Problems For Further Research Research Articles

Eco-oriented management accounting system as a tool for sustainable functioning of an economic entity

Modern challenges of a global nature, as well as dependence on environmental impacts, dictate the need to determine environmental costs for economic entities, as well as account, analyze and control them. In this regard, the system of environmental management accounting is one of the tools that ensure the sustainable functioning of the enterprise. The article examines the categorical apparatus of an eco-oriented management accounting system in order to study the presented topic. The paper propose a system of information support for environmental management accounting for the purpose of improving environmental safety and leveling existing environmental risks. The main objects of environmental management accounting are identified and the reflection of payments in the environmental sphere on a separate account with the necessary level of detail for the effective functioning of the system is justified. The paper also formulates problems for further research of the environmental management accounting system using advanced achievements and practices in the world scientific arena.

«Сохранение лица» — цель или средство? Социально-психологические характеристики концепции лица

Background. The concept of “face” appeared in scientific discourse in the middle of the last century and has since been used by researchers in the fields of communication studies, linguistics and psychology. Such a diversified approach to the study of this phenomenon leads to a number of disagreements in the understanding of its main characteristics and functions. The relevance of this review lies in the systematic analysis of face and facework, highlighting it as an independent subject of study and formulating problems for further research. Objective. The purpose of this article is to analyze the relationship between the concepts of “identity”, “self-presentation” and “face”, as well as to identify the main characteristics and features of the process of saving face from the socio-psychological point of view. Methods. Systemic and subjective approaches, comparative analysis method. Results. “Face” is defined as a universal phenomenon of the individual and relational levels that cannot be considered independently of the object and context of communication. In addition, special attention is paid to the consideration of this concept as a component of intercultural communication. New research directions are outlined. Conclusions. For further study of “face”, one needs a more detailed understanding of the factors influencing the face concerns and facework at the individual, situational and cultural levels. In addition, the concept of “face” can be viewed as a component of intercultural communicative competence.

The maximum [formula omitted]-spectral radius and the majorization theorem of [formula omitted]-uniform supertrees

Let α be a real number with 0≤α<1, G be a uniform hypergraph, and Aα(G)=αD(G)+(1−α)A(G), where D(G) and A(G) are the diagonal degree tensor and the adjacency tensor of G, respectively. The spectral radius of Aα(G) is called the α-spectral radius of G. In this paper, some properties for the α-spectral radius of connected k-uniform hypergraphs are investigated, the unique k-uniform supertree with the largest α-spectral radius among all k-uniform supertrees with a given degree sequence is characterized, and the majorization theorem for k-uniform supertrees is obtained. By applying the majorization theorem, we determine the k-uniform supertrees obtaining the three largest α-spectral radius among all k-uniform supertrees with n vertices, give a new proof ordering the eight largest spectral radius among all k-uniform supertrees with n vertices, propose an open problem for further research, and characterize the unique k-uniform supertree with the largest α-spectral radius among all k-uniform supertrees with given different parameters, e.g., the maximum degree △, or the number of pendent vertices.

A Conservative Negation Extension of Positive Semilattice Logic Without the Finite Model Property

In this article, I present a semantically natural conservative extension of Urquhart’s positive semilattice logic with a sort of constructive negation. A subscripted sequent calculus is given for this logic and proofs of its soundness and completeness are sketched. It is shown that the logic lacks the finite model property. I discuss certain questions Urquhart has raised concerning the decision problem for the positive semilattice logic in the context of this logic and pose some problems for further research.

Graph neural network

In recent years, with the emergence of massive data, graph structure data that can represent complex relationshipsbetween objects has received more and more attention and has brought great challenges to existing algorithms.As a deep topology information can be revealed, graph neural network models have been widely used in many fields such as communication,life sciences, and finance. This paper reviews the basic models, algorithms, applications and recent developments of existing graph neuralnetworks in recent years, and proposes problems for further research.

Subspace packings: constructions and bounds

The Grassmannian $\mathcal{G}_q(n,k)$ is the set of all $k$-dimensional subspaces of the vector space $\mathbb{F}_q^n$. K\"{o}tter and Kschischang showed that codes in Grassmannian space can be used for error-correction in random network coding. On the other hand, these codes are $q$-analogs of codes in the Johnson scheme, i.e., constant dimension codes. These codes of the Grassmannian $\mathcal{G}_q(n,k)$ also form a family of $q$-analogs of block designs and they are called subspace designs. In this paper, we examine one of the last families of $q$-analogs of block designs which was not considered before. This family, called subspace packings, is the $q$-analog of packings, and was considered recently for network coding solution for a family of multicast networks called the generalized combination networks. A subspace packing $t$-$(n,k,\lambda)_q$ is a set $\mathcal{S}$ of $k$-subspaces from $\mathcal{G}_q(n,k)$ such that each $t$-subspace of $\mathcal{G}_q(n,t)$ is contained in at most $\lambda$ elements of $\mathcal{S}$. The goal of this work is to consider the largest size of such subspace packings. We derive a sequence of lower and upper bounds on the maximum size of such packings, analyse these bounds, and identify the important problems for further research in this area.

Climate indicators of changes in hydrological characteristics (a case of the Psyol river basin)

Formulation of the problem. A national climate program, complying with the Association Agreement between Ukraine and the EU, is aimed at long-term adaptation measures to climate change, providing for the development of legislation in the field of environmental protection, sectoral strategies, improving air and water quality. These measures require identification of climatic factors’ impact on hydrological characteristics of water bodies in any area in order to protect and improve them, as well as a comprehensive approach to the rational management of water resources. Analysis of previous research. Using mathematical models of atmospheric circulation allows us to obtain generalized calculations of the average global and regional air temperature, characterized by significant errors in case of different models. Problems of further research. Modern changes in climatic conditions in Ukraine are characterized by locality and rapidity: increasing number of anomalous atmospheric phenomena, frequency of droughts, dry winds which, according to preliminary estimates, may lead to reduction of water resources, changes in internal annual redistribution of water temperature and runoff against the background of increasing thermal resources of the territory. The purpose. The article analyses climatic indicators’ influence on the main hydrological characteristics on the example of the Psyol river basin within Ukraine. Research methods. Research methods are presented by statistical and cartographic analysis (correlation analysis method). The initial information is the results of observations contained in the State Climate Cadastre and the State Water Cadastre for the Dnieper Valley. Presentation of the main research material. Analysis of climate change in the Psyol river basin indicates a decrease in water consumption, both in the main river of the basin and in its main tributaries. In addition to changes in temperature and humidity, the reasons for this process were the shifts that occurred in the nature of the intra-annual distribution of the runoff. During the late XX – early XXI century the share of spring floods decreased due to the reduced period of ice phenomena and corresponding decrease in the thickness of the snow cover on the rivers. As a result, the most important component of the annual runoff of rivers began to decrease rapidly. The role of groundwater in the formation of water runoff increased against the background of a predominant decrease in precipitation. This is especially true for medium-size and small rivers, subject to significant anthropogenic pressure: over-regulation of channels, creation of artificial lakes, their shallowing. Practical value. Based on the main provisions of the national environmental policy of Ukraine on the use of water resources and the implementation of European principles of the Water Framework Directive 2000/60 / EC (ERVD) the study of changes in hydrological regime of rivers is of practical importance for sustainable management. Research results. The study of the impact of changes in climatic indicators on hydrological characteristics makes it possible to determine the reference conditions and classes of ecological status of rivers under conditions of anthropogenic pressure against the background of further changes in climatic indicators that will have different trends.

Vehicle Vision Robust Detection and Recognition Method

With the rapid growth of the global economy, the global car ownership is also increasing year by year, which has caused a series of problems, the most prominent of which is traffic congestion and traffic accidents. In order to solve the traffic problem, all countries are actively studying the intelligent transportation system, and one of the important research contents of the intelligent transportation system is vehicle detection. Vehicle detection based on vision is to capture vehicle images in the driving environment through a camera, and then use computer vision recognition technology for vehicle detection and recognition. Although computer vision recognition technology has made great progress, how to improve the detection accuracy of the image to be detected is still an important content of visual recognition technology research. Intelligent vehicle visual robust detection and identification of methods of research to reduce the growing incidence of traffic accidents, improve the existing road traffic safety and transportation efficiency, alleviate the degree of driver fatigue problem are of great significance. This paper considers the intelligent vehicle environmental awareness of the key technology to the goal of robust detection and recognition based on machine vision problems for further research. The particle filter is used to extract the local energy of the image to realize the fast segmentation of the region of interest (ROI). In order to further verify the ROI, a measure learning method based on multi-core embedding is proposed, and the semantic classification of ROI is realized by integrating the color, shape and geometric features of ROI. Experimental results show that the algorithm can effectively eliminate false sexy ROI interest, and the algorithm is robust to complex background, illumination changes, perspective changes and other conditions.

A Device-to-System Perspective Regarding Self-Heating Enhanced Hot Carrier Degradation in Modern Field-Effect Transistors: A Topical Review

As foreseen by Keyes in the late 1960s, the self-heating effect has emerged as an important concern for device performance, output power density, run-time variability, and reliability of modern field-effect transistors. The self-heating effect is aggravated as the device footprint scales down for higher level of integration (low-power devices) or as the devices are operated in ultrahigh voltage regimes (high-power devices). In this article, we focus on the implications of self-heating on hot carrier degradation (HCD) of modern transistors by integrating within a coherent theoretical framework a broad range of experimental data scattered in the literature. We explain why system integration exacerbates transistor self-heating, while high-frequency digital operation ameliorates it, suggesting an opportunity for co-optimization. We conclude this article by discussing the various material–device–system design strategies to reduce HCD and suggesting open problems for further research.

Exponents of primitive companion matrices

A nonnegative matrix $A$ is primitive if for some positive integer $m$ all entries in $A^m$ are positive. The smallest such $m$ is called the exponent of $A$ and written $\exp (A)$. For the class of primitive companion matrices $X$, we find $\exp (A)$ for certain $A \in X$. We find certain values of $m$ for which there is an $n \times n$ primitive companion matrix (for given $n$) with exponent $m$. We also propose open problems for further research.

A survey of swarm and evolutionary computing approaches for deep learning

Deep learning (DL) has become an important machine learning approach that has been widely successful in many applications. Currently, DL is one of the best methods of extracting knowledge from large sets of raw data in a (nearly) self-organized manner. The technical design of DL depends on the feed-forward information flow principle of artificial neural networks with multiple layers of hidden neurons, which form deep neural networks (DNNs). DNNs have various architectures and parameters and are often developed for specific applications. However, the training process of DNNs can be prolonged based on the application and training set size (Gong et al. 2015). Moreover, finding the most accurate and efficient architecture of a deep learning system in a reasonable time is a potential difficulty associated with this approach. Swarm intelligence (SI) and evolutionary computing (EC) techniques represent simulation-driven non-convex optimization frameworks with few assumptions based on objective functions. These methods are flexible and have been proven effective in many applications; therefore, they can be used to improve DL by optimizing the applied learning models. This paper presents a comprehensive survey of the most recent approaches involving the hybridization of SI and EC algorithms for DL, the architecture of DNNs, and DNN training to improve the classification accuracy. The paper reviews the significant roles of SI and EC in optimizing the hyper-parameters and architectures of a DL system in context to large scale data analytics. Finally, we identify some open problems for further research, as well as potential issues related to DL that require improvements, and an extensive bibliography of the pertinent research is presented.

On Classes of Meromorphic Locally Univalent Functions Defined by Differential Inequalities

In this article, we consider functions meromorphic in the unit disk. We give an elementary proof for a condition that is sufficient for the univalence of such functions which also contains some known results. We include few open problems for further research.

Sumsets with restricted number of prime factors

In 1934, Erdős and Turan proved that if a1, a2, . . . , an are distinct positive integers such that the product Π1≤i<j≤n(ai + aj) has at most k distinct prime factors, then n < 3 × 2k − 1. In this paper, we introduce the notion of the p-graph of a set of positive integers and improve the bound to n ≤ 2k. In particular, we prove that the bound 2k is optimal for k = 2. Beyond these, we also obtain some related results and pose several problems for further research.

The spectral characterization of the connected multicone graphs [formula omitted

A multicone graph is defined to be the join of a clique and a regular graph. Let w, n and m be natural numbers, and let Kw and Kn,n denote a complete graph and a complete bipartite graph, respectively. In this work, it is proved that connected multicone graphs Kw▽mKn,n, natural generalizations of friendship graphs, are determined by their adjacency spectra as well as their Laplacian spectra. Also, we show that the complement of multicone graphs Kw▽Kn,n is determined by their adjacency spectra. Furthermore, we prove that any graph cospectral with a multicone graph Kw▽mKn,n is perfect with respect to its adjacency (Laplacian) spectra. At the end of the paper, we pose two problems for further research.

Identification of climate changes based on antropogenic transformation of landscapes

Formulation of the problem. Functioning of natural geosystems is aimed at preserving their structure, but economic activity leads to imbalances, decreases in order, loss of internal organization and the inability to maintain the necessary stabilization. Analysis of previous research. Studies of the last decades have shown that the climatic conditions of Ukraine can be unfavorable for the life and economic activity of the society. Problems of further research. To find the solution to the problem of preserving the ability of the biosphere to self-regulation, self-restoration by optimizing anthropogenic load on natural systems is very important. Identification of climate change factors is aimed at finding the most active sources of environmental impact in order to determine the real threat of global climate change. The purpose of the research is to determine the causes, areas of initial formation, further development of negative meteorological processes and phenomena on the territory of Kharkiv region during the last decades and to study parameters and causes of air masses transformation, changes in their properties and various resistance to anthropogenic impact. Research methods are observation with the help of various devices and technical means. An integrated approach using field-based observations and technology of climatic series analysis with the help of statistical methods for climate information processing, characterized by high accuracy, allow us to determine their spatial-temporal features and future projections to the natural environment. Presentation of the main research material. Optimal strategic socio-economic development of the regions requires identification of specific links between natural and socio-economic entities, as well as studying large-scale and profound by the consequences violations of the ecosystem at the planetary level - the biosphere and its components. There is a general tendency towards directed climate change, the so-called "global warming", which threatens natural landscapes, upsetting and destroying them. Practical value. There are causal relationships between climatogenic changes, influence of human activity and the reaction of landscapes to them. This is manifested in creation of a variety of transformed landscapes (agrarian, residential, industrial). The consequence of anthropogenic transformations is the change in the parameters and characteristics of the components of nature. Research results. Indicators are the basis for information blocks concerning decision-making in the areas of socio-economic development. Climate parameters of a certain territory may differ from zonal ones and in combination with anthropogenic transformation affect the general condition of the landscapes, lead to the intensification of adverse hydrometeorological and exogenous geodynamic processes and phenomena (erosion, deluvial processes, landslides, suffusion, deflation, flooding.

Some Properties of the Strong Primitivity of Nonnegative Tensors

We show that an order m dimension 2 tensor is primitive if and only if its majorization matrix is primitive, and then we obtain the characterization of order m dimension 2 strongly primitive tensors and the bound of the strongly primitive degree. Furthermore, we study the properties of strongly primitive tensors with n≥3 and propose some problems for further research.

NComputing Adoption: Issues and Challenges

NComputing Technology is becoming increasingly important and is being used both in academe and business industry because of its capability of saving energy and maintenance costs. However, the adoption of this technology faces with concerns particularly in end users experiences. The paper aimed to examine the collection of some of the issues and challenges facing the NComputing technology adoption in academe particularly in Surigao del Sur State University and offered an initial roadmap to view the challenges and problems for further research. Findings revealed that most of the students were not satisfied with the performance of this technology. But, for technical support, they found it easy to maintain and troubleshoot.Â

Computational Geometry Column 67

In the limited workspace model, we consider algorithms whose input resides in read-only memory and that use only a constant or sublinear amount of writable memory to accomplish their task. We survey recent results in computational geometry that fall into this model and that strive to achieve the lowest possible running time. In addition to discussing the state of the art, we give some illustrative examples and mention open problems for further research.

Food-Consumer Interactions: Role of Time – Varying Key Parameters – a New Perspective

In this article, we have considered a simple food-consumer dynamic model in which the supply of food and the death of consumer species play the major role. The parameters representing these factors are allowed to vary with respect to time. It is established that by proper selection of these parameter functions, the system may be made to approach a desired state. It is noticed that these parameters define a space of equilibria for the given system in the limiting case. In case of different consumer species surviving on the same food, when there is no interference in consumption of one by the other, the growth is as desired. Growth is not as desired when one of the species is interfering with the food consumption of the other and the growth of the larger consumer is dominating. By simple variations in the death/removal of dominating species, the situation may be reversed in favor of the other species. The growth is as desired when the parameters are fixed constants. Examples are provided to understand the results and to illustrate various situations. The approach is tried on a popular mathematical model of biology to draw some useful conclusions. The study opens interesting problems for further research.

Communication in Colonial North America

AbstractCommunication in Colonial North America was difficult. To stay informed, people in the early modern world employed a variety of different methods and technologies. Before the regularization of postal routes and the proliferation of newspapers and other printed media, communication depended on the movement and connections of a wide variety of people. Exchanging information was not simply about having the most up‐to‐date news or the quickest messenger. It was a way of establishing and maintaining relationships, expressing identity, as well as articulating values and enforcing priorities—a process inextricably tied to social and geopolitical realities. Questions about how people communicated in colonial America open‐up wider discussions of literacy, technology, and power. This article reviews the most recent literature on the acquisition and spread of information in colonial North America, explores the different lines of inquiry scholars have pursued, and posits suggestions and problems for further research.