Improve Information Processing Research Articles

Research on Recommendation Operation Strategy of News and Information Products

<p>For China’s news industry, personalized recommendation of news and information products is beginning to take off, but it is growing rapidly. Excess information content and limited time and energy of users urgently need common numbers to balance. It is not the ultimate goal to blindly provide users with instant news content as media. With the rising status of users, the times have higher requirements for media. In today’s society, improving information processing ability is more important than the speed of information dissemination. Users are forbidden to keep copper in the information cage. Repeated bloody, violent, misleading and other information are distressing. How to solve information overload for news and information product operators? How to adjust operation strategy from the perspective of users? How to solve the relationship between technical algorithm and manual intervention? How can personalized recommendation promote the development of news industry?</p>

Iterative heuristic design of temporal graphic displays with clinical domain experts.

Conventional electronic health record information displays are not optimized for efficient information processing. Graphical displays that integrate patient information can improve information processing, especially in data-rich environments such as critical care. We propose an adaptable and reusable approach to patient information display with modular graphical components (widgets). We had two study objectives. First, reduce numerous widget prototype alternatives to preferred designs. Second, derive widget design feature recommendations. Using iterative human-centered design methods, we interviewed experts to hone design features of widgets displaying frequently measured data elements, e.g., heart rate, for acute care patient monitoring and real-time clinical decision-making. Participant responses to design queries were coded to calculate feature-set agreement, average prototype score, and prototype agreement. Two iterative interview cycles covering 64 design queries and 86 prototypes were needed to reach consensus on six feature sets. Interviewers agreed that line graphs with a smoothed or averaged trendline, 24-h timeframe, and gradient coloring for urgency were useful and informative features. Moreover, users agreed that widgets should include key functions: (1) adjustable reference ranges, (2) expandable timeframes, and (3) access to details on demand. Participants stated graphical widgets would be used to identify correlating patterns and compare abnormal measures across related data elements at a specific time. Combining theoretical principles and validated design methods was an effective and reproducible approach to designing widgets for healthcare displays. The findings suggest our widget design features and recommendations match critical care clinician expectations for graphical information display of continuous and frequently updated patient data.

HMIC: Hierarchical Medical Image Classification, A Deep Learning Approach.

Image classification is central to the big data revolution in medicine. Improved information processing methods for diagnosis and classification of digital medical images have shown to be successful via deep learning approaches. As this field is explored, there are limitations to the performance of traditional supervised classifiers. This paper outlines an approach that is different from the current medical image classification tasks that view the issue as multi-class classification. We performed a hierarchical classification using our Hierarchical Medical Image classification (HMIC) approach. HMIC uses stacks of deep learning models to give particular comprehension at each level of the clinical picture hierarchy. For testing our performance, we use biopsy of the small bowel images that contain three categories in the parent level (Celiac Disease, Environmental Enteropathy, and histologically normal controls). For the child level, Celiac Disease Severity is classified into 4 classes (I, IIIa, IIIb, and IIIC).

Is There a Link between Stress and Cognition, and Capacity to Execute Motor Skill?

This study aimed to examine the link between stress (measured via salivary cortisol and testosterone), cognition (measured via pupillometry, with greater pupil constriction and reduced pupil constriction latency associated with increased attention and improved information processing), and motor skill capacity (measured via somatosensory processing). Twenty-five professional rugby players participated in this study. Saliva samples were collected upon waking, before pupillometry and somatosensory processing testing, and after testing. Testing times varied for participants; however, it was always in the morning, and the order of testing was randomized. Very small differences in hormone concentrations were seen across the morning (effect size = 0.01). Moderate to large differences in left eye pupil constriction for direct (left eye) versus consensual (right eye) stimulus were also seen (P < 0.01; effect size = 0.51 to 1.04). No differences for pupil constriction latency were seen for direct versus consensual stimulus. Some positive weak to moderate relationships were seen for testosterone and pupil constriction latency (r = 0.37 to 0.39, P < 0.05). Moderate to strong inverse relationships were seen for hormones with left eye pupil constriction difference between direct and consensual stimulus, and for pre- to posttest testosterone-to-cortisol ratio decline with left eye pupil constriction for direct and consensual stimulus (r = 0.41 to 0.52, P < 0.05). Weak to moderate inverse relationships for testosterone-to-cortisol ratio decline and somatosensory processing were seen (r = 0.36 to 0.47, P < 0.05). Stress may affect ability to receive information and ability to execute motor tasks. Thus, stress may compromise ability to make appropriate objective decisions and consequently execute skill/task behavior. Strategies to help mitigate negative stress responses are noted.

Effects of green supply chain integration and green innovation on environmental and cost performance

This paper argues that mechanisms such as information sharing and collaboration used in green supply chain integration (GSCI) to improve information processing capacity can reduce uncertain outcomes of green product and process innovation. Based on data from a survey of Chinese (Hong Kong) firms, the paper tests whether the three dimensions of GSCI (green internal, customer and supplier integration) improve environmental performance and cost reduction by facilitating green product and process innovation. The results show that green customer integration improves cost and environmental performance through green process innovation (not green product innovation). Both green product and process innovations are facilitated by green customer integration (not green supplier integration), while both green customer and supplier integration significantly depend on green internal integration. These suggest that the distinctive information processing capacity created by green internal and customer integration can facilitate the green process innovation required to improve environmental and cost efficiency, while green product innovation and green supplier integration cannot create such efficiencies.

Improving text summarization of online hotel reviews with review helpfulness and sentiment

Abstract The considerable volume of online reviews for today's hotels are is difficult for review readers to manually process. Automatic review summarizations are a promising direction for improving information processing of travelers. Studies have focused on extracting relevant text features or performing sentiment analysis to compile review summaries. However, numerous reviews contain nonspecific or nonsentimental content, hindering the ability of sentiment-based techniques' to accurately summarize useful information from hotel reviews. This paper proposes a systematic approach that first constructs classifiers to identify helpful reviews and then classifies the sentences in the helpful reviews into six hotel features. Finally, the sentiment polarities of sentences are analyzed to generate the review summaries. Experiment results indicated that the performance of the proposed approach was superior to other methods.

Cryptanalysis and Countermeasure of “An Efficient NTRU-based Authentication Protocol in IoT Environment”

A quantum computer is a paradigm of information processing that can show remarkable possibilities of exponentially improved information processing. However, this paradigm could disrupt the current cryptosystem, which is called quantum computing attacks, by calculating factoring problem and discrete logarithm problem. Recently, NTRU is applied to various security systems, because it provides security against to provide secu-rity against quantum computing attacks. Furthermore, NTRU provides similar security level and efficient computation time of encryption/decryption compared to traditional PKC. In 2018, Jeong et al. proposed an user authentication and key distribution scheme using NTRU. They claimed that their scheme provides various security properties and secure against quantum comput-ing attacks. In this paper, we demonstrate that their scheme has security pitfalls and incorrectness in login and authentication phase. We also suggest countermeasures to fix the incorrectness and provide security against various attacks.

A recursive learning technique for improving information processing through message classification in IoT–cloud storage

Processing and accessing distributed information is a prominent requirement for Internet of Things (IoT) in supporting business and consumer applications to improve accessibility. As the volume of information is being stored and processed is hefty, message classification is challenging in a mobile environment. This also results in prolonged processing delays and backlogs. In order to bridge the gap between message classification and request processing, this paper proposes a classification technique that operates on the basis of request-prioritized recursive learning for ease of message identification and service mapping. This learning technique predicts the type of information and its attributes through intensive learning and services them based on priority to minimize retrieval time. The priority of message servicing relies on the error obtained during the learning process. Despite an increasing number of user requests, attributes associated with each are bundled independently to provide an instant response. Prioritization accounts for the minimum number of error states while learning a message with different attributes to curtail prolonged response time. Error in the learning process is evaluated through a numerical analysis for different learning scenarios of the classified messages. The proposed learning-based access and retrieval technique were analyzed using the metrics of request backlogs, response time, caching delay, and the rate of utilization. The results of experiments verified the effectiveness of the proposed technique in terms of minimizing response time, backlogs, and caching delays, and improving utilization.

Spatiotemporal model of tripartite synapse with perinodal astrocytic process.

Information transfer may not be limited only to synapses. Therefore, the processes and dynamics of biological neuron-astrocyte coupling and intercellular interaction within this domain are worth investigating. Existing models of tripartite synapse consider an astrocyte as a point process. Here, we extended the tripartite synapse model by considering the astrocytic processes (synaptic and perinodal) as compartments. The scattered extrinsic signals in the extracellular space and the presence of calcium stores in different astrocytic sites create local transient [Ca2+]. We investigated the Ca2+ dynamics and found that the increase in astrocytic intracellular [Ca2+] enhances the probability of neurotransmitter release. However, the period in which the extrasynaptic glutamate lingers in the extracellular space may cause excitotoxicity. We propose further biological investigation on intercellular communication, considering that unconventional sources (nonsynaptic) of glutamate may improve information processing in neuron-astrocyte networks.

OGRU: An Optimized Gated Recurrent Unit Neural Network

Due to the structural problem, the traditional neural network models are prone to problems such as gradient explosion and over-fitting, while the deep GRU neural network model has low update efficiency and poor information processing capability among multiple hidden layers. Based on this, this paper proposes an optimized gated recurrent unit(OGRU) neural network.The OGRU neural network model proposed in this paper improves information processing capability and learning efficiency by optimizing the unit structure and learning mechanism of GRU, and avoids the update gate being interfered by the current forgetting information. The experiment uses Tensorflow framework to establish prediction models for LSTM neural network, GRU neural network and OGRU neural network respectively, and compare the prediction accuracy. The results show that the OGRU model has the highest learning efficiency and better prediction accuracy.

The impact of a volunteer-led community cancer awareness programme on knowledge of cancer risk factors and symptoms, screening, and barriers to seeking help

ObjectiveTo analyse the impact of a community cancer awareness programme on knowledge of cancer risk factors and symptoms, screening, and barriers to seeking help. MethodsPersonalised information through peer-led champions was delivered to 5500 people in a range of settings and Cancer Awareness Measures questionnaires were completed by 119 participants at pre-arranged sessions (convenience sampling) before and after the intervention. Data were analysed using McNemar tests, Mann-Whitney U test and a Wilcoxon Signed Rank test. ResultsData showed increase in knowledge after the intervention for cancer screening programmes (p < 0.05), recognition of warning signs for cancer (p < 0.05), and recognition of risk factors for cancer in seven of the eleven options (p < 0.001). Results suggest a decrease in perception of barriers to seeking help (p < 0.05). The intervention had a stronger impact on recognition of cancer symptoms for people who have been affected by cancer (p = 0.02). ConclusionThe Cancer Awareness Measures questionnaire proved an effective tool for evaluation and awareness improved after the intervention amongst those who completed it. Practice ImplicationsEnhancing the perceived personal relevance of information to those with experience of cancer may improve information processing and retention. The study highlights cancer awareness gaps among the public for future intervention development.

Preserved capacity for learning statistical regularities and directing selective attention after hippocampal lesions

Prior knowledge about the probabilistic structure of visual environments is necessary to resolve ambiguous information about objects in the world. Expectations based on stimulus regularities exert a powerful influence on human perception and decision making by improving the efficiency of information processing. Another type of prior knowledge, termed top-down attention, can also improve perceptual performance by facilitating the selective processing of relevant over irrelevant information. While much is known about attention, the mechanisms that support expectations about statistical regularities are not well-understood. The hippocampus has been implicated as a key structure involved in or perhaps necessary for the learning of statistical regularities, consistent with its role in various kinds of learning and memory. Here, we tested this hypothesis using a motion discrimination task in which we manipulated the most likely direction of motion, the degree of attention afforded to the relevant stimulus, and the amount of available sensory evidence. We tested memory-impaired patients with bilateral damage to the hippocampus and compared their performance with controls. Despite a modest slowing in response initiation across all task conditions, patients performed similar to controls. Like controls, patients exhibited a tendency to respond faster and more accurately when the motion direction was more probable, the stimulus was better attended, and more sensory evidence was available. Together, these findings demonstrate a robust, hippocampus-independent capacity for learning statistical regularities in the sensory environment in order to improve information processing.

Towards an integrated conceptual framework of supply chain finance: An information processing perspective

Based on a systematic review of SCF literature and the information processing theory, this paper builds an integrated conceptual framework to illustrate how SCF providers deal with uncertainties, develop capabilities and further achieve whole financial supply chain (SC) integration. It shows that uncertainties faced by SCF providers (including SCF task characteristics, SCF task environment and SCF task independence) delineate the information processing requirements. To meet these requirements, SCF providers could improve information processing capacity by enabling some mechanisms (i.e., organisation structure design, coordination and control, and information technology). The fit between SCF providers’ information processing requirements and capacity could further improve SCF capability, which would help to achieve integration of the whole financial SC. Building on this framework, seven future research directions are provided.

Properties of Entanglement between the JC Model and Atom-Cavity-Optomechanical System

We investigate the dynamics of remote entanglement in the system consisting of a Jaynes-Cummings model and an atom-cavity-optomechanical system. Meanwhile, we find that the remote entanglement is related to the initial entanglement degree between two atoms, the coupling strength between atom and cavity. Moreover, the phenomenon of entanglement sudden death appears in the evolution of entanglement for some initial conditions. By investigating the entanglement transfer among two atoms and cavity 1, we show that the entanglement transfer can be realized at some special time. In particular, we evaluate the tripartite entanglement of the two atoms and cavity 1 through π-tangle, and prepare the larger tripartite entanglement. This implementation of tripartite entanglement might provide a potential way to realize improved information processing and distributed quantum computing.

Salivary levels of alpha-amylase are associated with neurobehavioral alertness during extended wakefulness, but not simulated night-shift work

Sleep loss is one of the most common causes of accidents and errors in operational environments. Currently, no single method satisfies all of the requisite criteria of an effective system for assessing the risk of injury prior to safety being compromised. Research has concentrated towards the development of a biomarker for individualized assessment of sleepiness-related deficits in neurobehavioral alertness, with salivary alpha-amylase (sAA) recently reported as a potential biomarker during acute total sleep deprivation. The present study extends on previous research by investigating the association between sAA and neurobehavioral alertness during simulated night-shift work, during individuals are required to work at night when biological processes are strongly promoting sleep and sleep during the day when endogenous processes are promoting wakefulness.In a laboratory-controlled environment, 10 healthy non-shift working males aged 24.7 ± 5.3 years (mean ± SD) underwent four consecutive nights of simulated night-shift work. Between 17:30–04:30 h participants provided saliva samples and completed a 3 min psychomotor vigilance test (PVT-B), 40 min simulated driving task, and 3 min digit symbol substitution test (DSST). Higher sAA levels were associated with faster response speed on the PVT-B, reduced lane variability on the simulated driving task, and improved information processing speed on the DSST during the first night-shift. There were no associations between sAA levels and performance outcomes during subsequent night-shifts. Findings indicate that the usability of sAA to assess the risk of neurobehavioral deficits during shift-work operations is limited. However, the robust circadian rhythm exhibited by sAA during the protocol of circadian misalignment suggests that sAA could serve as a potential circadian marker.

Working memory affine technological support functions improve decision performance

While working memory limits constrain the complexity of manageable tasks, technological devices offer vast information processing capacity and thus the potential to improve individual information processing capabilities and task performance. We explored the effects of providing individuals with intuitive, working memory affine information structuring support functionalities on a multi-touch table on decision performance. In the employed hidden profile personnel selection task (Stasser & Titus, 1985) support should enable participants to offload cognitive processing, thus improving information processing and decision quality. In Experiment 1 (N = 76) we compared decision performance without vs. with technological support (self-directed and automatic structuring functionalities). Support led to higher chances for a correct decision, more appropriate candidate suitability ratings and better information recognition compared to no support. In Experiment 2 (N = 81) we focused on self-directed structuring, comparing conditions with vs. without detailed usage instructions for self-structuring functionalities. While there was no difference with regard to decision quality, participants displayed more appropriate candidate suitability ratings and better recognition performance with detailed usage instructions than without. Our findings indicate that offering working memory affine technological support functions to ameliorate cognitive limitations is effective and highlight that detailed instructions might amplify this potential.

Blog Folio in Blended Learning: a Development of Students’ Information Processing Skills in Digital Age

Paradigm shift in educational context support to instructional innovation, such as online learning, blended learning, and mobile learning. Researcher implemented the blended learning by using blog as portfolios for students. The purpose in this research was to identify the effects of using a blog in blended learning to improve collage student’s information processing skill in virtual environment. The facilitation given to college students in order to familiar with through search, collect, manages, and communicates information in digital age. Research subject is collage students in Development of Innovation Instructional Model course on period January-June 2017 at Educational Technology in Universitas Negeri Padang. This research used three instruments, consist of 1) the rubrics for identify information processing skill, 2) questionnaire for using blog folio, and 3) interview guided about advantages, challenges and obstacles to use a blog in blended learning. The result show that using blog folio can help collage students to improved information processing skills because they understood and tried the steps of that skill. Furthermore, they admitted by using blog folio can increased motivation, participation and give advantages.

IPlasticity: Induced juvenile-like plasticity in the adult brain as a mechanism of antidepressants.

The network hypothesis of depression proposes that mood disorders reflect problems in information processing within particular neural networks. Antidepressants (AD), including selective serotonin reuptake inhibitors (SSRI), function by gradually improving information processing within these networks. AD have been shown to induce a state of juvenile‐like plasticity comparable to that observed during developmental critical periods: Such critical‐period‐like plasticity allows brain networks to better adapt to extrinsic and intrinsic signals. We have coined this drug‐induced state of juvenile‐like plasticity ‘iPlasticity.’ A combination of iPlasticity induced by chronic SSRI treatment together with training, rehabilitation, or psychotherapy improves symptoms of neuropsychiatric disorders and issues underlying the developmentally or genetically malfunctioning networks. We have proposed that iPlasticity might be a critical component of AD action. We have demonstrated that iPlasticity occurs in the visual cortex, fear erasure network, extinction of aggression caused by social isolation, and spatial reversal memory in rodent models. Chronic SSRI treatment is known to promote neurogenesis and to cause dematuration of granule cells in the dentate gyrus and of interneurons, especially parvalbumin interneurons enwrapped by perineuronal nets in the prefrontal cortex, visual cortex, and amygdala. Brain‐derived neurotrophic factor (BDNF), via its receptor tropomyosin kinase receptor B, is involved in the processes of synaptic plasticity, including neurogenesis, neuronal differentiation, weight of synapses, and gene regulation of synaptic formation. BDNF can be activated by both chronic SSRI treatment and neuronal activity. Accordingly, the BDNF/tropomyosin kinase receptor B pathway is critical for iPlasticity, but further analyses will be needed to provide mechanical insight into the processes of iPlasticity.

The role of uncertainty in performance information disclosure

PurposeThe purpose of this paper is to investigate the relationship between the environmental uncertainty faced by public administrations and their likelihood of disclosing performance information, particularly at municipal level.Design/methodology/approachThe existence of the relationship between environmental uncertainty and performance information disclosure is explored, drawing on organizational information processing theory. The paper describes an empirical quantitative investigation in a sample of 490 Italian municipalities.FindingsMunicipalities facing more uncertainty are more likely to disclose performance information. There is no unique set of factors that can explain the difference in the disclosure activity of Italian municipalities, but this activity appears to be contingent on the level of environmental uncertainty.Originality/valueThe paper explores the under-investigated field of factors influencing the disclosure of performance information by public administrations. It identifies uncertainty as one of the determinants of performance information disclosure. The findings suggest that the use of theories and variables not previously used in this type of study can improve understanding of the phenomenon. The study also suggests that public officials should consider adequate enforcement mechanisms to promote performance information disclosure, especially for organizations with lower incentives to improve information processing capabilities.

Perspective-Taking, Information Processing and Workplace Verbal Abuse: A Bangladesh Factory Manager Field Experiment

A randomized controlled trial analyzing perspective-taking on processing information concerning verbal abuse was conducted with factory managers in 16 Bangladesh factories. Managers’ modal perception of the prevalence of verbal abuse was inconsistent with worker reports, indicating managers’ resistance to acknowledging verbal abuse. Perspective-taking improved information processing but the response was heterogeneous. Acknowledgement of the prevalence of verbal abuse increased only in those managers for whom there was consonance between personal beliefs and the data. Among managers who engaged with the exercise or viewed verbal abuse as inappropriate, treatment increased interest in and willingness to make changes based on the data.