Improving the Effectiveness of Image Classification Structural Methods by Compressing the Description According to the Information Content Criterion

The research aims to improve the performance of image recognition methods based on a description in the form of a set of keypoint descriptors.The main focus is on increasing the speed of establishing the relevance of object and etalon descriptions while maintaining the required level of classification efficiency.The class to be recognized is represented by an infinite set of images obtained from the etalon by applying arbitrary geometric transformations.It is proposed to reduce the descriptions for the etalon database by selecting the most significant descriptor components according to the information content criterion.The informativeness of an etalon descriptor is estimated by the difference of the closest distances to its own and other descriptions.The developed method determines the relevance of the full description of the recognized object with the reduced description of the etalons.Several practical models of the classifier with different options for establishing the correspondence between object descriptors and etalons are considered.The results of the experimental modeling of the proposed methods for a database including images of museum jewelry are presented.The test sample is formed as a set of images from the etalon database and out of the database with the application of geometric transformations of scale and rotation in the field of view.The practical problems of determining the threshold for the number of votes,based on which a classification decision is made,have been researched.Modeling has revealed the practical possibility of tenfold reducing descriptions with full preservation of classification accuracy.Reducing the descriptions by twenty times in the experiment leads to slightly decreased accuracy.The speed of the analysis increases in proportion to the degree of reduction.The use of reduction by the informativeness criterion confirmed the possibility of obtaining the most significant subset of features for classification,which guarantees a decent level of accuracy.

Unlocking the Potential:A Comprehensive Systematic Review of ChatGPT in Natural Language Processing Tasks

As Natural Language Processing(NLP)continues to advance,driven by the emergence of sophisticated large language models such as ChatGPT,there has been a notable growth in research activity.This rapid uptake reflects increasing interest in the field and induces critical inquiries into ChatGPT’s applicability in the NLP domain.This review paper systematically investigates the role of ChatGPT in diverse NLP tasks,including information extraction,Name Entity Recognition(NER),event extraction,relation extraction,Part of Speech(PoS)tagging,text classification,sentiment analysis,emotion recognition and text annotation.The novelty of this work lies in its comprehensive analysis of the existing literature,addressing a critical gap in understanding ChatGPT’s adaptability,limitations,and optimal application.In this paper,we employed a systematic stepwise approach following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)framework to direct our search process and seek relevant studies.Our review reveals ChatGPT’s significant potential in enhancing various NLP tasks.Its adaptability in information extraction tasks,sentiment analysis,and text classification showcases its ability to comprehend diverse contexts and extract meaningful details.Additionally,ChatGPT’s flexibility in annotation tasks reducesmanual efforts and accelerates the annotation process,making it a valuable asset in NLP development and research.Furthermore,GPT-4 and prompt engineering emerge as a complementary mechanism,empowering users to guide the model and enhance overall accuracy.Despite its promising potential,challenges persist.The performance of ChatGP Tneeds tobe testedusingmore extensivedatasets anddiversedata structures.Subsequently,its limitations in handling domain-specific language and the need for fine-tuning in specific applications highlight the importance of further investigations to address these issues.

Enlightenment and Suggestions on the Construction of Information Platform and Processing Mechanism of Drug Shortages in Developed Countries to China

Objective To study how to improve and perfect the information platform and processing mechanism of drug shortages in China.Methods By searching the relevant policies from official websites of FDA,European Medicines Agency(EMA),Health Canada(HC)and National Health Commission,the good experience of the United States,the European Union and Canada in the construction of information platform and processing mechanism of drug shortages was summarized for reference in China.Results and Conclusion China has initially established the processing mechanism of drug shortages,but the platform construction should be improved,and the information disclosure of drug shortages varies from province to province.We should improve the information platform of drug shortages,strengthen the disclosure and communication of information,enrich the processing tools and measures after the drug shortages occurs,and strengthen the cooperation with relevant associations and other non-governmental departments.

Investigation of system structure and information processing mechanism for cognitive skywave over-the-horizon radar

Based on the cognitive radar concept and the basic connotation of cognitive skywave over-the-horizon radar（SWOTHR）, the system structure and information processingmechanism about cognitive SWOTHR are researched. Amongthem, the hybrid network system architecture which is thedistributed configuration combining with the centralized cognition and its soft/hardware framework with the sense-detectionintegration are proposed, and the information processing framebased on the lens principle and its information processing flowwith receive-transmit joint adaption are designed, which buildand parse the work law for cognition and its self feedback adjustment with the lens focus model and five stages informationprocessing sequence. After that, the system simulation andthe performance analysis and comparison are provided, whichinitially proves the rationality and advantages of the proposedideas. Finally, four important development ideas of futureSWOTHR toward ＂high frequency intelligence information processing system＂ are discussed, which are scene information fusion, dynamic reconfigurable system, hierarchical and modulardesign, and sustainable development. Then the conclusion thatthe cognitive SWOTHR can cause the performance improvement is gotten.

Research on the Processing Methods of the Computer Format Information Flow in the Network English Translation System

The development o f the network technology, and especially the web search engine, has brought great changes to the field of the English translation. Translators can acquire the background information of the translated texts by using the web search engine correctly, inquire about the correct translation methods of the rare professional terms, apply the fixed sentence patterns, and check the correctness of the translation, so as to improve the translation speed and quality.

How to Improve Listening Skills——in Light of the Information Processing Theory

Using Gagne's information processing theory to analyze the listening process so as to provide a pedagogical model for L2 learners to solve listening problems as well as to cast some lights on listening teaching.

Application of Information Processing Theory in Second Language Vocabulary Acquisition

Vocabulary acquisition is an intricate process,which has a close relationship with memory.In cognitive psychology,a large number of studies on memory system have been conducted based on the information processing theory,placing great value on second language learners’cognitive process.This study intends to probe into second language vocabulary acquisition from the perspective of information processing theory in hope to help learners acquire vocabulary more scientifically and efficiently.

Construction and Practice of Online Course Resources Based on Information Processing Theory:Taking“A Bite of Teochew Cuisine,”a Guangdong First-Class Course,as an Example

“Cantonese Cuisine Master”project is an important policy proposed by China to inherit Cantonese Cuisine culture,promote employment,and achieve targeted poverty reduction and rural revitalization.Confronted with the demands of more diverse education,it is an essential opportunity and task for the education system to consider how to construct high-quality online courses and pursue higher-quality“Cantonese Cuisine Master”projects in line with the new era.This paper,based on the theory of instructional media and information processing theory,will further clarify the demand,dilemma,and developing strategy of online course construction for culinary majors,and explore its construction and practice with the example of“A Bite of Teochew Cuisine,”a Guangdong first-class course.

Self-Frustration of Expectations in Major Depressive Disorder: The Syncytiopathy Hypothesis of Depression Revisited

This paper is a further elaboration of my model of the pathophysiology of major depressive disorder focusing on imbalances of glial-neuronal interactions in tripartite synapses and the glial network (syncytium). Basically, it is proposed that the connexin proteins building gap junctions in the glial syncytium are underexpressed or dysfunctional in major depression, called syncytiopathy. As a compensatory effect the astrocytic receptors in tripartite synapses are overexpressed. This leads to protracted synaptic information processing because of a relative lack of neurotransmitter substances for the occupancy of astrocytic receptors. Based on a new biophysical formal description of astrocytic receptors as expectation variables it can be shown that the protracted processing of sensory information frustrate the full comprehension of the expected event, since it cannot be grasped in time. Moreover, expectation frustration may stress the glial syncytium aggravating memory impairment. This cyclic process of dysbalanced synaptic information processing is characterized as self-frustration of expectations explanatory for the main cognitive dysfunctions in major depression as slowing down processing speed, deficits in attention and working memory. The main result of the study is that patients with major depression cannot fully acknowledge the existence of an intended event.

Application of graph neural network and feature information enhancement in relation inference of sparse knowledge graph

At present,knowledge embedding methods are widely used in the field of knowledge graph(KG)reasoning,and have been successfully applied to those with large entities and relationships.However,in research and production environments,there are a large number of KGs with a small number of entities and relations,which are called sparse KGs.Limited by the performance of knowledge extraction methods or some other reasons(some common-sense information does not appear in the natural corpus),the relation between entities is often incomplete.To solve this problem,a method of the graph neural network and information enhancement is proposed.The improved method increases the mean reciprocal rank(MRR)and Hit@3 by 1.6%and 1.7%,respectively,when the sparsity of the FB15K-237 dataset is 10%.When the sparsity is 50%,the evaluation indexes MRR and Hit@10 are increased by 0.8%and 1.8%,respectively.

Physicochemical Properties and Health Risks of Informal E-Waste Processing at Alaba International Market in Lagos, Nigeria

This study investigated the groundwater quality and health risks associated with informal e-waste processing in the Alaba International Market in Lagos, Nigeria. Twenty-two groundwater samples were collected from hand-dug wells in the market area and analyzed for physicochemical properties and heavy metal concentrations. The results showed that the groundwater quality was poor, with high levels of heavy metals, including cadmium, lead, and chromium. The health index (HI) for children and adults was above the tolerable threshold levels, indicating a potential health risk to the population. Principal component analysis and hierarchical cluster analysis were used to identify the sources of metals in groundwater, and the results showed that informal e-waste processing was a significant source of contamination. The study highlights the need for effective management strategies to mitigate the potential health risks associated with informal e-waste processing and ensure public health and environmental safety.

A Device to Improve Collaborative Practices of Sanitation Department Agents of a Territory: The Case of the Lamkansa District in Casablanca

The aim of this article is to strengthen and improve the collaboration between professional agents of a service that manages one of the technical processes acting on a given territory by synchronizing the spatio-temporal dimensions including all agents assembled for the task. This proposal was tested in the Lamkansa neighborhood in Casablanca, Morocco. The employed approach is based GIS resources and on systemic analysis of communication present in a territory. We were inspired by several methodological developments that carried multi-actor processes in land use planning. We focused our work on strengthening the collaboration between professionals, field agents and office agents, in the process of design and monitoring the liquid sanitation system. The device is based on geolocation and synchronous feedback of topological, geographical, and multimedia data related to the liquid sanitation network. Thanks to a geo-collaborative, participative, and motivating logic, we reduced the management costs of the network and made it faster and more efficient by equally mobilizing another type of non-specialized actors (the inhabitants). This device uses spatial and temporal dimensions to consolidate collaborative work tools through ICT and GIS technologies that thematize and exchange information collected in the field. Furthermore, this device raises great interest as it entails the concept of integration of several actors in a geo-collaborative mode while combining geomatics with communication and information sciences.

^(23)Na relaxometry: An overview of theory and applications

^(23)Na is a nuclear magnetic resonance(NMR)-active isotope with a nuclear spin quantum number of 3/2.^(23)Na relaxation phenomenon is at the core of ^(23)Na NMR measurement and analysis.Due to the dominance of quadrupolar interaction,the relaxation behavior of ^(23)Na is physically and mathematically more complex than that of a typical spin-1/2 isotope.In this review,we overview the semi-classical Redfield theory for deriving the formulations of ^(23)Na relaxation.We show that the relaxation behaviors of ^(23)Na can be quantitatively described by constructing the spectral density functions based on the second-order perturbation theory.In addition,we summarize the applications of ^(23)Na relaxometry in different research fields,including biomedicine,sodium ion batteries,and quantum information processing.Because sodium is an essential element in our body,food and industrial materials,the research on sodium by ^(23)Na NMR emerges as important future directions.The theoretical and practical understandings on ^(23)Na relaxation are the step stones for mastering advanced ^(23)Na NMR techniques.

The Classification to Stationary Process of Tidal Motion Observed at the Time of Kuroshio’s Meandering

The tide level displays information about the state of the sea current and the tidal motion. The tide level of the southern coast of Japan Island is affected strongly by Kuroshio Current flowing in the western part of North Pacific Ocean. When Kuroshio takes the straight path and flow along the Japan Islands, the tide level increases, and it is calculated from two tide level data observed at Kushimoto and Uragami in the southern part of Kii Peninsula. In contrast, the tide level decreases at the time when Kuroshio leaves from the Japan Islands. In this paper, the hourly tidal data are analyzed using the Autocorrelation Function (ACF) and the Mutual Information (MI) and the phase trajectories at first. We classify the results into 5 types of tidal motion. Each categorized type is investigated and characterized precisely using the mean tide level and the unit root test (ADF test) next. The frequency of the type having unstable tidal motion increases when the Kuroshio Current is non-meandering or in a transition state or the tide level is high, and the type shows a non-stationary process. On the other hand, when the Kuroshio Current meanders, the tidal motion tends to take a periodical and stable state and the motion is a stationary process. Though it is not frequent, we also discover a type of stationary and irregular tidal motion.

Data processing of small samples based on grey distance information approach

Data processing of small samples is an important and valuable research problem in the electronic equipment test. Because it is difficult and complex to determine the probability distribution of small samples, it is difficult to use the traditional probability theory to process the samples and assess the degree of uncertainty. Using the grey relational theory and the norm theory, the grey distance information approach, which is based on the grey distance information quantity of a sample and the average grey distance information quantity of the samples, is proposed in this article. The definitions of the grey distance information quantity of a sample and the average grey distance information quantity of the samples, with their characteristics and algorithms, are introduced. The correlative problems, including the algorithm of estimated value, the standard deviation, and the acceptance and rejection criteria of the samples and estimated results, are also proposed. Moreover, the information whitening ratio is introduced to select the weight algorithm and to compare the different samples. Several examples are given to demonstrate the application of the proposed approach. The examples show that the proposed approach, which has no demand for the probability distribution of small samples, is feasible and effective.

Using the Analytical Hierarchy Process Model in the Prioritization of Information Assurance Defense In-Depth Measures?—A Quantitative Study

Organizational computing devices are increasingly becoming targets of cyber-attacks, and organizations have become dependent on the safety and security of their computer networks and their organizational computing devices. Business and government often use defense in-depth information assurance measures such as firewalls, intrusion detection systems, and password procedures across their enterprises to plan strategically and manage IT security risks. This quantitative study explores whether the analytical hierarchy process (AHP) model can be effectively applied to the prioritization of information assurance defense in-depth measures. In response to these threats, the President, legislators, experts, and others have characterized cyber security as a pressing national security issue. The methods used in this study consisted of emailing study participants a survey requesting that they prioritize five defense in-depth information assurance measures, anti-virus, intrusion detection, password, smart-cards, and encryption, with a range of responses from 1 - 5 using a Likert scale to consider standard cost, effectiveness, and perceived ease of use in terms of protection of organizational computing devices. The measures were then weighted, based on ranking. A pair-wise comparison of each of the five measures is then made using AHP to determine whether the Likert scale and the AHP model could be effectively applied to the prioritization of information assurance measures to protect organizational computing devices. The findings of the research reject the H0 null hypothesis that AHP does not affect the relationship between the information technology analysts’ prioritization of five defense in-depth dependent variables and the independent variables of cost, ease of use, and effectiveness in protecting organizational devices against cyber-attacks.

The Combination Operator of Information Sources by a New Expressive Matrix

The multi-sensors fusion refers to the synergistic combination of sensory data from multiple sensors to provide more accurate and reliable information. The potential benefits of the Fusion are multi-sensors’ redundancy and extra information acquired. The fusion of redundant information can reduce the overall uncertainty and thus helps to provide information specified more precisely. Several sensors providing redundant information can also be used to increase reliability in the case of error, omission or failure of sensors. The combination operators are exponential and are more complex in terms of calculation;the Dempster-Shafer operator is exponential for more than three (3) information sources?[1] [2]. Our work focuses on the definition of another formulation of this operation, and puts it in a matrix form to illuminate the computational complexity, more precision guaranty and a minimal execution time. We propose to use each information source in a form of a matrix, which contains 0 value in lines that do not contain the masses (m(Ai) = 0) or once m(Ai) is not null (m(Ai) ≠ 0). The use of this expressed matrix attempts to ameliorate Dempster-Shafer operator via initialing either a criterion or criteria sources’ solution, increasing the efficiency of the Dempster-Shafer operator and facilitates the combination among the sources. We evaluate our approach by conducting a case study for showing the effectiveness of this matrix.

Possible roles of electrical synapse in temporal information processing: A computational study

Temporal information processing in the range of tens to hundreds of milliseconds is critical in many forms of sensory and motor tasks. However, little has been known about the neural mechanisms of temporal information processing. Experimental observations indicate that sensory neurons of the nervous system do not show selective response to temporal properties of external stimuli. On the other hand, temporal selective neurons in the cortex have been reported in many species. Thus, processes which realize the temporal-to-spatial transformation of neuronal activities might be required for temporal information processing. In the present study, we propose a computational model to explore possible roles of electrical synapses in processing the duration of external stimuli. Firstly, we construct a small-scale network with neurons interconnected by electrical synapses in addition to chemical synapses. Basic properties of this small-scale neural network in processing duration information are analyzed. Secondly, a large-scale neural network which is more biologically realistic is further explored. Our results suggest that neural networks with electrical synapses functioning together with chemical synapses can effectively work for the temporal-to-spatial transformation of neuronal activities, and the spatially distributed sequential neural activities can potentially represent temporal information.

Mobile Technology and Dissemination of Information in the Kenyan Insurance Industry

It is estimated that only 15 percent of Kenyans have made plans for retirement, and many people fall into poverty once they retire. A 2018 survey by the Unclaimed Property Asset register found that insurance companies hold 25 percent of unclaimed funds with 10 percent belonging to pensioners. This was attributed to a lack of effective information flow between insurance companies and the customers and also between various departments in the insurance companies. Further, there were numerous cases of loss of documents and files and certain files were untraceable in the departments. This paper investigates ways in which mobile technology influences dissemination of information for processing pension claims in the insurance industry. An improvement in dissemination of information for processing of pension claims can carry out a key function in increasing percentage of Kenyans making plans for retirement. The study deployed a descriptive study design. The target population in this study was 561 pensioners in Jubilee Insurance and 8 heads of pensions business, finance, legal services, internal audit, operations, information and communication technology, actuary, business development and strategy and business development departments. The sample size of this study was obtained by use of Krejcie and Morgan formula of determining sample size. As a result of the small number of heads of departments, they were not sampled. Through systematic sampling a sample of 288 pensioners was selected from the list of pensioners in Jubilee Insurance. The findings from the study led to a conclusion that mobile application has a positive and significant association with dissemination of information for pension claims processing in Jubilee Insurance. It was further revealed that text messages have a positive and significant influence on dissemination of information. Concerning unstructured supplementary service data (USSD) it was concluded that it has a positive and significant influence on dissemination of information. The study findings also revealed that voice calls have a positive and significant influence on dissemination of information for pension claims processing in Jubilee Insurance.

Optimal Size for Maximal Energy Efficiency in Information Processing of Biological Systems Due to Bistability

Energy efficiency is closely related to the evolution of biological systems and is important to their information processing. In this work, we calculate the excitation probability of a simple model of a bistable biological unit in response to pulsatile inputs, and its spontaneous excitation rate due to noise perturbation. Then we analytically calculate the mutual information, energy cost, and energy efficiency of an array of these bistable units. We find that the optimal number of units could maximize this array＇s energy efficiency in encoding pulse inputs, which depends on the fixed energy cost. We conclude that demand for energy efficiency in biological systems may strongly influence the size of these systems under the pressure of natural selection.