Thread Communication Research Articles

Extracting informational cues between initial coin offering projects and the public

AbstractAn initial coin offering (ICO) seeks to raise initial investments for companies by selling crypto tokens to individuals interested in crowdfunding. As ICOs have gained popularity, a lack of information regarding startup companies' prior financial status and business health has led to information asymmetry between potential investors and ICO projects. This study explores the informational cues necessary to bridge this gap. Employing signaling theory, we elucidate the presence of information asymmetry and conduct two case analyses to identify relevant informational cues. Twitter data from two ICO projects (Stratis and NEO), which achieved the highest return on investment at the time of data collection, are extracted and analyzed to identify informational themes. Our findings reveal multiple and distinctive themes of informational cues for each ICO project, demonstrating that transmitted signals vary across different stages and are generated by both the coin publisher and the public. This research illuminates the flow of informational cues between ICO initiators and potential investors on social media. By analyzing online communication threads using qualitative methods, this study significantly contributes to the understanding of information asymmetry in the context of ICOs.

Challenges and Opportunities to the Flow of Communication: Online Focus Groups with Parents of Young Children, Professional Caregivers, and Intermediaries

To explore the information behavior in the context of child injury prevention, we conducted online focus groups with parents, professional caregivers, and intermediaries as part of a larger project. In this paper, we discuss our qualitative interview design: audiovisual, synchronous online focus groups. To do so, we analyze a crucial methodological issue of focus group interviews: the flow of communication. In our study, three main topics emerged that influenced the flow of communication in online focus groups: (a) communication mode(s), (b) (co-)moderation, and (c) distractions and interjections of other people. We conclude that depending on the research topic and target group, audio-only communication may be advantageous compared to audiovisual communication because lay people may disclose more on sensitive topics. Moreover, the considerate composition of the focus group is essential for participants’ interaction, so that all participants feel they have an important part to contribute to the discussion. Skilled co-moderation is crucial to successfully integrating all participants and evolving communication threads, and dealing with disruptions.

A Software-Defined Distributed Architecture for Controlling Unmanned Swarm Systems

An unmanned swarm is usually composed of a group of homogeneous or heterogeneous hardware platforms, software control systems, and interfaces for human–computer interaction that operate collectively to achieve a specific goal by information interaction. They exhibit robustness and fault tolerance when facing complex missions, making it crucial in military, transportation, intelligent traffic, and other fields. However, the coupling between the hardware and software of a heterogeneous unmanned swarm can indeed have significant implications for system flexibility, software development and deployment, and hardware maintenance. Over the years, there has been a significant shift from traditional hardware-focused control systems to a greater emphasis on the core software layer. In this paper, a distributed network architecture is proposed to solve this problem, in which hardware resources are abstracted and represented to accomplish standardization and unification by defining a consistent and uniform set of data formats, and a resource pool of hardware data is constructed to realize the function that the number and scale of platforms is irrelevant, the task module can be plug-and-play at any time, and the software can be configured on demand. The resource scheduling of a single platform is achieved through process and thread communication using shared memory, while the resource scheduling of a cross platform is achieved through a network using request and response and subscription and notification. As a result, it can satisfy the development of functional modules in a software-defined mode and gradually improve the intelligence capability of an unmanned swarm. Based on the above architecture, the overall framework of the autonomous navigation system and the collaborative control system has been successfully established. Finally, a hardware-in-the-loop simulation environment is constructed, and the integration and verification of the proposed distributed architecture is carried out by the cooperative formation experiment, which proves the feasibility of this proposal.

Synchronous Deterministic Parallel Programming for Multi-Cores with ForeC

Embedded real-time systems are tightly integrated with their physical environment. Their correctness depends both on the outputs and timeliness of their computations. The increasing use of multi-core processors in such systems is pushing embedded programmers to be parallel programming experts. However, parallel programming is challenging because of the skills, experiences, and knowledge needed to avoid common parallel programming traps and pitfalls. This article proposes the ForeC synchronous multi-threaded programming language for the deterministic, parallel, and reactive programming of embedded multi-cores. The synchronous semantics of ForeC is designed to greatly simplify the understanding and debugging of parallel programs. ForeC ensures that ForeC programs can be compiled efficiently for parallel execution and be amenable to static timing analysis. ForeC’s main innovation is its shared variable semantics that provides thread isolation and deterministic thread communication. All ForeC programs are correct by construction and deadlock free because no non-deterministic constructs are needed. We have benchmarked our ForeC compiler with several medium-sized programs (e.g., a 2.274-line ForeC program with up to 26 threads and distributed on up to 10 cores, which was based on a 2.155-line non-multi-threaded C program). These benchmark programs show that ForeC can achieve better parallel performance than Esterel, a widely used imperative synchronous language for concurrent safety-critical systems, and is competitive in performance to OpenMP, a popular desktop solution for parallel programming (which implements classical multi-threading, hence is intrinsically non-deterministic). We also demonstrate that the worst-case execution time of ForeC programs can be estimated to a high degree of precision.

Product-part level digital twin modeling method for digital thread framework

Digital twin (DT) is not only a core technology of smart manufacturing but also a dynamic intelligent system. By organically combining virtual and realistic models with multiple data sources, DT is used in monitoring product operation status and in predicting product life. A systematic modeling method with high fidelity, punctuality, and efficiency has an important meaning to DT model. However, most of the current DT modeling approaches focus on individual objects and individual aspects of products, and lack of modeling approaches for the whole life cycle and multiple objects, which is not conducive to the mining and utilization of data from all aspects of products. On account of this, a part-level DT modeling approach is proposed based on PLM/PDM theory, integrating the property model, the process model, the simulation model, and the feedback model within a digital thread communication framework, with their modeling methods and application algorithms investigated separately. The results of the Part Digital Twin Model (PDTM) are presented by virtue of a visualization platform. There is interaction among customers, designers, and processors throughout the entire system, ensuring real-time monitoring of product manufacturing process. Finally, a test case of hanging axle is implemented, aiming at validating the proposed part-level DT modeling method. According to the result of this case, the proposed method in this paper can be used in generating the property of hanging axle, and giving real-time monitoring to the whole lifecycle of hanging axle, thereby demonstrating its feasibility.

The principles of building a parallel program for steganographic file protection

In the modern era, the unprecedented growth of data and its consequential demands on transmission and storage systems have highlighted the necessity for efficient and secure information processing mechanisms. This paper delves into the potential of steganography as a robust tool for ensuring confidentiality by embedding data covertly within other files. Recognizing the limitations of traditional steganographic techniques in the face of expansive contemporary data sets, the paper explores the amalgamation of parallel programming with steganographic processes. Such a fusion promises to distribute computational tasks effectively, thereby reducing the overall execution time. Detailed discussions underscore the significance of data decomposition, process synchronization, and thread coordination, illustrating how parallel algorithms can markedly expedite concealed data embedding and extraction. However, inherent challenges like minimizing thread communication, optimizing shared data access, and preventing race conditions are brought to the fore. Solutions are proposed through diverse methods, tools, and design strategies aimed at streamlining workload distribution and enhancing task execution. In conclusion, the paper emphasizes that blending steganography with parallel programming can potentially revolutionize data protection systems, with continual refinements in techniques and methods driving the domain towards offering more potent solutions for electronic data confidentiality and security.

Evaluation of WhatsApp as a Platform for Teledermatology in Botswana: Retrospective Review and Survey.

In emerging market countries in sub-Saharan Africa, access to specialty services such as dermatology is limited. Teledermatology is an innovative solution to address this issue; however, many initiatives have been tried without sustained success. Recently, WhatsApp has been used as a store-and-forward telemedicine communication platform for consultation and education in Botswana. This study aims to describe the utilization of WhatsApp for teledermatology and the satisfaction levels of participating providers. A 2-part pilot study was conducted. First, a retrospective review was performed of WhatsApp communications received by participating dermatologists in Gaborone, Botswana, from January 2016 to December 2019. Sender information, patient demographics and history, response time, diagnoses made, and follow-up recommendations were collected. Second, a 12-question cross-sectional survey was distributed to health care providers who utilized WhatsApp for teledermatology during this period. Descriptive statistics were then performed. There were 811 communication threads over the study period. The majority (503/811, 62%) of communications were consultations from providers inquiring about a specific patient, followed by multidisciplinary care coordination communications (90/811, 11%). Our in-depth analysis focused on the former. In 323 (64%) provider consultations, dermatologists responded within 1 hour. A diagnosis was made in 274 (55%) consultations. Dermatologists gave treatment recommendations remotely in 281 (56%) consultations and recommended an in-person dermatology visit in 163 (32%). Of the 150 health care providers surveyed, 23 (15%) responded. All respondents (100%) felt that there was a need for teledermatology and improved teledermatology education in Botswana. Moreover, 17 (74%) respondents strongly felt that the guidance received via WhatsApp was high quality, and 22 (96%) were satisfied with WhatsApp as a platform for teledermatology. This retrospective review and survey demonstrated that WhatsApp is a quick, well-received, and sustainable method of communication between dermatologists and providers across Botswana. The app may offer a solution to the challenges providers face in accessing specialty referral systems, point-of-care education, and medical decision-making support for complex dermatologic cases in Botswana. The information gained from this pilot study can serve as the basis for future telemedicine studies to improve the implementation of teledermatology in Botswana and other resource-limited countries.

Accelerating distributed deep neural network training with pipelined MPI allreduce

TensorFlow (TF) is usually combined with the Horovod (HVD) workload distribution package to obtain a parallel tool to train deep neural network on clusters of computers. HVD in turn utilizes a blocking Allreduce primitive to share information among processes, combined with a communication thread to overlap communication with computation. In this work, we perform a thorough experimental analysis to expose (1) the importance of selecting the best algorithm in MPI libraries to realize the Allreduce operation; and (2) the performance acceleration that can be attained when replacing a blocking Allreduce with its non-blocking counterpart (while maintaining the blocking behaviour via the appropriate synchronization mechanism). Furthermore, (3) we explore the benefits of applying pipelining to the communication exchange, demonstrating that these improvements carry over to distributed training via TF+HVD. Finally, (4) we show that pipelining can also boost performance for applications that make heavy use of other collectives, such as Broadcast and Reduce-Scatter.

Predicting the Soft Error Vulnerability of Parallel Applications Using Machine Learning

With the widespread use of the multicore systems having smaller transistor sizes, soft errors become an important issue for parallel program execution. Fault injection is a prevalent method to quantify the soft error rates of the applications. However, it is very time consuming to perform detailed fault injection experiments. Therefore, prediction-based techniques have been proposed to evaluate the soft error vulnerability in a faster way. In this work, we present a soft error vulnerability prediction approach for parallel applications using machine learning algorithms. We define a set of features including thread communication, data sharing, parallel programming, and performance characteristics; and train our models based on three ML algorithms. This study uses the parallel programming features, as well as the combination of all features for the first time in vulnerability prediction of parallel programs. We propose two models for the soft error vulnerability prediction: (1) A regression model with rigorous feature selection analysis that estimates correct execution rates, (2) A novel classification model that predicts the vulnerability level of the target programs. We get maximum prediction accuracy rate of 73.2% for the regression-based model, and achieve 89% F-score for our classification model.

Crowdsourcing in a Pandemic: Pearls and Pitfalls From the Trainee Experience.

Crowdsourcing in a Pandemic: Pearls and Pitfalls From the Trainee Experience.

SUBLIMINAL MESSAGES - MOTIVATING LEARNERS USING VISUAL CUES: AN EXPERIMENTAL STUDY

Subliminal messages have grown into a contentious practice getting a bad reputation in coercive advertising and progressed towards psycholinguistic communication threads over the years. The current studies investigate how priming techniques using visual cues can change learning and motivate learners. In two phases of the experimental study, the visual system of subliminal messages was exposed to three age groups: children, teens, and adults. Results on both phases show an improvement in memory reception among the children’s group. These results corroborate the effectiveness of subliminal stimulus on human beings’ minds and decision-making. The subliminal message can be used as a medium for memory improvements empowering learners to reach their goals in education. Future research projects should explore well-defined aural and visual tools used for teaching and measure the effectiveness of such powerful tools. Keywords: Subliminal messages, motivate, learners, experiment, mass media, education

50 Million Followers Can’t Be Wrong, or Can They? The Influence of Social Media on CEO Communication

The rise of social media introduces new ways in which executives communicate and receive feedback on their words and actions. Social media feedback is generated quickly in large volumes with a format that discourages in-depth critical feedback (e.g., availability of only “like” option), from partly unknown (and unknowable) and heterogeneous sources. In this paper, I theorize and test how long-term exposure to social media feedback influences the communication patterns of CEOs. Through applying novel machine learning methods on 820,000 communication threads of CEOs from S&P 1500, I found that long-term exposure to aggregate social media feedback increases the frequency and affective tone of communication. The relationship is moderated by recent textual feedback. These findings have important implications for the literature on CEO communications and feedback.

Characterizing communication patterns among members of the clinical care team to deliver breast cancer treatment.

Research to date focused on quantifying team collaboration has relied on identifying shared patients but does not incorporate the major role of communication patterns. The goal of this study was to describe the patterns and volume of communication among care team members involved in treating breast cancer patients. We analyzed 4 years of communications data from the electronic health record between care team members at Vanderbilt University Medical Center (VUMC). Our cohort of patients diagnosed with breast cancer was identified using the VUMC tumor registry. We classified each care team member participating in electronic messaging by their institutional role and classified physicians by specialty. To identify collaborative patterns, we modeled the data as a social network. Our cohort of 1181 patients was the subject of 322424 messages sent in 104210 unique communication threads by 5620 employees. On average, each patient was the subject of 88.2 message threads involving 106.4 employees. Each employee, on average, sent 72.9 messages and was connected to 24.6 collaborators. Nurses and physicians were involved in 98% and 44% of all message threads, respectively. Our results suggest that many providers in our study may experience a high volume of messaging work. By using data routinely generated through interaction with the electronic health record, we can begin to evaluate how to iteratively implement and assess initiatives to improve the efficiency of care coordination and reduce unnecessary messaging work across all care team roles.

Study on progress threads placement and dedicated cores for overlapping MPI nonblocking collectives on manycore processor

To amortize the cost of MPI collective operations, nonblocking collectives have been proposed so as to allow communications to be overlapped with computation. Unfortunately, collective communications are more CPU-hungry than point-to-point communications and running them in a communication thread on a dedicated CPU core makes them slow. On the other hand, running collective communications on the application cores leads to no overlap. In this article, we propose placement algorithms for progress threads that do not degrade performance when running on cores dedicated to communications to get communication/computation overlap. We first show that even simple collective operations, such as those based on a chain topology, are not straightforward to make progress in background on a dedicated core. Then, we propose an algorithm for tree-based collective operations that splits the tree between communication cores and application cores. To get the best of both worlds, the algorithm runs the short but heavy part of the tree on application cores, and the long but narrow part of the tree on one or several communication cores, so as to get a trade-off between overlap and absolute performance. We provide a model to study and predict its behavior and to tune its parameters. We implemented both algorithms in the multiprocessor computing framework, which is a thread-based MPI implementation. We have run benchmarks on manycore processors such as the KNL and Skylake and get good results for both performance and overlap.

Refactoring Java Programs for Customizable Locks Based on Bytecode Transformation

Developers of parallel programming are faced with choices of using various Java locks. Choosing the best lock is a challenging task because a multithreaded application implemented using different locks may end up with uncertain performance. There is a strong need for automated tool support that helps Java programmers choose the best lock for each specific application. This paper presents an automated transformation approach to convert an implementation using a synchronized lock to a ReentrantLock or a ReentrantReadWriteLock at the bytecode level. For the ReentrantLock, our approach runs analysis for global monitors using the visitor pattern in the Joeq compiler. For the ReentrantReadWriteLock, a read or write lock is chosen after a side-effect analysis. Then, the proposed system validates the consistency of the analysis results to ensure a correct sequence of lock usage. Finally, lock operations and related thread communication operations are transformed into a ReentrantLock or a ReentrantReadWriteLock using a bytecode transformation framework Javassist. We validate our approach on several benchmarks including RBTree, PC, SPECjbb2005, and HSQLDB. The experimental results show that the proposed automated transformation approach can transform these benchmarks successfully in a timely fashion.

GPU acceleration of a petascale application for turbulent mixing at high Schmidt number using OpenMP 4.5

This paper reports on the successful implementation of a massively parallel GPU-accelerated algorithm for the direct numerical simulation of turbulent mixing at high Schmidt number. The work stems from a recent development (Comput. Phys. Commun., vol. 219, 2017, 313–328), in which a low-communication algorithm was shown to attain high degrees of scalability on the Cray XE6 architecture when overlapping communication and computation via dedicated communication threads. An even higher level of performance has now been achieved using OpenMP 4.5 on the Cray XK7 architecture, where on each node the 16 integer cores of an AMD Interlagos processor share a single Nvidia K20X GPU accelerator. In the new algorithm, data movements are minimized by performing virtually all of the intensive scalar field computations in the form of combined compact finite difference (CCD) operations on the GPUs. A memory layout in departure from usual practices is found to provide much better performance for a specific kernel required to apply the CCD scheme. Asynchronous execution enabled by adding the OpenMP 4.5 NOWAIT clause to TARGET constructs improves scalability when used to overlap computation on the GPUs with computation and communication on the CPUs. On the 27-petaflops supercomputer Titan at Oak Ridge National Laboratory, USA, a GPU-to-CPU speedup factor of approximately 5 is consistently observed at the largest problem size of 81923 grid points for the scalar field computed with 8192 XK7 nodes.

Encrypted Jihad: Investigating the Role of Telegram App in Lone Wolf Attacks in the West

The study aims to capture links between the use of encrypted communication channel -Telegram and lone wolf attacks occurred in Europe between 2015-2016. To understand threads of ISIS communication on Telegram we used digital ethnography approach which consists of the self-observation of information flows on four of ISIS’s most celebrated telegram Channels. We draw on public sphere theory and coined the term terror socio-sphere 3.0 as the theoretical background of this study. The collected data is presented as screenshots to capture a visual evidence of ISIS communication threads. This study shows that ISIS Telegram channels play critical role in personal communication between potential recruits and dissemination of propaganda that encourage ‘lone wolves’ to carry attacks in the world at large. This study was limited to the number of the channels that have been widely celebrated.

Stateless model checking with data-race preemption points

Stateless model checking is a powerful technique for testing concurrent programs, but suffers from exponential state space explosion when the test input parameters are too large. Several reduction techniques can mitigate this explosion, but even after pruning equivalent interleavings, the state space size is often intractable. Most prior tools are limited to preempting only on synchronization APIs, which reduces the space further, but can miss unsynchronized thread communication bugs. Data race detection, another concurrency testing approach, focuses on suspicious memory access pairs during a single test execution. It avoids concerns of state space size, but may report races that do not lead to observable failures, which jeopardizes a user’s willingness to use the analysis. We present Quicksand, a new stateless model checking framework which manages the exploration of many state spaces using different preemption points. It uses state space estimation to prioritize jobs most likely to complete in a fixed CPU budget, and it incorporates data-race analysis to add new preemption points on the fly. Preempting threads during a data race’s instructions can automatically classify the race as buggy or benign, and uncovers new bugs not reachable by prior model checkers. It also enables full verification of all possible schedules when every data race is verified as benign within the CPU budget. In our evaluation, Quicksand found 1.25x as many bugs and verified 4.3x as many tests compared to prior model checking approaches.

The design of the intelligent parking system for urban business districts

A parking management system needs to be designed to improve the efficiency of the management of parking lots in urban business districts that witness difficult parking. In this paper, the overall design of an intelligent parking system is expounded, the architecture of which includes the PXA270 master control platform, ZigBee network, the remote communication section and Android software; the LCD interface circuit is stated and the design philosophy for the analogue camera circuit is described. Meanwhile, the functions of the parking-space detection module and the vehicle identification unit are explained, and the structure diagram of the software in the intelligent parking system is put forward. Also, the design philosophies for the gate control unit and the GPRS communication program are expounded, a detailed definition of the control frame of the gate module is given, the flow charts of the parking-space status detection procedure and the vehicle identification procedure are presented, and the server of the Android system and the software design for the client are described. Furthermore, the flow chart of the network communication thread is put forward, in which data is transferred between the server and the client, the interface design for the intelligent parking system is realized, the display of the system’s main interface is presented, and the parking-space reservation interface and the function of entry guiding animation are realized.

The value of literature in introducing performance studies

ABSTRACTAs Oral Interpretation broadened into Performance Studies, some introductory performance classes abandoned teaching performance of literature for more contemporary theory and practice. However, the shape of the course at Louisiana State University has held firm for decades. This essay theorizes the pedagogy of the "Introduction to Performing Literature" course at Louisiana State University. It provides a historical overview of the scholarship that shaped the philosophy of the course, describes the assignments in the current course (taking into consideration how those assignments accommodate innovations or trends in performance studies), and argues that the enduring shape of the course places it in relationship to the other communication areas represented in the department, emphasizes the communication thread in performance studies, and develops students to be better citizens by encouraging nuanced, empathetic, and critical performances of a broad array of literary texts.