Set Of Programs Research Articles

Clone detection to prevent software piracy in android play store

Android is currently one of the most popular smartphone operating systems. Many application developers have been enticed by the enormous demand for mobile smartphone devices. The availability of reverse engineering tools for Android applications, however, also attracted virus authors' and plagiarists' attention. Cloning of applications has been a significant challenge to the Android market in recent years. However, Android accounts for the lion's share of all mobile malware globally, and its security vulnerabilities have garnered a lot of public attention. In this research, we look into how to recognize known Android malware using a clone detector. We compile a set of Android programs known to be malicious as well as a set of good programs. NiCad, a near-miss clone detector, is used to locate the classes of clones in a small fraction of the malicious programs after we retrieve the Java source code from the dex (Dalvik Executable file) file of the applications. The remaining malicious programs' source files are then searched for using these clone classes as a signature. As a control group, the non-harmful collection is utilized. In our analysis, we were able to decompile over 100 potentially harmful programs from 19 different malware families. According to our findings, a small sample of malicious programs can be used as a training set to detect 95% of known malware with a 96.88% accuracy rate and extremely few false positives. Our technique can successfully and consistently identify detrimental programs that are part of specific malware families. Moreover, illegal distribution is another part of software piracy, which is also a prevalent issue in the IT industry. We described an algorithm for the Android library licensing improvement to give insights to a developer on enhancing security measures to prevent the illegal distribution of individual Android applications.

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The UN Sustainable Development Goals program sets a number of important goals for the development of education. These are primarily related to determining the direction of development of education. In this regard, the article characterizes the following important concepts of the development of education in our country in the context of the concept of sustainable development: 1) implementation of the concept of safe development; 2) directing education to the development of society; 3) linking education with social, economic, political context; 4) acceptance of the concept of sustainable development as a methodological basis of ideas about the personality, its place in society; 5) ensuring that the content and methods of education are based on the basic principles of the concept of sustainable development; 6) effective use of the potential of student youth, who form a large socio-demographic group of the population, to ensure the progress and sustainable development of our society.

Enhancing Efficiency in Virtualized Environments: Intelligent Solutions for VMware Errors through Artificial Intelligence and API Integration

Today, virtualization technologies play a critical role in the information technology sector, enabling businesses to manage their infrastructures more efficiently and flexibly. However, the complex structure and extensive feature set of virtualization programs often lead users to encounter error codes and technical issues. This can result in significant time losses and decreases in productivity, especially for inexperienced users. To address these challenges quickly and effectively, the IT sector is increasingly focusing on integrated solutions developed with artificial intelligence and smart assistant technologies. This study introduces the "VMware Assistant" software, designed to address technical issues related to VMware products. VMware Assistant utilizes pre-trained AI models, APIs from various websites, and comprehensive error and warning datasets to automatically detect and provide real-time solutions for user issues. The system aims to alleviate the complexities associated with virtualization programs and offer practical support to users. VMware Assistant consolidates error and warning data from multiple sources, enabling users to swiftly access the information they need. As a result, it accelerates the resolution process for technical issues encountered in virtualized environments, allowing users to maintain workflow continuity. VMware Assistant was developed to facilitate the use of virtualization technologies, potentially enhancing productivity in the IT sector and contributing to technical support processes.

სამღეროვანი წამწის პარამეტრების ოპტიმალური მნიშვნელობების განსაზღვრა არაწრფივი მათემატიკური დაპროგრამების მეთოდის გამოყენებით

The work considers the possibility of using the method of non-linear mathematical programming to calculate the optimal, according to the criterion of weight, the values of the parameters of a symmetrical three-tire farm. The proposed method allows you to choose the area of the transverse sections of the farm rods so that their weight would be minimal, with given loads and restrictions imposed on the area of the rods. The work also considers the effect of changing the angle of inclination of the edge rods to the abscissa axis on the structure and values of the optimal parameters of the farm. To find the global minimum of target functions, a random search method is used. A set of programs for finding numerical values of the optimal parameters of the farms has also been developed.

Rebuilding Participatory Institutions in Brazil: The PPA Participativo Between Corporate Demands and Climate and Animal Rights

In 2023, Brazil regained momentum in proposing innovative participatory institutions by launching a complex participatory experiment for budget planning within its “Multiannual Plan” (PPA). While this was not a scaled-up version of the local participatory budgeting plan that emerged decades earlier, its launch did reopen the debate on the possibilities of expanding political participation. The challenge was significant due to the intricate nature of budget planning and the complexity of the plan’s participatory design. This paper examines that experience by outlining the institutional design of the PPA Participativo and analyzing its results in terms of online participation. It also discusses the prominence of climate-related proposals, suggesting that the PPA Participativo serves as a relevant indicator of national concerns regarding climate-based issues. Building on previous experiences, the PPA Participativo is a strategy consisting of three layers: an online platform for digital participation, state-level meetings with civil society activists, and a high-level forum composed of members from national councils. This paper analyses some of the results from the online platform, which recorded 4 million visits from 1.5 million individual participants. These citizens were invited to submit proposals, vote for up to three proposals, and choose from a set of pre-designed government programs. The main concerns that emerged from this open-ended process included corporate demands, stemming from highly organized sectors, such as public health and education employees. However, animal rights also ranked among the most-voted proposals. The program of the Ministry of the Environment on climate change reached the top position in this segment, largely due to its strong campaigning strategy. This paper discusses these outcomes, drawing on evidence of both societal engagement and institutional activism to promote specific agendas.

Mathematical Modeling of Temperature Fields in Cultivation Structures

Purpose. The main purpose of the article is to develop a method for calculating thermal fields in greenhouse soil in the case of its artificial heating. Since the temperature regime in greenhouse soil has a significant impact on plant yields, it is very important, on the one hand, to ensure the required temperature in the soil, and on the other hand, to determine the energy-saving heating regime. Methodology. The method is based on the numerical integration of the heat transfer equation. A two-dimensional heat transfer equation was used to analyze and predict the unsteady process of soil heating in a greenhouse under artificial heating, and two finite-difference schemes were used to solve it. On the basis of the constructed numerical models, a computer program was developed to conduct a computational experiment. Findings. Effective computer models have been created to predict the unsteady formation of thermal zones in the greenhouse soil during its artificial heating. The results of numerical modeling are presented. Originality. Prognostic numerical models have been developed to analyze the dynamics of thermal fields formation in greenhouse soil during its artificial heating. On the basis of the developed numerical models, a set of application programs was created to conduct a computational experiment to determine the unsteady temperature field in greenhouse soil. The constructed numerical models belong to the class of «operational models», i.e., they are designed for the operational analysis of thermal fields in the soil. For the practical use of the developed numerical models, standard input information is required. Practical value. The constructed numerical models are a tool for analyzing the dynamics of soil heating and can be used in the development of energy-saving heating technology. These models can be used to determine the time of optimal soil heating in different zones (root system, soil surface) and to determine the rational location of heating elements, the time when the heating elements should be turned off, and the time when they should be turned on again. These models allow us to develop an energy-saving technology for heating the soil in a greenhouse.

Research of the role of charitable foundations in the provision of medicines to the population

Introduction. Despite the positive developments in providing patients with orphan diseases, achieved through the implementation of a set of federal and regional programs, it has not yet been possible to achieve full and timely satisfaction of the target segment's need for medicines, and patients are forced to look for additional sources of funding for drug therapy, one of which is the budgets of charitable foundations. Objective: research the role and place of charitable foundations in the system of drug provision for patients with orphan diseases. Material and methods. Сontent analysis of legislative and regulatory acts of the Russian Federation in the field of healthcare and circulation of medicines, open data from the official website of the All-Russian Society of Orphan Diseases, statistical data of the Ministry of Health of the Russian Federation, open official reports of the Circle of Good Foundation and official websites of 57 charitable foundations. Results and discussion. The elaboration of mechanisms for including charitable foundations in the list of organizations that have the right to work with narcotic drugs and psychotropic substances in exceptional cases in terms of patients with orphan diseases seems to be another way to improve the quality of drug provision for privileged categories of patients. Conclusion. The elaboration of mechanisms for including charitable foundations in the list of organizations that have the right to work with narcotic drugs and psychotropic substances in exceptional cases in terms of patients with orphan diseases seems to be another way to improve the quality of drug provision for privileged categories of patients.

Prospects of using artificial intelligence for improving cancer screening efficаcy

Introduction. The effectiveness of screening as one of the strategies for cancer control is beyond doubt. Screening reduces the risk of diagnosing cancer at a late stage and identifies precancerous pathologies, thereby preventing the development of cancer. Potential limitations of screening include the high probability of false positives, false negatives, and overdiagnosis. The consequences are additional examinations and unnecessary and, often, excessive treatment. At the same time, interval cancers, which are characterized by an aggressive course, often do not come into view.The purpose of the study: to explore the data on effectiveness of artificial intelligence (AI) for improving the sensitivity and specificity of cancer screening and reducing the probability of false negative and false positive results, and overdiagnosis.Materials and methods. Review and analysis of published data on a) screening of breast cancer (BC), lung cancer (LC), prostate cancer (PC), cervical cancer (CC) and large bowel cancer (LBC); b) development and application of AI systems to improve the effectiveness of screening. The PubMed and Cochrane Library databases were searched for relevant publications.Results. In mammography screening, AI reduces the number of abnormal interpretations of mammograms, the number of recalls, the number of biopsies with a negative result, and increases the efficacy of mammogram interpretation regardless of the characteristics of the breast (dense breast, calcifications). The use of AI in conjunction with low-dose computed tomography (LDCT) for LC screening not only improves the diagnosis of various types of LC, but also predicts the risk of developing cancer several years in advance. A systematic review and meta-analysis of 12 studies evaluating the effectiveness of AI in tandem with multiparametric magnetic resonance imaging (mpMRI) of the prostate showed high overall effectiveness in the diagnosis of clinically significant PC. The performance of the AI system – based on the multimodal data including demographics, clinical characteristics, laboratory tests and ultrasound reports of patients with PC, was better than the effectiveness of PSA tests in diagnosing clinically significant PC. The effectiveness of AI in tandem with colonoscopy, despite the use of the most advanced AI systems (deep learning system based on a convolutional neural network), remains controversial. The solution to this problem depends on what goal we are pursuing when developing and training the system? Increasing “detection rate” of adenomas, regardless of their size, and removing them, or identifying and removing only large adenomas? The successful use of AI for cytological diagnosis of cervical pathology, including all stages of cervical intraepithelial neoplasia (CIN), is encouraging. The introduction of AI systems developed and trained to interact with a cytopathologist in reading and evaluating cytological material and diagnosing CIN and CC into general practice will reduce the burden on cytopahologists and other medical personnel.Conclusion. The analysis of published data has shown the promising results concerning the use of AI for cancer diagnostics, especially in the setting of population screening programs, which cover many thousands of people. The use of AI significantly increases the effectiveness of diagnostic tool, improves its sensitivity and specificity, and reduces the probability of false negative, false positive results and overdiagnosis. The decision to introduce into practice any of the AIs with proven effectiveness in clinical trials should be made only after its testing in a real world, at the population level. The “informed consent” forms that objectively describe all the advantages and disadvantages of the use of AI compared to current practice has to be developed.

A co-design process to develop personalized mobility programming for individuals with mobility impairments.

Individuals with neurological conditions (e.g., stroke, spinal cord injury, multiple sclerosis) may experience challenges to their mobility. While the individual needs for persons with neurological conditions may vary, thus making intervention development more difficult, identifying key personalization or tailoring variables may help to customize interventions. However, the process to personalize treatments has not been well described. It is also unclear how adaptive intervention design includes the perspective of those with lived experience. Co-design methods may be a way to be transparent about intervention development to meet the needs of persons with mobility impairments while ensuring the resulting intervention is relevant and applicable to those who will be participating. The purpose of the present article is to describe a co-design process to facilitate the development of personalized mobility programming for persons with mobility impairments. Development of a set of personalized mobility programming for individuals with mobility impairments was conducted following an adaptive intervention design approach with a co-design component. A series of working groups and individual sessions with key interest groups (e.g., persons with lived experience, fitness instructors, front-line clinicians, students) were conducted in order to develop the personalized mobility programming based on the needs and preferences described during various working groups. Two sets of working groups and three individual one-to-one sessions were conducted with a total of 14 participants (n = 6 persons with lived experience, n = 4 research team members, n = 2 physiotherapists, n = 2 occupational therapists, n = 1 registered kinesiologist). From the information gathered during the working groups a set of four personalized mobility programs were developed: (1) cognitive cardio class, (2) functional strength class, (3) mobility circuit group, and (4) an open gym. Participants also discussed the onboarding process, how to effectively track participant goals throughout the programming and personalization variables. The current paper provides a guideline for future work that aims to develop programming that is personalized to the needs of the persons with mobility impairments due to various neurological conditions. The strengths of this approach include the collaborative nature of the program development, while the main limitations were logistical in nature (e.g., scheduling, engaging all working group members).

The Role of Artificial Intelligence in the Culture of the Tourism Industry of the Modern World

The trend in using artificial intelligence to promote business processes and form marketing campaigns is increasingly being used in the travel industry. Artificial intelligence is a set of programs that can simulate human skills, for example, planning, solving specific tasks, learning and improving its functionality as information accumulates. AI technologies are improving and transforming travel in all sorts of ways. Offers of personal recommendations are based on a systematic selection of information and improving the quality of customer service. Virtual assistants and optimization of operational efficiency improve the booking service of travel products. When examining the importance of artificial intelligence in the development of the modern tourism industry, one can note both advantages – this is data analysis and its transformation, improving the quality of service in travel, ensuring the preservation of historical sites, and disadvantages – digital replication, the use of neural networks to change the appearance of objects or even entire cities, which in the future can lead to a distorted view of tourists on a particular tourist destination.

A real scene 3D Model-Driven sunlight analysis method for complex building roofs

A real-scene 3D model of complex buildings, derived from UAV (Unmanned Aerial Vehicle) surveys, can significantly improve the accuracy of sunlight analysis for the arrangement of photovoltaic panels. We propose a method for sunlight analysis of complex building roofs driven by the real-scene 3D model, which includes generating and optimizing the 3D model and a parameterized sunlight analysis algorithm. The generation and optimization method involves: reducing the number of model meshes by selecting a lower level of detail and proposing a mesh simplification algorithm to simplify the model; reconstructing the structure of the model meshes to smooth them and solve the pseudo-occlusion problems caused by the model’s triangular structures by transforming triangular meshes into quadrilateral meshes; improving the accuracy of the obstacles’ 3D models on the roof by completing high-precision obstacle modeling and superimposing it on the simplified model. Subsequently, a parameterized sunlight analysis algorithm suited to the optimized 3D model is presented based on the Grasshopper parameterized software platform. We design a complete set of sunlight analysis algorithm programs by exploring the geographical location, time range, time step, and other parameters of the real-scene 3D model. Finally, the method’s feasibility is verified through a case study of a complex building.

Taking risk to heart: An evaluation of cardiometabolic risk and screening guideline adherence in outpatients with spinal cord injury

Objectives: To evaluate cardiometabolic disease (CMD) in outpatients with spinal cord injury/disease (SCI/D). The study aims were to (1) estimate the prevalence of CMD risk factors in a cohort of Canadian adults with SCI/D; (2) assess whether the frequency of CMD screening aligns with evidence-based guidelines; and (3) gain a preliminary understanding of the barriers to CMD screening and/or treatment within a rehabilitation program setting. Design: Quality improvement initiative involving chart review extracting the presence of and frequency of screening for four CMD risk factors (obesity, hypertension, dyslipidemia, diabetes mellitus). Values were compared to evidence-based guidelines for CMD risk identification and management. Root cause analysis and focused interviews were conducted with clinic staff to identify barriers. Setting: Academic, tertiary rehabilitation hospital. Participants: Consecutive outpatients with SCI/D from October 2020 to December 2021 (n = 73). Results: 43.8% of outpatients sampled had established CMD (≥3 risk factors) and 94.5% had at least one risk factor. Obesity was the most prevalent (82.2%), followed by dyslipidemia (71.7%), hypertension (46.5%), and diabetes mellitus (34.8%). Hypertension and obesity screening were completed at 14.3% and 10.4% of appointments. The frequency of dyslipidemia and diabetes mellitus screening could not be determined. Eighteen barriers to timely CMD screening and treatment intensification were identified. Conclusions: The prevalence of CMD risk factors in outpatients with SCI/D was high. While approximately two of every five outpatients had established CMD, adherence to screening guidelines was poor. These findings reinforce the need for strategies to improve screening and reduce preventable harm from CMD in this vulnerable population.

THE ROLE OF EXPERT SYSTEMS WITHIN ARTIFICIAL INTELLIGENCE

Expert systems (ES) arose as a significant practical result in the application and development of artificial intelligence methods - a set of scientific disciplines that study methods for solving problems of an intellectual (creative) nature using a computer. From the beginning of its development, the field of artificial intelligence has considered several very complex problems, which, along with others, are still the subject of research: automatic theorem proofs, machine translation, image recognition, planning, game algorithms, strategies, etc. In modern understanding, an expert system is a set of programs that perform the functions of an expert when solving problems from a certain subject area. Expert systems advise, conduct analysis, provide consultations, and diagnose. The practical use of expert systems in enterprises contributes to work efficiency and improved qualifications of specialists. When creating expert systems, several difficulties arise. This is primarily because the customer cannot always accurately formulate his requirements for the system being developed. It is also possible that difficulties of a purely psychological nature may arise when creating a knowledge base of a system, an expert may hinder the transfer of his knowledge, fearing that he will subsequently be replaced by a “machine”. But these fears are not justified, since expert systems are incapable of learning, they do not have common sense or intuition. Currently, expert systems are being developed that implement the idea of self-learning. Advantages of an ES over a human expert. Knowledge-based systems have certain advantages over human experts: they have no prejudices, they don't rush to conclusions, these systems work systematically, looking at all the details, often choosing the best alternative from all possible ones,the knowledge base can be very, very large, once entered the machine, the knowledge is stored forever, a person has a limited knowledge base, and if data is not used for a long time, then it is forgotten and lost forever. Knowledge-based systems are resistant to “interference.” The expert uses collateral knowledge and is easily influenced by external factors that are not directly related to the problem being solved. ES that are not burdened with knowledge from other areas is, by their nature, less susceptible to “noise.” Over time, knowledge-based systems may be viewed by users as a type of replication - a new way of recording and disseminating knowledge. Like other types of computer programs, they cannot replace a person in solving problems but rather resemble tools that enable him to solve problems faster and more efficiently. These systems do not replace a specialist but are a tool in his hands. The modern idea of expert systems is given in the article. Their differences from traditional software products are shown, and advantages and disadvantages are considered. A conclusion is drawn about the perspectives of development. Keywords: information technology, expert systems, knowledge base, knowledge processing algorithm.

Aging drives a program of DNA methylation decay in plant organs.

How organisms age is a question with broad implications for human health. In mammals, DNA methylation is a biomarker for biological age, which may predict age more accurately than date of birth. However, limitations in mammalian models make it difficult to identify mechanisms underpinning age-related DNA methylation changes. Here, we show that the short-lived model plant Arabidopsis thaliana exhibits a loss of epigenetic integrity during aging, causing heterochromatin DNA methylation decay and the expression of transposable elements. We show that the rate of epigenetic aging can be manipulated by extending or curtailing lifespan, and that shoot apical meristems are protected from this aging process. We demonstrate that a program of transcriptional repression suppresses DNA methylation maintenance pathways during aging, and that mutants of this mechanism display a complete absence of epigenetic decay. This presents a new paradigm in which a gene regulatory program sets the rate of epigenomic information loss during aging.

Practical use of S-Detect Thyroid artificial intelligence-based program for automatic detection and characterization of thyroid nodules

In order to assess the practical efficacy of the S-Detect Thyroid artificial intelligence-based program for automatic detection and analysis of thyroid lesions, the prospective assessment of 84 focal thyroid lesions was carried out. he risk of malignancy was stratified according to the EU-TIRADS at the same time. A fine-needle aspiration biopsy was performed for all detected nodules of EU-TIRADS 3–5 category and a diameter ≥10 mm. Cytological examination was performed using the Bethesda classification. According to the cytology data, all patients were divided into two groups: 73 patients with benign thyroid nodules (Bethesda II) and 11 patients with malignant nodules (Bethesda V). Patients with “uncertain” Bethesda categories “I”, “III”, and “IV” were excluded from the study. The results of the study showed that the use of the S-Detect program based on artificial intelligence allows for differential diagnostics of benign (Bethesda II) and malignant (Bethesda V) thyroid nodules with a sensitivity of 90.9%, specificity of 94.5%, positive and negative predictive value of 71.4% and 98.6%, accuracy of 94%, and AUC 0.941. In our opinion, the best results of all program settings show the S-Detect “High Accuracy” mode, which we recommend for practical use. In some cases, there was disagreement between the S-Detect and the doctor's opinion in characterizing the nodule structure and echogenicity, as well as in determining the presence of macro- and microcalcifications. In our opinion, the use of the S-Detect benign/malignant criteria as indications for needle aspiration biopsy would avoid obviously unnecessary diagnostic interventions in some patients with thyroid nodules classified as EU TIRADS 3–5. However, the S-Detect artificial intelligence program cannot currently fully replace the doctor's intellect, erudition, and experience.

Designing tests for some motor abilities and predicting the level of performance skill for academic school football players aged (13-14) years

The study aims to design tests to measure some motor abilities in the study sample, to find standard grades and levels for some tests of motor abilities in the study sample, preparing equations to predict the level of performance skill of soccer players in terms of mobility tests in the research sample. The researcher used the descriptive approach, and the research community was selected from football academy players aged (13-14) years in Raparin. The research sample was selected intentionally, which included (260) players. So as to reach the results, the researcher used a set of statistical programs by using SPSS. It was concluded to find and determine the grades and standard levels modified for the research sample in the motor tests, determining an equation to predict the level of performance skill in terms of motor abilities. It is recommended that the prediction equation can be adopted as indicators through which the components of motor abilities are determined and the possibility of upgrading it according to the time period of the preparation stage to reach the level of competition.

Healthy lifestyle promotion project among healthcare workers

Abstract Background The psychosocial risks generated from difficult work conditions are damaging not only for the workers’ health and safety, but also have a huge impact on the organization and management efficiency. Description Some of the primary challenges that health workers face are demanding schedules and stressful shift patterns which lead to higher levels of worker burnout. Ensuring the well-being of healthcare staff is crucial not only for the individual workers, but it also brings important lessons to the community creating an environment built on a culture of health. Results In the past year, the Hospital of Cittadella (Province of Padua) has launched a set of programmes structured to help the staff make better lifestyle choices that affect not only their personal life but also create a more sustainable work environment. One of the projects involved various meetings with a Physical Medicine-Rehabilitation physician, a physical therapist, an Occupational Medicine physician and a medical yoga teacher. The encounters, attended by nearly 10% of the hospital staff, were aimed to help healthcare workers create a more balanced lifestyle and to implement physical activity and posture exercises in their daily routine. Four nutrition classes were also organized with the help of a nutritional biologist. The aim of this course was to show the basics of healthy diets supported by scientific data and guide the participants towards realistic and healthy meal plans. Lessons In conclusion, increasing the general wellbeing within the healthcare context is not an easy task, especially when organizational circumstances like staff reduction are being faced. These projects represent a small step towards facing these difficulties. It is important to note that the motivation, collaboration, inclusivity, flexibility and reliance are all elements that contribute to better mental and physical health of the healthcare staff which is crucial on an individual, organizational and societal level. Key messages • Increasing personal well being amongst healthcare workers can help create a more sustainable work environment. • A healthy work environment is crucial for a better functioning organization.

Effects of screening coverage and screening quality assurance on cervical cancer mortality: Implication for integrated framework to monitor global implementation of cervical cancer screening programmes.

Cervical cancer is a global health threat and a manifestation of inequality, and screening is an effective intervention. However, little is known about how screening coverage and quality assurance, influence cervical cancer mortality. We aimed to investigate the association between screening coverage, screening quality assurance and cervical cancer mortality among women from countries at different developmental levels. We obtained data on age-standardised mortality from cervical cancer from the GLOBOCAN 2020 database; coverage of cervical cancer screening from World Health Organization (WHO) Global Health Observatory; and cervical screening programme settings and quality assurance from the Cancer Screening in Five Continents (CanScreen5) database. We assessed the dependency of cervical cancer age-standardised mortality on screening coverage and quality assurance by simple and multiple regression models. We also used linear regression models to identify factors that improved the screening coverage. The study included data from 53 countries. Reduced mortality was associated with increased screening programme quality assurance in 22 high-development countries. In 31 low-development countries, screening coverage in women aged 30-49 years was inversely associated with cervical cancer mortality. Political commitment (documentation of the cervical cancer screening policy as law) and financial support (treatment services provided free of charge) positively associated with screening coverage. Screening programmes need strengthening commensurate with local resources and context. Priority should be given to improving screening coverage through stronger political commitment and financial support in low-development countries, and to ensuring good performance at all levels in high-development countries.

Optimizing a linear function over the efficient set of a multiple objective integer quadratic program

In this paper, we investigate the optimization of a function over the efficient set of a Multiple Objective Integer Quadratic Program (MOIQP). The method described employs a branch-and-cut approach to address the problem. At every node within the search tree, a profound cut is derived by considering the ascending trends of the criteria. This cut enables the removal of branches where the associated sub-problems don’t contain efficient solutions. The proposed methodology is illustrated in an example. Extensive numerical experiments are conducted to demonstrate the method’s effectiveness against state-of-the-art methods.

Research on cargo volume prediction and personnel scheduling optimization of sorting center based on BP neural network and improved genetic algorithm

With the development of Internet technology, e-commerce has become the primary choice for consumers to shop, and the huge order transaction volume has generated logistics problems. As an important part of the logistics network, the sorting platform is essential to improve its management efficiency. To enhance the efficiency of the sorting center, the topological relationship diagram is used to show the logistics network, and the cargo volume of the sorting center in the next 30 days and every hour is predicted based on the BP neural network model. Based on the mixed integer linear programming model and the improved genetic algorithm SCAGA model, the total man-days are minimized to ensure that the cargo volume is processed. At the same time, to ensure that the actual hourly efficiency is as balanced as possible, the optimization problem of personnel scheduling is studied. To maintain the efficient operation of the logistics industry, the accurate prediction of the number of goods and the reasonable scheduling of personnel, to provide a set of efficient and economical personnel scheduling programs for the logistics company, thus improving the overall operational efficiency and service quality.