Harsh Communication Research Articles

Research on chaotic secure optical communication system based on dispersion keying with time delay signatures concealment

In response to the possibility of time delay (TD) signatures (TDSs) leakage becoming a serious problem in chaotic optical communication, from the perspective of improving the security of chaotic optical communication, this paper proposes a chaotic secure optical communication system based on dispersion keying, which generates signals with TDSs concealment characteristics. In this scheme, a common laser is used to drive chaotic synchronization between the transmitter and the receiver. The complex chaotic signal is generated by the combination of all-optical feedback and optical injection, and the TDSs are hidden by using the structure of dual filters and setting the parameters of each device reasonably. The switch is controlled by binary message to connect fiber Bragg gratings (FBGs) with different dispersion coefficients and maps different symbols to different chaotic attractors instead of the traditional way of directly sending messages to the channel. In addition, the generated signal no longer suffered from return map attacks. FBGs can compress and expand signals in the time domain to enhance the complexity of chaotic signals, and the dispersion value is an important key to effectively increasing the key space. Finally, the performance of TDSs concealment, sensitivity of parameter mismatch, and return map attack in this scheme are discussed in detail. The scheme still achieves a bit error rate (BER) of 1.74 × 10−4 when transmitting at a rate of 10Gbit/s under harsh communication environments such as 10 dB signal-to-noise ratio (SNR), which provides a reference for realizing high-speed and secure optical communication at the physical layer.

Representation of Parental Communication in Nanti Kita Cerita Tentang Hari ini (2020)

Family is the primary socialization agent, parents as important figures have the responsibility to educate and raise their children, one of which is through communication. But, in this day, there is still a lot of disharmonies in the family caused by several factors such as the lack of parental communication education from parents to children. On the other hand, a harmonious atmosphere can be built if there is an attitude of openness and good communication within the family, both verbally and non-verbally. Departing from this matter, the researcher further discussed the topic of family communication through the film, Nanti Kita Cerita Tentang Hari Ini as a reflection of similar cases in real life. This research uses Charles Sanders Pierce's semiotic method through signs, objects, and meanings. The results show that the father character has a dominant role with harsh communication that has a negative impact on the child, while the mother applies responsive communication that helps the growth of a positive personality in the child. Although the mother's role is not dominant, her parental communication serves as a balance to the father's communication in the family

Neural Myerson auction for truthful and energy-efficient autonomous aerial data delivery

A successful deployment of drones provides an ideal solution for surveillance systems. Using drones for surveillance can provide access to areas that may be difficult or impossible to reach by humans or in-land vehicles gathering images or video recordings of a specific target in their coverage. Therefore, we introduces a data delivery drone to transfer collected surveillance data in harsh communication conditions. This paper proposes a Myerson auction-based asynchronous data delivery in an aerial distributed data platform in surveillance systems taking battery limitation and long flight constraints into account. In this paper, multiple delivery drones compete to offer data transfer to a single fixed-location surveillance drone. Our proposed Myerson auction based algorithm, which uses the truthful second-price auction (SPA) as a baseline, is to maximize the seller's revenue while meeting several desirable properties, i.e., individual rationality and incentive compatibility while pursuing truthful operations. On top of this SPA-based operations, a deep learning based framework is additionally designed for delivery performance improvements.

Brain inspired optoelectronic integrated receiver chip for wireless optical communication

Inspired by the mechanism of visual attentional selection, a wireless optical communication (WOC) Integrated receiver consisting of a vertical double junction photodetector (VDJ-PD) and an attentional selection circuit (ASC) is presented. The whole receiver is fabricated in standard CMOS technology. The VDJ-PD can realize optical signal detection and wavelength identification. The attentional selection circuit activates the competition among the two PN junctions in VDJ-PD to select the signal with significant feature in real-time while discarding non-significant signals. A higher-order signal modulation scheme is applied by the proposed receiver to obtain a high transfer rate, and all data are decoded using color features. The optical testing results show that parallel and real-time communication of the red and blue light can be achieved, and the rise time is 4.47 μs. To measure the anti-interference performance of the receiver, a water tank is used to simulate a harsh communication environment. Results indicate that the real-time and reliable communication requirements in a harsh channel condition are satisfied. When the percentage ratio between the intensity of stray light relative to the light with maximum intensity is 84%, an accurate information decoding can still be achieved. Moreover, the whole processing procedure does not require the participation of ADC, CPU and memory, consequently avoiding the von Neumann bottleneck.

Edge-Enabled Anti-Noise Telepathology Imaging Reconstruction Technology in Harsh Environments

With the advent of the 5G era, telemedicine and mobile health play an increasingly important role in our daily lives. In the diagnosis process of telemedicine, image processing of telepathology is particularly important to doctors, pathologists, and relevant researchers. In this article, we propose an intelligent telepathology imaging terminal system, the images of which are obtained by Fourier ptychographic microscopy (FPM). For the proposed system, a CNN model is designed and trained to perform the FPM reconstruction to increase the quality of the images and improve the speed of reconstruction. Furthermore, edge learning technology is used in the proposed system to reduce the pressure of data storage and transmission. The proposed scheme is applied in harsh communication environments of low signal-to-noise ratio. The theoretical analysis and experimental results show that the proposed system achieves high-quality digital images and phase maps of histological samples.

Distributed Cooperative Energy Management System of Connected Hybrid Electric Vehicles With Personalized Non-Stationary Inference

This article develops a distributed cooperative energy management system (EMS) with two distributed control layers for speed-coupling plug-in hybrid electric vehicles (PHEVs). By introducing personalized non-stationary inference, this system can fuse driving behavior and vehicle state information to adaptively adjust power-split control parameters for the improvement of vehicle energy economy. In the on-board control layer, five sets of personalized control parameters are optimized offline using chaos-enhanced accelerated particle swarm optimization (CAPSO). In the distributed control layer, interval type 2 (IT2) fuzzy sets are applied to develop a real-time driving style recognition function. The driving behavior is detected remotely, via the vehicle-to-everything (V2X) network, and downloaded to adaptively adjust the power-split control parameters in the on-board vehicle controller. Hardware-in-the-loop testing is carried out based on the four laboratory driving cycles and four personal driving cycles. The proposed system has been demonstrated with strong robustness that saves energy by up to 5.25% over the equivalent consumption minimization strategy (ECMS), especially for gentle drivers. Even under harsh communication conditions (with signal loss 80+%), it still performs better than the ECMS (by 0.57%) and the series–parallel (SP) control strategy (by 2.66%).

Event-Based Distributed Frequency Control in Harsh Communication Conditions

In this article, distributed control methods are widely applied in the operation of distributed generators (DGs) in modern power grids. As distributed control, the control operation depends greatly on information exchange among neighboring distributed controllers, where harsh communication conditions (e.g., limited communication rates and accidental communication failures) may cause significant performance deterioration. Therefore, it is necessary to investigate distributed control of DGs under imperfect communication conditions in practical systems. This article proposes an event-based distributed DG frequency control strategy. By introducing an event-based update mechanism for real-time DG data measurements and the communication topology, the adaptability of the control strategy to low communication rates and communication failures is significantly enhanced. Besides, the above-mentioned nonideal communication conditions, the proposed control also shows high adaptability to communication delays. Furthermore, an optimal design method of the control parameters is developed, which ensures proper steady-state performance and optimizes the dynamic performance of the proposed control. Simulations based on MATLAB/Simulink and hardware experimental validations using dSPACE under various conditions verify the effectiveness of the proposed control.

Parental Discipline Patterns on Children in Penjaringan Slums

This research aimed to describe the discipline pattern that the parents had on their children. This research was held in slum area of Penjaringan in DKI Jakarta. Total of 154 people became the participant in this research. This was a descriptive study that wish to explore the discipline pattern that parents implemented to their children. Along with that we also explored about communication pattern and relation in family. We used questioners for information gathering and implemented observation, interview and small group discussion. To analyze the data, we used describtive statistical analysis technique and qualitative analysis. Most of the participant cared about their children. Nevertheless they implemented harsh communication style to their children.The parcitipant had a hope to be an ideal parent but did not have any idea what to do. Further research needed to be done and actions had to be implemented in order to create a healthy and fully functioning family in the slum area of Penjaringan.

A Novel Multi-Robot Task Allocation Model in Marine Plastics Cleaning Based on Replicator Dynamics

As marine plastic pollution threatens the marine ecosystem seriously, the government needs to find an effective way to clean marine plastics. Due to the advantages of easy operation and high efficiency, autonomous underwater vehicles (AUVs) have been applied to clean marine plastics. As for the large-scale marine environment, the marine plastic cleaning task needs to be accomplished through the collaborative work of multiple AUVs. Assigning the cleaning task to each AUV reasonably and effectively has an essential impact on improving cleaning efficiency. The coordination of AUVs is subjected to harsh communication conditions. Therefore, to release the dependence on the underwater communications among AUVs, proposing a reliable multi-robot task allocation (MRTA) model is necessary. Inspired by the evolutionary game theory, this paper proposes a novel multi-robot task allocation (MRTA) model based on replicator dynamics for marine plastic cleaning. This novel model not only satisfies the minimization of the cost function, but also reaches a relatively stable state of the task allocation. A novel optimization algorithm, equilibrium optimizer (EO), is adopted as the optimizer. The simulation results validate the correctness of the results achieved by EO and the applicability of the proposed model. At last, several valuable conclusions are obtained from the simulations on the three different assumed AUVs.

Harsh Communication Environment Oriented Consortium Blockchain Construction on Edge for Internet of Things

In recent years, the Internet of Things has developed rapidly, and users have gradually become more precise in their control of IoT devices. The use of mobile cloud services in IoT has become a new trend. However, its information security and traceability strategies are still to be studied. This article introduces the application of edge computing architecture in harsh communication environments, and analyzes its deployment requirements for consortium blockchain in combination with IoT application scenarios. The consortium blockchain framework for the harsh communication environment of IoT is proposed, and the overall structure, node deployment, consensus algorithm and security mechanism are introduced, the basic process is finally explained. It provides credible solutions for the information security, traceability, and sharing of IoT devices in harsh communication environments.

A dynamic source routing protocol based on path reliability and link monitoring repair.

The two most essential factors for mobile self-organizing networks applicable to drones are reliability and stability. In harsh communication environments, such as mountainous regions and natural disasters, the use of satellites and terrestrial communication stations has severe time delays due to the high speed of UAVs, resulting in frequent communication interruptions with UAVs. Therefore, UAVs need to establish self-organizing networks for communication and information sharing. High-speed movement will lead to rapid changes in the network topology, resulting in established links being in an unstable connection state and even frequent routing errors, thus preventing the establishment of stable communication links. In order to improve the communication quality of UAVs under high-speed movement, we propose a dynamic source routing protocol based on path reliability and monitoring repair mechanism (DSR-PM). The model performs data transmission by filtering the best reliability path. The link state information is monitored during transmission and broken links are repaired in time to ensure the communication stability and reliability of the links and improve the data transmission efficiency. We simulated the approach in NS2 software and the simulation results show that the DSR-PM protocol effectively reduces parameters such as overhead, packet loss and delay, improves network throughput, and provides better communication performance.

On the robustness of consensus-based behaviors for robot swarms

In swarm robotics, behaviors requiring consensus, meaning having the robots agree on a set of variables, have attracted great attention over the years. Determining the robustness and applicability of these behaviors in harsh communication environments is an open area of research. In this paper, we propose the use of a formal software engineering technique, statistical model checking, to model and assess the robustness of consensus-based behaviors from a communication standpoint. We validate our approach on two common scenarios for a robot swarm: the election of a leader and the allocation of a set of tasks. With the proposed model, we verify the functional correctness of these consensus-based algorithms, as well as assessing their robustness to communication loss and robot failures.

Signal Detection for Underwater IoT Devices With Long and Sparse Channels

Underwater acoustic communication often suffers from extended channel impulse response (CIR) and large Doppler spread such that signals become difficult to detect and decode. For the underwater Internet-of-Things (IoT) applications, the challenges are even bigger, because the IoT devices usually transmit very short messages due to severe power constraints, and the length of pilots are often shorter than that of CIR. Therefore, conventional pilot-assisted channel estimation and equalization approaches are incapable of detecting the information data. Moreover, the existing blind channel equalization algorithms, which do not require pilots, are not able to detect information data either, because the number of transmitted symbols is too small to approximate the expected loss with empirical loss, where the loss refers to as the error of estimated signal envelopes. In this article, a new equalization and decoding algorithm is proposed for the underwater IoT devices under harsh communication environments. Inspired by the recent blind deconvolution and compressive sensing techniques, we construct an optimization problem with the objective function rewarding sparsity of the estimated CIR using l4-norm and convexify the feasible set of the problem while guarantee the same solution. Then, we develop a pruned tree search initialization method and use gradient descent to find an optimal solution efficiently. The new algorithm is first verified by simulations, which show that the proposed algorithm outperforms conventional methods, such as the linear minimum mean square error (LMMSE) equalizer and a constant modulus algorithm (CMA). The proposed algorithm, along with a practical procedure for compensating large Doppler spread and carrier frequency offset, is further employed to process the real-world underwater IoT data collected in a fish-tag project. It shows that the proposed algorithm can equalize and detect the IoT data which were corrupted by channels whose lengths are longer than that of pilots, but the existing algorithms, such as LMMSE equalizer and CMA-based blind equalizer are not able to accomplish. It also shows that the proposed algorithm can provide a very impressive improvement compared to raw detection (no equalization or decoding) and decoding-only approaches.

The effect of region-based message selective delivery strategy on post-disaster emergency network

Stricken areas are shut off from the world, as large-scale infrastructures (e.g. bridges, roads and power equipments) have been destroyed after earthquakes, floods, and other disasters. Large-scale and cross-regional communication in the disaster area is difficult to achieve due to the harsh communication environment, such as unstable communication links and limited network resources, especially for remote isolated areas. Delay tolerant networks (DTNs) use the way of a “store-carry-forward” to transfer messages, which is suitable for the large transmission delay and intermittent link communication. In this paper, the DTNs based on regional center node and Unmanned Aerial Vehicle (UAV) is proposed to build the post-disaster emergency communication network. Further, a region-based message selective delivery routing policy is proposed for the emergency communication network. The received messages are classified according to its destination address at the regional center node and the UAV ferry node. In this way, the data packets can be accurately delivered to the corresponding area, and redundant data packets will be reduced in the network. The effect of the routing policy on network performance is evaluated. Simulation results show that the policy can effectively improve the data delivery rate, reduce the overhead ratio and significantly reduce the transmission delay.

Optimisation of delay tolerance in wireless sensor networks based on unscented Kalman filter estimation

Delay tolerance in wireless sensor network can be applied to complex and harsh communication environment. In order to improve the communication performance of delay tolerance in wireless sensor network, the optimisation of delay tolerance in wireless sensor network based on Unscented Kalman filter estimation is studied. Firstly, the model of delay tolerance in wireless sensor network is established according to the theory of dynamics and position constraints, and then an unscented Kalman filter estimation algorithm is used. Through analysing the basic state and measurement equation of delay tolerance in wireless sensor network model, the measurement equation of round-trip delay model is obtained. The pre handover time estimated by unscented Kalman filter is set, to effectively reduce the pre handover time and energy consumption, and optimise the delay wireless sensor network. The experimental results show that the delay tolerance of wireless sensor network optimised by the proposed method is within 30 ms under different observation noises, and the packet loss rate and energy consumption are low.

Harsh communication: characteristics of caregivers and persons with dementia

Objectives: While ways to reduce caregiver burden have dominated dementia care research, there is little understanding of daily communication and its relationship to caregiver burden and depression. In this study, we sought to: (1) describe the frequency of harsh communication used by caregivers; (2) examine the relationship between harsh communication, caregiver and person with dementia characteristics; and (3) determine the contributions of caregiver depression and burden on such communication.Method: Cross-sectional baseline data were drawn from 250 dyads, who participated in the Dementia Behavior Study (NCT01892579). Hierarchical linear regression models were used to examine the relationship between dyad characteristics and harsh communication scores (using the 6-item Negative Communication Scale), controlling for three groups of covariates: sociodemographic, relationship characteristics and health factors.Results: More than half of the caregivers (mean age = 65.4, 81.2% women, 45.6% spouses) reported they felt like screaming/yelling (N = 138, 55.2%) or used a harsh tone (N = 129, 51.6%) at persons with dementia (Mini Mental Status Examination mean = 14.3, SD: 7.8) at least sometimes. When controlling for all covariates, for each unit increase in caregiver burden, harsh communication increased by 0.486 units (p < 0.001); similarly, for each unit increase in caregiver depression, harsh communication increased by 0.301units (p < 0.001).Conclusion: Over half of dementia caregivers reported they felt like or used one or more harsh forms of communication. Caregiver burden and depression were incrementally associated with greater use of negative communication. Providing caregivers with knowledge, support and specific communication skills may lessen the frequency of harsh communication and possibly reduce burden and depression.

Flooding Message Mitigation of Wireless Content Centric Networking for Last-Mile Smart-Grid

In view of Smart-Grid architecture, wireless Last-Mile Network (LMN) devices as smart meters and intelligent home control machines are normally installed in harsh and lossy communication environment. In order to improve communication reliability of LMN, we proposed Wireless Topology Aware Content Centric Networking (TOP-CCN) protocol. TOP-CCN reduces channel access overhead of traditional Content Centric Networking and supports efficient multicast message transmission by using Multiple Point Relay (MPR), and Publisher MPR (PMPR). In addition, TOP-CCN LMN provides simple multi-hop forwarding scheme that can reduce the traditional routing control message overhead in multi-hop wireless LMN environment. The simulation result shows TOP-CCN can improve the service provisioning time and reliability compared to traditional IP based network model in LMN.

Designing an Image Encryption Scheme Based on Compressive Sensing and Non-Uniform Quantization for Wireless Visual Sensor Networks

Wireless visual sensor networks (WVSN) have been widely used to capture images in the fields of monitoring, intelligent transportation, and reconnaissance in recent years. Because of the wireless transmission mode and the huge amount of image data, major challenges in this application are frequent information stealing, big data problems, and harsh communication circumstances. Some encryption schemes based on compressive sensing (CS) and chaotic systems have been proposed to cope with these threats, but most of them are vulnerable against the chosen-plaintext attack (CPA). To remedy these defects, this paper designs a novel method based on non-uniform quantization (NQ). Then, in order to evaluate the true compression ratio (CR), our work takes into account limited data precision in cipher images, while most papers ignored this fact and calculated CR with the assumption of infinite data precision. Besides, to eliminate the periodic windows in the bifurcation diagram of the logistic map (LM), an optimized logistic map (OLM) is designed. Furthermore, simulation results prove that the performance of anti-jamming in the proposed cryptosystem is better than that in existing schemes under the condition of strong noise interference or severe data loss. In conclusion, the proposed method could improve the performance of security and anti-jamming for WVSN.

Compressed Sensing in Multi-Hop Large-Scale Wireless Sensor Networks Based on Routing Topology Tomography

Data acquisition from multi-hop large-scale outdoor wireless sensor network (WSN) deployments for environmental monitoring is full of challenges. This is because of the severe resource constraints on tiny battery-operated motes (e.g., bandwidth, memory, power, and computing capacity), the data acquisition volume from large-scale WSNs, and the highly dynamic wireless link conditions in outdoor harsh communication environments. We present a novel compressed sensing approach, which can recover the sensing data at the sink with high fidelity when a very few data packets need to be collected, leading to a significant reduction of the network transmissions and thus an extension of the WSN lifetime. Interplaying with the dynamic WSN routing topology, the proposed approach is both efficient and simple to implement on the resource-constrained motes without motes’ storing of any part of the random projection matrix, as opposed to other existing compressed sensing-based schemes. We further propose a systematic method via machine learning to find a suitable representation basis, for any given WSN deployment and data field, which is both sparse and incoherent with the random projection matrix in compressed sensing for data collection. We validate our approach and evaluate its performance using a real-world outdoor multi-hop WSN testbed deployment in situ . The results demonstrate that our approach significantly outperforms existing compressed sensing approaches by reducing data recovery errors by an order of magnitude for the entire WSN observation field while drastically reducing wireless communication costs at the same time.

Peran Komunikasi Ayah dalam Perkembangan Mental Anak: Studi atas Santri Putri Pondok Tahfidz Karanganyar

This article attempts to explore the role of father’s communication in a child's mental development. Using a descriptive qualitative approach, the data were collected by interviewing 10 informants at Pondok Tahfidz Karanganyar, then the data were analyzed by literature review. The results showed that father's communication to children is very important in forming the child's mental. In addition, harsh communication to the children will negatively affect the child's mental development, so they become testy, often moody, and difficult to socialize. The quality of father and child communication is influenced by several factors, such as education level and family economic condition. Thus, the father must pay attention to the quality of his communication in order to form a positive mentality to the child.Keywords:father, communication, child’s mental development