Intelligent Information Technology Research Articles

Status and Influential Factors of Intelligent Healthcare in Nursing Homes in China.

With the support of the Chinese government, nursing homes have increasingly adopted Internet and intelligent information technology to provide daily healthcare services to residents. However, no research has reported the status of intelligent healthcare in nursing homes. From September 2017 to May 2018, we conducted a survey of 197 nursing homes and collected information on their general characteristics, the intelligent healthcare services provided, the effectiveness of the application products used, and the attitudes of the staff and residents toward intelligent healthcare. Overall, 79.69% of the surveyed nursing homes have provided intelligent healthcare services, including medical care services (eg, chronic disease management and intelligent nursing) and daily life services (eg, fall monitoring and wireless positioning). Portable health monitoring devices and data management and service platforms are the most used healthcare products. The attitudes of staff probably affected the development of intelligent healthcare. Financial investment and the attitudes of staff and residents are factors that influence the effectiveness of the application of intelligent healthcare products in nursing homes. With the support of national policies, nursing homes have implemented primary intelligent healthcare. Stakeholders play pivotal roles in the provision of intelligent healthcare services.

Digitalization in Developing Maritime Business Environments towards Ensuring Sustainability

The paper focuses on assessing the level of digitalization in several developing maritime business environments in Albania, Bosnia and Herzegovina, Montenegro, and Serbia. The assessment has been done in reference to Holtham’s and Courtney’s Intelligent Information and Communication Technologies (ICT) Exploiter Model. The dimensions as maritime business system effectiveness, roles, and skills of information technology personnel, ladders of knowledge, ICT strategy, organizational culture, and manager’s mindset are analyzed. In addition, benchmarking with findings from developed maritime business environments in Croatia, Greece, Italy, and Slovenia, which belong to the European Union (EU), by using the same model, has been conducted. This is done with the aim to outline directions for improving the quality and speed of digitalization in non-EU countries, which have been functioning for decades in transitional conditions. The maritime ecosystem naturally has a tendency to be unique and to function smoothly as such. Alleviating the differences in the level and effectiveness of digitalization in developed and developing European countries is a path towards achieving this goal. By sharing their own expertise in the rational and intelligent use of ICT, developed EU countries can support developing non-EU countries towards ensuring sustainability in the entire European and worldwide maritime business ecosystem.

A summary of research progress on intelligent information processing methods for pregnant women's remote monitoring

The monitoring of pregnant women is very important. It plays an important role in reducing fetal mortality, ensuring the safety of perinatal mother and fetus, preventing premature delivery and pregnancy accidents. At present, regular examination is the mainstream method for pregnant women's monitoring, but the means of examination out of hospital is scarce, and the equipment of hospital monitoring is expensive and the operation is complex. Using intelligent information technology (such as machine learning algorithm) can analyze the physiological signals of pregnant women, so as to realize the early detection and accident warning for mother and fetus, and achieve the purpose of high-quality monitoring out of hospital. However, at present, there are not enough public research reports related to the intelligent processing methods of out-of-hospital monitoring for pregnant women, so this paper takes the out-of-hospital monitoring for pregnant women as the research background, summarizes the public research reports of intelligent processing methods, analyzes the advantages and disadvantages of the existing research methods, points out the possible problems, and expounds the future development trend, which could provide reference for future related researches.

Hybrid Physical Education Teaching and Curriculum Design Based on a Voice Interactive Artificial Intelligence Educational Robot

In order to promote the development of individualized, accurate and intelligent physical education teaching, combined with artificial intelligence technology, the current physical education teaching mode has been improved. Through the establishment of an artificial intelligence educational robot based on voice interaction, a hybrid physical education teaching mode is constructed to realize personalized education for students. First, the speech recognition system is designed from three aspects of speech recognition, interaction management and speech synthesis, and the accuracy of recognition is improved by algorithm. Second, a new mode of hybrid physical education teaching is constructed. Through intelligent information technology, the advantages of traditional physical education teaching are combined to improve the classroom efficiency of physical education teaching and personalized education ability for students. Finally, the relevant experimental scheme and questionnaire are designed, and the actual situation of an educational robot introduced into physical education teaching is investigated and evaluated. The results show that the recognition accuracy of the artificial intelligence speech recognition system can reach more than 90%. It can communicate well with students and answer students’ questions. An educational robot is introduced into physical education teaching, and students’ learning attitude and interest are evaluated. The results show that before and after the introduction of an educational robot in physical education teaching, the average score of students’ learning interest increases by 21 points, and the average score of learning attitude increases by 9.8 points. Therefore, the introduction of an artificial intelligence educational robot based on voice interaction in physical education teaching can help to improve the classroom efficiency of physical education teaching and students’ interest. This study provides a reference for the development of artificial intelligence teaching and promoting the development of artificial intelligence.

A Study on the Interconnection between National Disaster Management System and Private Disaster Prevention IT Technology through Application

In order to strengthen the disaster prevention phase and the management of social disasters, we will examine the plan of To-Be disaster management system interconnected by using intelligent information technologies such as IoT, Cloud, Big Data, Mobile and AI. The disaster management system can be upgraded by constructing an intelligent infrastructure based on Big Data analysis of the disaster signals before and after the disasters generated by private mobile and IoT. Big Data of disaster Signals can be customized to users in a timely manner through AI methodologies of supervised and unsupervised learning and reinforcement training. In the long term, it is expected that not only will the capacity of disaster response be improved, but the management ability centering on prevention will be enhanced as well.

MODELS AND PROCEDURES OF INTELLECTUAL TECHNOLOGY FOR FORMATION MULTI-GROUP TRAINS AND STREMLINE THE HETEROGENEOUS SEQUENCES OF ORDERS

Purpose. The article presents the mathematical models development of intellectual technology for the multi-group railway trains formation, as well as the transition to its generalization and the mathematical models formation of the organizing inhomogeneous order sequences logistical task. Method. The article proposes an approach to modeling the processes of multi-group trains disbandment-formation, as well as constructive processes of ordering sets of heterogeneous order sequences by means of the oriented graphs theory. There has been formed the improved structure of intelligent information technology for ordering order sequences, which uses knowledge base management procedures. Results. The article proposes new formulations of problems of ordering nondeterministic sequences, which differ due to the different complexity ("weight") of design operations. There is proposed A method for forming models of ordering processes based on the theory of oriented and weighted graphs. There is proposed To implement graphical models of ordering the sequences of elements, the use of parallel synchronous algorithms for scheduling flows in networks . There have been developed specialized metrics for ordering sequences, the use of which has allowed to implement the task of ordering sequences "by weight", as well as to build effective procedures for finding patterns in the knowledge bases of the processes of disbandment-formation of multi-group trains. Scientific novelty. For the first time, the task of ordering heterogeneous order sequences, as well as the task of dismantling and forming multi-group formations are presented by models on graphs - models of critical path and maximum flows of minimum cost. The indicators for determining the degree of ordering of sequences, as well as there have been improved the procedure for searching for analogues in knowledge bases. Practical significance. Representation of processes of ordering heterogeneous orders sequences and tasks of multi-group structures dismantling-formation by classical models of optimal planning on the basis of the graph theories allows to increase efficiency, performance and reliability of the corresponding planning processes. Intelligent information technology through the use of knowledge bases will reduce the cost of planning the multi-group railway trains disbandment and formation processes.

How to drive holistic end-to-end supply chain risk management

The constantly rising supply chain risk probabilities and increasingly negative performance impact on the supply chain force us to rethink and define an effective supply chain risk management approach. When a certain risk occurs, all internal and external stakeholders along the entire supply chain are affected. Therefore, it is essential to drive a holistic end-to-end supply chain risk management by setting up a dedicated supply chain risk management organisation with interfaces to all relevant business functions, by implementing an customised supply chain risk management process and by putting digital information technologies (eg artificial intelligence [AI]) in place in order to enable the process. The organisation builds a solid fundament and acceptance environment of the process implementation, while the process determines the strategic direction and scope of the information technologies selection. Only a clear vision, mission, strategy and roadmap can ensure and keep the enterprise-wide supply chain risk management programme running in the most efficient way. The systematic set-up of risk and business continuity management in the supply chain requires a sophisticatedly designed organisational structure and a comprehensive stakeholder management. An independent supply chain risk management organisation could be a recommended option in order to drive this strategic topic without any target conflicts between different business functions. The coverage and responsibility share between supply chain risk management and enterprise risk management must be aligned in order to use the existing enterprise-wide risk governance framework, methodology of risk quantification and risk management knowledge. A corporate supply chain risk management process defines a standard approach with roles and responsibilities and should cover the entire risk management cycle: identification, analysis and evaluation, treatment, monitoring and review. Both preventive and reactive supply chain risk management approaches should be considered and integrated as a complete concept. With advanced intelligent information technology, for example machine learning or risk management tools, the complete supply chain risk management process can be automated and digitalised. The process can be managed with minimum human effort and maximum benefit for the entire enterprise.

A Hybrid Method Based on Genetic Algorithm and Ant Colony System for Traffic Routing Optimization

TThis paper presents a hybrid method that combines the genetic algorithm (GA) and the ant colony system algorithm (ACS), namely GACS, to solve the traffic routing problem. In the proposed framework, we use the genetic algorithm to optimize the ACS parameters in order to attain the best trips and travelling time through several novel functions to help ants to update the global and local pheromones. The GACS framework is implemented using the VANETsim package and the real city maps from the open street map project. The experimental results show that our framework achieves a considerably higher performance than A-Star and the classical ACS algorithms in terms of the length of the global best path and the time for trips. Moreover, the GACS framework is also efficient in solving the congestion problem by online monitoring the conditions of traffic light systems.
 KeywordsTraffic routing; Ant colony system; Genetic algorithm; VANET simulator.
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Особливості автоматизації процесів вироблення рішень при оцінці повітряної обстановки на пунктах управління Повітряних Сил Збройних Сил України

У статті пропонується підхід по формалізації знань щодо розпізнавання дій повітряного противника з метою автоматизації процесів оцінки повітряної обстановки на пунктах управління Повітряних Сил з урахуванням невизначеності. В якості моделі представлення знань про процеси розпізнавання варіантів дій повітряного противника в умовах невизначеності, пропонується використовувати інтервальні нечіткі множини 2 порядку і засновані на них нечіткі логічні системи, що дозволяють в загальному випадку формалізувати задачі, що мають логіко-аналітичний характер.

Construction of hybrid intellectual monitoring and decision-making systems

The development of algorithms for constructing hybrid intelligent monitoring and decision-making systems, optimization of problem solving with fuzzy initial information, analysis of the correspondence model of complex difficult to formalize processes is considered. The main difference between the proposed development and the traditional ones is the use of modern intelligent information technologies for the development of algorithmic tools for constructing hybrid intelligent monitoring and decision-making systems.

Discussion on the remote visual control technology system of fully-mechanized heading face in mine

According to the present status of the intelligent and informational level of fully-mechanized heading face in mine, the remote visual control technology system of fully-mechanized heading face is put forward on the basis of the analysis of the working requirements of fully-mechanized heading face and the necessary intelligent information technology support for individual equipment and complete equipment of heading face. The six key technologies of complete equipment cooperative control, intelligent cutting, intelligent anchoring, intelligent transportation, working face vision, fault diagnosis and prediction are expounded. The present status and technical feasibility of fully-mechanized equipment are analyzed in detail, and the technical route of remote visual control of fully-mechanized heading face is defined. The problems that need to be innovated according to local conditions in the aspects of accessory materials transportation and environmental safety monitoring are put forward to realize the integration of the intelligent system. At present, through the remote visual control technology system, the goal of reducing people and increasing efficiency, safe operation and production data accumulation in fully-mechanized heading face has been achieved.

Human Being Emotion in Cognitive Intelligent Robotic Control Pt I: Quantum / Soft Computing Approach

The article consists of two parts. Part I shows the possibility of quantum / soft computing optimizers of knowledge bases (QSCOptKB™) as the toolkit of quantum deep machine learning technology implementation in the solution’s search of intelligent cognitive control tasks applied the cognitive helmet as neurointerface. In particular, case, the aim of this part is to demonstrate the possibility of classifying the mental states of a human being operator in on line with knowledge extraction from electroencephalograms based on SCOptKB™ and QCOptKB™ sophisticated toolkit. Application of soft computing technologies to identify objective indicators of the psychophysiological state of an examined person described. The role and necessity of applying intelligent information technologies development based on computational intelligence toolkits in the task of objective estimation of a general psychophysical state of a human being operator shown. Developed information technology examined with special (difficult in diagnostic practice) examples emotion state estimation of autism children (ASD) and dementia and background of the knowledge bases design for intelligent robot of service use is it. Application of cognitive intelligent control in navigation of autonomous robot for avoidance of obstacles demonstrated.

Rating algorithm development for assessing the effectiveness of the occupational health and safety management


 
 
 Purpose. The purpose of the article is development of a rating algorithm to assess the effectiveness of the occupational health and safety management system at electricity companies. The algorithm aims to determine the ranking scale of enterprises according to standardised safety indicators.
 Methodology. There is a certain level of uncertainty on the existing methods for providing and analysing statistical information on accidents, occupational hazards, occupational injuries and occupational diseases. Planning and management tasks are most often carried out when the necessary formal information is insufficient or uncertain. In addition to numerical statistics, information may include other, informal quantities that cannot be measured. Therefore, logical calculations with multivalued logic or ranking rules and investigate the invariance of selection rules for groups of transformations on a finite set of alternatives can be used to handle such knowledge. The formalisation of the ranking problem based on the Copeland method involves the construction of pairwise comparison tables for all formal safety indicators.Obtaining an assessment of the situation occurs with the use of a computer system and a decision support system, which increases the efficiency and accuracy of the assessment of the situation.
 Results. A formal apparatus for rating single-type enterprises to assess the effectiveness of the enterprise occupational health and safety management system in the have been developed using intelligent information technologies.
 Originality. Based on the Copeland method and the paired comparison method, a safety rating algorithm has been developed, the implementation of which makes it possible to assess the performance of the occupational safety and health system. The results have illustrated the competitive advantage of some enterprises over others and motivate management to take action to improve workplace safety.
 Practical value. Formalisation of information on hazardous and harmful occupational factors makes it possible to treat the subject area as a complex dynamic system, consisting of objects of a different nature, the totality of which determines the safety level. The developed rating method allows transferring the obtained results to decision-making support systems, illustrating competitive advantages of some enterprises over others, motivating management to take actions to improve occupational safety.
 
 

Application of Big Data in the Management System of “Second Classroom Education” Platform in Universities

Second classroom education, as an important part of expanding education, is an important part of the talent training program and an important way to reform the talent training model. With the advent of the era of big data, the second classroom education in colleges and universities uses the corresponding artificial intelligence model and information technology system, thereby greatly improving the management function of the second classroom education. This essay explains the importance of a “second classroom education” platform management system in the era of big data, and analyzes the current situation and problems of system management. It has been proved that the use of big data is helpful to guide and help college students to participate in the second classroom activities efficiently, so that the ability of college students is fully developed.

LEGAL REGULATION OF THE USE OF ARTIFICIAL INTELLIGENCE IN NOTARY AND CIVIL PROCESSES AS AN ELEMENT PROTECTION AND PROTECTION OF THE RIGHTS OF RESIDENTS (RESIDENTS) OF THE TEMPORARILY OCCUPIED TERRITORIES OF UKRAINE

The article considers the problem of application of artificial intelligence in the law of Ukraine in general and in the notarial and civil process in particular. The legal consequences of the legal regime of temporary occupation of some territories of Ukraine are indicated and the ways to eliminate obstacles in the protection and defense of the rights of citizens of Ukraine in these territories are determined. The legal construction of «artificial intelligence» is studied and its types are offered. The conclusion about the expediency of using intelligent computer programs, intelligent information technologies as types of artificial intelligence in notarial and executive processes is substantiated. It is proposed to consider the use of artificial intelligence in notarial and civil proceedings for citizens of Ukraine living in the Autonomous Republic of Crimea or in the occupied territories of Donetsk and Luhansk regions, within the limits, in the manner and in the manner prescribed by law of Ukraine. It is proved that the introduction of artificial intelligence through the mechanism of protection and defense of human and civil rights and freedoms in the civil process must be adapted to social relations that arise and exist, not violate the constitutional rights and freedoms of man and citizen in Ukraine and have a legal basis. Based on the scientific and practical analysis of the Civil Procedure Code of Ukraine, it is proposed for citizens of Ukraine living in the Autonomous Republic of Crimea or in the occupied territories of Donetsk and Luhansk regions to establish that lawsuits, separate and injunctive proceedings are entirely online. The procedure (procedure) and features of such proceedings with the use of various types of artificial intelligence (such as chatbots and other information intelligence technologies) should be defined in the Civil Procedure Code of Ukraine. It is noted that the introduction of the above mechanism to protect and defend the rights of citizens living in the Autonomous Republic of Crimea or in the occupied territories of Donetsk and Luhansk regions through intelligent computer programs will require proper maintenance and support of such programs to prevent leakage of information, leakage of personal data, etc. The conclusion is substantiated that e-litigation and remote notarial proceedings will increase the effectiveness of notarial and judicial forms of protection and protection of rights and make these state forms of protection more flexible, able to anticipate the peculiarities of procedural actions involving residents of the temporarily occupied territories.

An Extended Car-Following Model Considering the Drivers’ Characteristics under a V2V Communication Environment

In intelligent transportation systems, vehicles can obtain more information, and the interactivity between vehicles can be improved. Therefore, it is necessary to study car-following behavior during the introduction of intelligent traffic information technology. To study the impacts of drivers’ characteristics on the dynamic characteristics of car-following behavior in a vehicle-to-vehicle (V2V) communication environment, we first analyzed the relationship between drivers’ characteristics and the following car’s optimal velocity using vehicle trajectory data via the grey relational analysis method and then presented a new optimal velocity function (OVF). The boundary conditions of the new OVF were analyzed theoretically, and the results showed that the new OVF can better describe drivers’ characteristics than the traditional OVF. Subsequently, we proposed an extended car-following model by combining V2V communication based on the new OVF and previous car-following models. Finally, numerical simulations were carried out to explore the effect of drivers’ characteristics on car-following behavior and fuel economy of vehicles, and the results indicated that the proposed model can improve vehicles’ mobility, safety, fuel consumption, and emissions in different traffic scenarios. In conclusion, the performance of traffic flow was improved by taking drivers’ characteristics into account under the V2V communication situation for car-following theory.

Multiagency Modeling of Transformation Strategies Towards Sustainable Smart Cities

Given the relentless development of intelligent information and communication technology (ICT) systems, a growing need for cities to transform towards smart solutions and, on the other hand, a lack of firm methodological approaches to implement such transformations, the paper contributes to establishing a theory for modeling the transformation of cities towards sustainable, smart cities. The article presents the results of research: a model and a visualization method for supporting cities in elaborating and implementing transformation strategies. The authors’ experience is that intelligible, algorithmizable, and easily visualized models are being sought to assist city authorities in making informed decisions regarding the development of their cities. The paper proposes the concepts of the smartness zone and sustainability corridor, which allow one to devise and visualize the process of a city’s development and transformation in a simple, coherent, and comprehensible way, and to observe and monitor its development path. It presents a new generic instrument for modeling transformation strategies, which are the tools addressed to municipal authorities, analysts, and developers who can use them in order to design, implement, monitor, and optimize transformation strategies towards smart cities.

Genetic clustering algorithm

The genetic algorithm of clustering of analysis objects in different data domains has been offered within the hybrid concept of intelligent information technologies development aimed to support decision-making. The algorithm makes it possible to account for different preferences of the analyst in clustering reflected in a calculation formula of fitness function. The place of this algorithm among those used for cluster analysis has been shown. The algorithm is simple in its program implementation, which increases its usage reliability. The used technology of evolutionary modeling is rather expanded in the mentioned algorithm. Firstly, the decimal chromosomes coding is used instead of the traditional binary coding. This has resulted from the fact that the chromosome genes condition is multiple and not binary. Moreover, this is due to the absence of the genetic operator of inversion in this algorithm. Secondly, a new genetic operator used for filtering has been implemented. This operator eliminates chromosomes that do not meet the required clusters quantity condition in a task. Such chromosomes can appear in the stochastic process of their evolution. The presented algorithm has been studied in a series of simulation experiments. As a result, it has been found that stabilization of splitting into clusters is reached when the number of completed generations of evolution is 200 and more, and the population size is rather small: from 150 chromosomes (in this case no considerable amount of random-access store is required). The calculations carried out on real data showed for this algorithm the high quality of clustering and the acceptable computing speed of the same order with the computing speed of SOM and “k-means” algorithms.

Innovative approaches to manage entomophages production

Annotation Purpose. Improving the efficiency of entomophages production by developing innovative approaches for it management. Methods. System approach, intelligent information technologies. Results. Innovative approaches for it management of entomophages production have been developed, which consist of: determining and ranking the factors that have the greatest impact on the quality of entomological products, and factors that lead to substandard products; the creation of structural and parametric complexes for assessing product quality; real-time assessment of the intensity of entomocultures development processes; automation of management abiotic parameters stepwise development of insects (temperature and relative humidity of the box for growing of insects) in real time; determining the quality of entomological products in conditions of incomplete information, taking into account the impact of a combination of abiotic and biotic production parameters; calculation of optimal values of production parameters in conditions of uncertainty; systematization of knowledge about the interaction of heterogeneous parameters in the production of entomophages. Conclusions. The proposed innovative approaches to manage the production of entomophages can increase its efficiency by forming optimal management strategies, using the technological experience of specialists and modern intelligent information technologies in particular, SCADA-systems, fuzzy logic theory and cognitive analysis. Keywords: innovative approaches, production of entomophages, intelligent information technologies.

Research on Intelligent Informationization of Cigarette Processing and Production by Mes System

Cigarette processing and production process is essentially a production and implementation process, which has little difference with other production enterprises. With the deepening and development of information construction, the introduction of MES system makes the digitalization of new cigarette processing and production process further integrated and refined. The original production units have been scientifically organized through MES. But with the country’s encouragement of intelligent manufacturing and the stimulation of domestic and international environment, intelligent information technology has been put on the agenda. Different from MES, intelligent informatization pays more attention to production intelligence, big data application and Internet of things. Based on the information system constructed by MES, intelligent technology will make the cigarette processing and production process more efficient, and will directly bring value to cigarette enterprises.