as “Zone of Interest”. Generally, the proposed protocol forwards the packets to the cluster-heads and the cluster-head forwards the packets to the cluster-members. The proposed protocol outperforms than the existing protocols in terms of Throughput, Packet Delivery Ratio (PDR) and Average delay.

An approach for Secured Image Transmission: A High Capacitive and Confidentiality based Image Steganography using Private Stego-Key

In the proposed paper an approach for image transmission with security and also improvement of the gray-scale (8-bit image) image flexible stenographic system using LSB approach. In this process a secret key of 80 bits is applied while embedding the message into the cover image. To provide high security and also confidentiality of the data a key stego-key is applied. The proposed method the information bits are embedded adaptively into the cover-image pixels. With this method a high embedding capacity in terms of hiding the data is provided and also better imperceptibility is also achieved. The major advantage of this method verifies by the Security method of Digital Signature. It is to be verified whether the attacker has made a trials to change the Secret information in the present inside the stego-image which is intended to be kept secret throughout the communication process. In this technique the embedding process to hide the message data present in the transformed spatial domain of the cover image and makes use of a simple Exclusive-OR operation based on Security checking method of verifying the signature digitally by using key size value of 140 bits is used to check the integrity from the stego-image. The confidential data which is embedded can be retrieved from stego-images. The security level is enhanced by using the stego key and by adaptive steganography data inconspicuousness is improved.

Spacecraft collision avoidance challenge: Design and results of a machine learning competition

Spacecraft collision avoidance procedures have become an essential part of satellite operations. Complex and constantly updated estimates of the collision risk between orbiting objects inform various operators who can then plan risk mitigation measures. Such measures can be aided by the development of suitable machine learning (ML) models that predict, for example, the evolution of the collision risk over time. In October 2019, in an attempt to study this opportunity, the European Space Agency released a large curated dataset containing information about close approach events in the form of conjunction data messages (CDMs), which was collected from 2015 to 2019. This dataset was used in the Spacecraft Collision Avoidance Challenge, which was an ML competition where participants had to build models to predict the final collision risk between orbiting objects. This paper describes the design and results of the competition and discusses the challenges and lessons learned when applying ML methods to this problem domain.

Instant messaging apps and data protection: combining to improve hip fracture care?

IntroductionThe General Data Protection Regulation (GDPR) continues to have implications for how healthcare information is managed and shared. This presents challenges as telemedicine plays a more central role in service healthcare service provision, particularly since the beginning of 2020. We aim to measure how improved communication through a GDPR-compliant messaging app can influence time-dependent key performance indicators for hip fracture management in a tertiary-referral trauma hospital.Methods Using an instant messaging service, a hip fracture group was created and access was provided to all stakeholders in hip fracture care—trainee and consultant emergency physicians and orthopaedic surgeons, as well as advanced nurse practitioners, bed managers, ward managers and theatre managers. Irish Hip Fracture Database (IHFD) standard compliance was compared from April to December 2017 and April to December 2018.ResultsTwo periods in 2017 and 2018 saw 121 and 122 hip fracture patients admitted, respectively. Mean time to admission to an orthopaedic ward in 2017 was 47 ± 42.9 h and 33.3 ± 42 h in 2018 (P = 0.5). Mean time to surgery in 2017 was 83.66 ± 53.46 h and 39.11 ± 10.84 h in 2018 (p = 0.026).ConclusionsIrish Hip Fracture Database Standards present a challenge to orthopaedic departments competing with other hospital specialties for access to beds and theatre space. The introduction of a GDPR-compliant social media messaging service has contributed to significantly reducing the time to surgery for these patients. Streamlining communication through messaging services has and continues to be vital to improving care for hip fracture patients, both in the healthcare environment and beyond.

Task offloading algorithm of vehicle edge computing environment based on Dueling-DQN

With the wide application of the Internet of vehicles, the rapid development of intelligent vehicles provides drivers and passengers with a good driving and riding experience. However, how to process a large amount of data messages in real time on resource-limited vehicle terminals is still a huge challenge, and it will cause great energy consumption to terminal devices. In this paper, a semi-online task distribution and offloading algorithm based on Dueling-DQN is proposed for time-varying complex vehicle environments. Firstly, the vehicle offloading system is built by the reinforcement learning, because the original optimization problem is a joint optimization problem with high complexity, and divided into the vehicle scheduling sub-problem and the vehicle computation resources optimization subproblem. We predicts different vehicle offloading behaviour, and calculates total rewards value after a series of vehicle offloading action, so as to update the vehicle offloading decisions. The simulation results show that this algorithm can improve the efficiency and energy consumption of computation tasks to a certain extent.

A New Message Expansion Structure for Full Pipeline SHA-2

Once there are constant or infrequently changed bits (COIBs) in two adjacent input messages of SHA-2, the switching power of input messages data registers (IMD-REGs) used for COIBs will disappear. Meanwhile, when full pipeline SHA-2 is applied in a certain application scenario where the IMD-REGs used for COIBs can be removed, more area of full pipeline SHA-2 can be saved as the proportion of IMD-REGs in message word registers increases. This paper proposes a new message expansion structure for full pipeline SHA-2 to increase the proportion of IMD-REGs. By inserting two expanders in last part of expansion structure pipeline stages and rescheduling the expander, the consumption rate of input messages will be decreased and the proportion of IMD-REGs will be increased. Compared with normal message expansion structure, the ratio of IMD-REGs to total message word registers in the proposed structure is increased from 15.1% to 41.6% for full pipeline SHA256, and 11.2% to 32.4% for full pipeline SHA512. When COIBs exists in adjacent input messages, the power and area advantages of proposed new message expansion structure have been demonstrated by FPGA and ASIC implementations.

How to Analyze Communication Data from Laboratory Experiments Without Being a Machine Learning Specialist

Recently, the analysis of communication has gained attention in experimental research. One important question is whether certain types of communication affect decisions differently than others. In this regard, Houser & Xiao (2011) present an approach for the classification of natural language messages. The primary limitation of their approach is its limited applicability to large message datasets. Therefore, Penczynski (2019) extends the methodological instruments by applying a machine learning classifier to experimental communication data. This is accompanied by the problem of a dearth of machine learning knowledge among experimenters. Hence, this paper presents an approach that employs a publicly available machine learning text analysis application. This makes it possible to analyze larger datasets based on small training datasets classified beforehand by human evaluators. As a first step, I use primary communication data reported by Charness and Dufwenberg (2006) to generate both training and test datasets. Following this approach, I am able to substantially replicate the original classification results obtained by Charness and Dufwenberg. The second step again involves messages from Charness and Dufwenberg as training data, while I take messages from a related trust game published by Deck et al. (2013) as a test, dataset. Promisingly, I am also able to replicate the classification results obtained by the external evaluators, as reported by Deck et al. The findings suggest that machine learning can be used to analyze large message datasets, both if the artificial intelligence is trained with data from the very same experiment and if it is trained with message data from a comparable experiment.

Resilient Wide-Area Damping Control for Inter-Area Oscillations to Tolerate Deception Attacks

Deception attacks that threaten communication networks will result in serious consequences ranging from the deterioration of damping performances to instability of power systems. To address this problem, this paper proposes a resilient wide-area damping control (RWADC) for inter-area oscillation based on a secure networked predictive control (SNPC), which is combined with information technology security system (ITSS) and the resilient control scheme based on networked predictive control (NPC). The ITSS including data encryption, data decryption and deception attack detection, is designed to guarantee data confidentiality, integrity, and authenticity. This security system is based on Data Encryption Standard (DES) and Message Digest Algorithm (MD5). The NPC part is used to provide optimal control sequences and compensate the impact of communication constraints and deception attacks, which includes modified generalized predictive control (MGPC), network delay compensator (NDC), and model identifier. Case studies are undertaken on the 16-machine 68-bus AC/DC hybrid power system. Simulation results show that the proposed RWADC can suppress inter-area oscillations, provide better damping performances than those of the conventional and robust WADC over different operating conditions and compensate adverse effects caused by deception attacks actively.