Classification Of Problems Research Articles

Firefly algorithm applied to the job-shop scheduling problem

The job shop scheduling problem (JSSP) is one of the most researched scheduling problems. This problem belongs to the NP-hard class. An optimal solution for this category of problems is rarely possible. We try to find suboptimal solutions using heuristics or metaheuristics. The firefly algorithm is a great example of a metaheuristic. In this paper, this algorithm is used to solve JSSP. We used some benchmarking JSSP datasets for experiments. The experimental program was implemented in the aitoa library. We investigated the optimal parameter settings of this algorithm in terms of JSSP. Analysis of the experimental results shows that the algorithm is useful to solve scheduling problems.

Development Of Multi-Criteria Decision Making Model In Packed Beverage Industry Using Global Criterion Method

The packaged beverage industry with various brands has appeared on the market. The number of competitors in the market requires the packaged beverage industry to implement the right strategy to win the competition. One strategy that can be applied is to make savings and maximize the use of company resources. One of the savings that can be done is to minimize production costs, while maximizing the use of resources can be done by maximizing the utility of the machine owned by the company. Efforts to minimize production costs can be contradictory to efforts to maximize machine utility, this is because maximizing machine utility will certainly require additional production costs, even though the company also wants to minimize production costs. This is included in the category of multi-criteria decision-making problems. To facilitate the company's management in achieving these contradictory company goals, this study will develop a multi-criteria decision-making model to assist companies in making optimal decisions regarding these contradictory company goals. The multi-criteria decision-making model developed is a mathematical model consisting of two mutually contradictory objective functions, namely minimizing production costs and maximizing machine utility, as well as problem constraints which are limitations that are owned by the company in optimizing the achievement of these contradictory company goals. To optimize the multi-criteria decision-making model that has been developed, it will use the global criterion method. The global criterion method will produce a compromise solution that has a minimum deviation from the ideal value of each objective function. Using the global criterion method, a production plan that minimizes production costs and maximizes machine utility is obtained. The multi-criteria decision-making model developed will cause the production plan to have a small deviation from the actual demand, because the model development involves forecasting product demand. The developed model will also produce a production plan that will not exceed the warehouse capacity, so that product storage costs can be minimized, this is because the developed model includes warehouse capacity as a barrier.

Association Among Self-Injury, Suicidal Tendency, and Personality and Psychological Characteristics in Korean Adolescents.

ObjectiveTo compare mental health problems and personality characteristics between adolescents with self-injury (SI) and suicidal tendency (ST), including suicidal ideation and suicide planning. Methods The participants completed the Adolescent Personality and Mental Health Problems Screening Questionnaire, Third version (AMPQ-III), and Korean version of the Strengths and Difficulties Questionnaire (SDQ-Kr), and gave their demographic information. Based on the answered SI and ST items in AMPQ-III, the participants were divided into groups: without SI and ST, with SI and without ST, without SI and with ST, and with SI and ST. Analysis of variance (ANOVA) and post-hoc Scheffe test were used to determine group differences, stepwise multiple linear regression, and factors associated with SI and ST. ResultsANOVA yielded results for all categories of mental health problems. Significant differences were observed between the four groups. Conversely, for personality characteristics, only the sense of community item between the group without SI and with ST and the group without SI and ST were significantly different; sense of community was associated with ST (β=-0.054, p=0.005). Among the mental health subscales, SI was significantly associated with conduct problems (β=0.211, p<0.001), emotional problems (β=0.173, p<0.001), peer problems (β=0.085, p<0.001), and prosocial behavior (β=0.073, p<0.001). ST was significantly associated with emotional symptoms (β=0.317, p<0.001), peer problems (β=0.130, p<0.001), conduct problems (β=0.106, p<0.001), hyperactivity (β=0.050, p=0.010), and prosocial behavior (β=0.062, p<0.001). ConclusionThe findings highlight the necessity of assessing psychological strength, difficulties, and personality characteristics for the prevention and early intervention of adolescent SI.

Playability Evaluation using the Heuristic Evaluation of Playability Method in Warcraft 3 Reforged

Game is a digital activity that is very popular in the modern era, both among young and old. One game that is very popular with E-sports competition is Warcraft 3. However, in 2020 it immediately fell because Blizzard company has released a new version of those games which is called warcraft 3 reforged. The purpose of this study was to find out the reason this could happen by using the heuristic evaluation of playability method. With this method, you can find the scale of the problem in a game that will be released. The data used for this study uses the player persona as the source of the assessment that will be carried out in this game. The player persona is created by providing 10 respondents who will be required to perform and assess each task given according to the scenario codes. The benefits of this research can be used to analyse the readiness of games to be released to the market and to find out customer tastes in RTS (Real Time Strategy) type games. This assessment is based on the mean rating which will later be categorized as the level of problem in the running of the game. The results of this study indicate that the mean rating in this game is 2.91 or can be referred to as the Major Usability Problem with the highest value of percentage with the highest problem category found in the game usability with a percentage value of 41.7%.

Classification of cervical cells leveraging simultaneous super-resolution and ordinal regression

Automatic classification of cervical cells plays a critical role in the Computer-assisted Cytology Test (CCT) system. The efficiency of the CCT system can be promoted by sacrificing the microscopic image resolution to speed up the microscopic image acquisition. In this case, the low resolution of the cell image will severely deteriorate the performance of available Convolutional Neural Networks (CNN) based classification methods. Inspired by the positive effect of super-resolution in addressing classification or recognition tasks, we propose a cervical cell classification algorithm leveraging simultaneous super-resolution, which is achieved using Generative Adversarial Network (GAN) techniques. Our framework is designed in an end-to-end manner wherein the classification loss is back-propagated into the super-resolution network during training. Moreover, we perform ordinal regression with smooth L1 loss to further improve the classification results. Extensive experiments have verified the effectiveness of our method. Our simultaneous super-resolution based method achieves 93.5% classification accuracy on the 6-class Heer dataset, outperforming the method using only the state-of-the-art classifier by an obvious margin of 3.2%. Besides, our ordinal regression method significantly improves the MAE (Mean Absolute Error) by 0.0143 and 1-off accuracy by 0.95% on the 4-class Heer dataset. For the Herlev dataset, our method yields the classification accuracy of 98.1% and 97.6% for the 2-class and 7-class problems, which is still competitive even with low-resolution input.

Oscillatory electroencephalographic patterns of arithmetic problem solving in fourth graders

Numerous studies have identified neurophysiological correlates of performing arithmetic in adults. For example, oscillatory electroencephalographic (EEG) patterns associated with retrieval and procedural strategies are well established. Whereas fact retrieval has been linked to enhanced left-hemispheric theta ERS (event-related synchronization), procedural strategies are accompanied by increased bilateral alpha ERD (event-related desynchronization). It is currently not clear if these findings generalize to children. Our study is the first to investigate oscillatory EEG activity related to strategy use and arithmetic operations in children. We assessed ERD/ERS correlates of 31 children in fourth grade (aged between nine and ten years) during arithmetic problem solving. We presented multiplication and subtraction problems, which children solved with fact retrieval or a procedure. We analyzed these four problem categories (retrieved multiplications, retrieved subtractions, procedural multiplications, and procedural subtractions) in our study. In summary, we found similar strategy-related patterns to those reported in previous studies with adults. That is, retrieval problems elicited stronger left-hemispheric theta ERS and weaker alpha ERD as compared to procedural problems. Interestingly, we observed neurophysiological differences between multiplications and subtractions within retrieval problems. Although there were no response time or accuracy differences, retrieved multiplications were accompanied by larger theta ERS than retrieved subtractions. This finding could indicate that retrieval of multiplication and subtraction facts are distinct processes, and/or that multiplications are more frequently retrieved than subtractions in this age group.

Development of an exercise programme for balance abilities in people with multiple sclerosis: a development of concept study using Rasch analysis

BackgroundPeople with multiple sclerosis (PwMS) frequently have impaired balance from an early stage of the disease. Balance difficulties can be divided into categories; although, to date, these lack scientific foundation. Impaired balance in PwMS can be addressed using specific and challenging exercises. Such exercises should provide an optimal challenge point; however, the difficulty of balance exercises is often unknown, making it difficult to target the exercises to an individual’s abilities.The aims of this study were: to develop an exercise programme for PwMS relating the exercises to the balance problem categories; to establish the order of difficulty of exercises in each category and; to evaluate the content and structural validity of the exercise programme.MethodsA “construct map” approach was used to design and develop an exercise programme for PwMS. Potentially relevant balance exercises were identified, then a framework was set up, comprising four dimensions (subsequently reduced to three dimensions) of balance exercises. The relevance, comprehensibility, and comprehensiveness of the exercise programme were rated by 13 physiotherapists, who also linked 19 key exercises to balance categories. A total of 65 PwMS performed the 19 balance exercises, rated their difficulty and commented on the relevance and comprehensibility of each exercise. A Rasch model was used to evaluate the relative difficulty of the exercises. To assess fit of the data to the Rasch model a rating scale model was used, which is a unidimensional latent trait model for polytomous item responses.ResultsEvaluation by the physiotherapists and PwMS indicated that the content validity of the exercise programme was adequate. Rasch analysis showed that the latent trait “balance exercises in PwMS” comprised three subdimensions (“stable BOS”, “sway” and “step and walk”). The 19 balance exercises showed adequate fit to the respective dimensions. The difficulties of the balance exercises were adequate to cover the ability spectrum of the PwMS.ConclusionA balance exercise programme for PwMS comprising three dimensions of balance exercises was developed. Difficulty estimates have been established for each of the exercises, which can be used for targeted balance training. Content and structural validity of the programme was adequate.

Motivations for Prescription Drug Misuse Related to Mental Health Problems in Adults

Background Prescription drug misuse (PDM) is a significant public health problem associated with mental health symptoms. Objectives This project investigates the connections between PDM motivations and mental health to inform intervention efforts. Methods Using nationally representative adult data from the 2016–2018 National Survey on Drug Use and Health (N = 128,205; 53% female) this project investigated which motivations for misuse are related to past-year mental health problems including any mental illness, serious mental illness, major depressive episode, and suicidal thoughts. Complex samples logistic regression models of the main motivation of PDM for each mental health problem were conducted separately for each prescription drug class (i.e., opioids, tranquilizers, sedatives, and stimulants) while controlling for demographic characteristics. Results Adults that reported PDM were more likely than those with no PDM to endorse past year mental health problems. Compared to those that reported PDM of other medications, those misusing prescription opioids and tranquilizers to help with emotions and misusing sedatives to “relax or relieve tension” were more likely to have all categories of mental health problems. Those that misused prescription stimulants to “help study” had lower odds of all mental health problems. Conclusions While there were differences based on prescription drug class, a range of motivations increased adults’ likelihood to have mental health problems and common themes were found across drug classes. While causality is still undetermined, prevention and intervention efforts that are multifaceted and individualized, while broadly providing adults with other ways to cope with negative emotions are likely to help reduce PDM.

TEA-SEA: Tiling and scheduling of non-uniform two-level perfectly nested loops using an evolutionary approach

Nowadays, in scientific and computational programs, increasing the execution speed of programs is very important. In implementing scientific programs, loops are dedicating a large part of time to themselves. Therefore, the parallel execution of the iteration loop reduces the runtime of all programs. This paper has been working on the parallelism of two-level perfectly nested loops with non-uniform dependencies and rectangular iteration space, and then their scheduling is based on the scheduling of task graphs. For this purpose, the iteration space of non-uniform loop is partitioned using a tiling transformation, and then the tiled space is modelled as a task, graph for scheduling. In the task graph, vertices expressive tiles and edges expressive data dependencies inter-tiles. It should be noted that the computational load of vertices is not the same, and the vertices corresponding imperfect tiles have a less computational load. The scheduling is done on both types of homogeneous and heterogeneous multiprocessor systems. The tiling of iteration space loop and the scheduling of task graph is arranged in the category of NP-Hard problems that using evolutionary algorithms can be efficient to discover a suitable solution for them. The results of the proposed approach show the performance of this method better than previous methods in the tiling and scheduling of non-uniform loops. According to the examinations performed on uniform loops, this algorithm also performs better than previous algorithms on these types of loops.

An information entropy-based evolutionary computation for multi-factorial optimization

Recently, a new category of problems known as multi-factorial optimization (MFO) is gaining momentum in the field of evolutionary computation (EC). This paper aims at improving the aggregate performance of an underlying EC model in a multi-tasking environment by implementing simple strategies with minimal parameter tuning effort. Firstly, an enhanced Simulated Binary Crossover (SBX)-based unary variation operator to improve EC performance is devised. Secondly, to overcome the challenge in parameter tuning and operators selection, an adaptive control strategy underpinned by information entropy is proposed. We study the measure of entropy to quantify the uncertainty of evolutionary search and use the information to adapt the algorithmic parameters. Thirdly, the MFO problems are solved using the proposed methods. Three experiments are carried out to attest the methodology efficacy. The first experiment benchmarks the proposed method against twelve state-of-the-art single objective optimization algorithms in the CEC2014 competition. The second experiment compares the performance of the proposed method using a recent benchmark MFO problem. We further extend the investigation into the analysis of parameter sensitivity and solicit insights pertaining to the algorithm characteristics. Overall, the empirical results on various benchmark problems are promising. The third experiment offers a solution to a multi-mode resource-constrained project scheduling problem in the real-world construction industry. The results indicate improvements of 2.29% in project quality and 8.23% in project duration subject to an increase of 4.78% in project cost, which are well within the acceptance limits of the decision makers.

Analytical transient analysis of temporal boundary value problems using the d'Alembert formula.

Temporal boundary value problems (TBVPs) provide the foundation for analyzing electromagnetic wave propagation in time-varying media. In this paper, we point out that TBVPs fall into the category of unbounded initial value problems, which have traveling wave solutions. By dividing the entire time frame into several subdomains and applying the d'Alembert formula, the transient expressions for waves propagating through temporal boundaries can be evaluated analytically. Moreover, unlike their spatial analogs, TBVPs are subject to causality. Therefore, the resulting analytical transient solutions resulting from the d'Alembert formula are unique to temporal systems.

Approaching Identity Problems Common in Clinical Practice.

The concept of identity is pervasive in psychology and culture, but clinicians have lacked a conceptual framework for addressing problems related to identity. After reviewing the development of identity, I distinguish four of the most common categories of such problems and consider approaches to each: identity diffusion, distorted identity, threats to identity, and difficulty integrating disparate aspects of one's identity. While making identity a focus of clinical attention can strengthen the alliance and place the treatment within a larger context, doing so raises moral questions about the clinician's role as an agent of validation or change.

Regulating Hooligans and Mawaalis: Collective Action and the Politics of Public Order in Late Colonial India

In 1938, a communal conflict took place in the city of Bombay. This confrontation between Hindus and Muslims flared into large-scale violence. During the riots, the home minister of the provincial government invoked a combination of laws such as Section 144 of the Code of Criminal Procedure and instituted curfews to control the situation. As a result, hundreds of inhabitants of the city were arrested. The purpose of this article is threefold. Firstly, it will highlight how communal conflict in the late colonial period would often begin over trivial issues but could easily expand into large-scale riots influenced by metapolitical concerns. Secondly, moments of ‘disorder’ facilitated the administrative urge to institute extraordinary laws like Section 144 and curfews. And thirdly, the invocation of extraordinary laws was justified in reference to various problem categories like mawaalis and hooligans in this case. Overall, the article will show that the provincial government led by Indians continued the colonial art of governance by resorting to repression as a significant tool to deal with political unrest.

A Taxonomy of Food Supply Chain Problems from a Computational Intelligence Perspective.

In the last few years, the Internet of Things, and other enabling technologies, have been progressively used for digitizing Food Supply Chains (FSC). These and other digitalization-enabling technologies are generating a massive amount of data with enormous potential to manage supply chains more efficiently and sustainably. Nevertheless, the intricate patterns and complexity embedded in large volumes of data present a challenge for systematic human expert analysis. In such a data-driven context, Computational Intelligence (CI) has achieved significant momentum to analyze, mine, and extract the underlying data information, or solve complex optimization problems, striking a balance between productive efficiency and sustainability of food supply systems. Although some recent studies have sorted the CI literature in this field, they are mainly oriented towards a single family of CI methods (a group of methods that share common characteristics) and review their application in specific FSC stages. As such, there is a gap in identifying and classifying FSC problems from a broader perspective, encompassing the various families of CI methods that can be applied in different stages (from production to retailing) and identifying the problems that arise in these stages from a CI perspective. This paper presents a new and comprehensive taxonomy of FSC problems (associated with agriculture, fish farming, and livestock) from a CI approach; that is, it defines FSC problems (from production to retail) and categorizes them based on how they can be modeled from a CI point of view. Furthermore, we review the CI approaches that are more commonly used in each stage of the FSC and in their corresponding categories of problems. We also introduce a set of guidelines to help FSC researchers and practitioners to decide on suitable families of methods when addressing any particular problems they might encounter. Finally, based on the proposed taxonomy, we identify and discuss challenges and research opportunities that the community should explore to enhance the contributions that CI can bring to the digitization of the FSC.

Child Sexual Abuse and Problems Reported by Survivors of CSA: A Meta-Review

ABSTRACT A systematic meta-review of reviews and meta-analyses on problems reported by survivors of Child Sexual Abuse (CSA) was conducted. The aim was to comprise a comprehensive overview of 1) problems reported by survivors of CSA, and 2) variables moderating these relations. Two raters independently conducted a search through PubMed, PsychINFO, Campbell Library, Cochrane Library and Web of Science. Twenty-five reviews and meta-analyses reporting on 53 problems related to CSA were analyzed. All fell into five domains: medical, psychological, sexual, repeated (self-)harm, and a final category of other problems. Thirty-six of all problems (68%) were consistently and significantly more commonly reported by CSA survivors as compared to individuals without a history of CSA. Most moderator analyses did not significantly influence these relationships. In conclusion, CSA is associated with various problems across different domains and overall, these problems are prevalent independent of specific characteristics of and circumstances surrounding the abuse.

Practical and Emotional Problems Reported by Users of a Self-guided Digital Problem-solving Intervention During the COVID-19 Pandemic: Content Analysis.

BackgroundTo better direct assessments and interventions toward the general population during both the ongoing COVID-19 pandemic and future crises with societal restrictions, data on the types of practical and emotional problems that people are experiencing are needed.ObjectiveThe aim of this study was to examine the types of practical and emotional problems that the general population is experiencing during the COVID-19 pandemic and to construct an empirically derived inventory based on the findings.MethodsA total of 396 participants, recruited among members of the general public in Sweden who were experiencing practical and/or emotional problems during the pandemic, accessed a self-guided digital problem-solving intervention for a period of 1 week to report and solve the problems they experienced. Prior to accessing the intervention, the participants completed a short self-assessment regarding symptoms of depression and anxiety. Content analysis was used to account for the types of problems participants reported. A set of items for an inventory was later proposed based on the problem categories derived from the analysis.ResultsA majority of participants had clinically relevant symptoms of either depression or anxiety. The problems reported were categorized as 13 distinct types of problems. The most common problem was difficulty managing daily activities. Based on the categories, a 13-item inventory was proposed.ConclusionsThe 13 types of problems, and the proposed inventory, could be valuable when composing assessments and interventions for the general population during the ongoing pandemic or similar crises with societal restrictions. The most common problem was of a practical nature, indicating the importance of including examples of such problems within assessments and interventions.Trial RegistrationClinicalTrials.gov NCT04677270; https://clinicaltrials.gov/ct2/show/NCT04677270

A numerical approach for a class of nonlinear optimal control problems with piecewise fractional derivative

In this study, a kind of piecewise fractional derivatives based on the Caputo fractional derivative is used to define a novel category of fractional optimal control problems. The piecewise Chebyshev cardinal functions as an appropriate family of basis functions are considered to construct a numerical method for solving such problems. The classical and piecewise fractional derivative matrices of these basis functions are derived and used in constructing the proposed technique. The established scheme transforms obtaining the solution of such problems into finding the solution of algebraic systems of equations by approximating the state and control variables using the mentioned basis functions. The accuracy of the expressed approach is investigated by solving some examples.

О задаче и алгоритмах согласованного оптимального управления производством и материальными потоками предприятия

At present, any unified approach that would allow solving the problems of coordinated optimal control of input and output material flows and production has not been implemented in the theory and practice of managing technological and organizational systems. The works published in this area are often aimed at solving specific problems. When attempting a complex solution the declared systemicity is either indicated only in words, or is implemented heuristically by gluing the constituent components without discussing and analyzing the effectiveness and, moreover, proof. This article, based on the earlier works of the authors, develops an apparatus of coordinated optimal control of all logically related subsystems. A formal setting created for this purpose is a discrete optimization problem and it takes into account all the main factors of production and movement of material flows. A special algorithm for an approximate solution is constructed, which transfers the created problem from the category of NP-hard problems to the category of polynomially solvable ones. The formal setting contains logical conditions for choosing from a variety of parameters, including sources and directions of flows, conditions of supply, volumes and dynamics of production, and determination of optimal prices at the output. Thus, the restrictions systematically take into account both production components and restrictions on resources and the logic of movement of input and output material flows. A maximum net profit at the end of the planning period was used as a criterion for the effectiveness of all processes. The considered model and control problems are investigated using a unified approach that allows working with logical conditions of any complexity and setting appropriate formal optimization problems. The results of testing the algorithm on test data close to real dimensions are also given.

Characterizing the reach of comprehensive medication management in a population health primary care model.

As care teams adopt team-based models of care, it is important to examine the reach of interdisciplinary services, such as pharmacists providing comprehensive medication management (CMM). This study examined the reach of pharmacist-delivered CMM in the first 10 months of a population health-focused primary care transformation (PCT). Using electronic health record data, descriptive statistics (counts and percentages, as well as means and standard deviations) were quantified to summarize the patients who received CMM in two PCT pilot clinics pre- and post-PCT. Patients who had at least one CMM visit increased from 554 during the pre-PCT window to 880 during the post-PCT window. However, when adjusted for the increased pharmacist full-time equivalents (FTE) included as part of the PCT, 462 and 330 patients/FTE were seen in the pre- vs post-PCT periods, respectively. When calculating the percentage of patients who received CMM, this increased from 2.3% of all primary care patients seen in the two pilot clinics before the PCT began to 4.4% after the PCT was implemented. Most patient demographics remained largely the same between the pre- and post-PCT periods. However, CMM patients seen in the post-PCT period had more medication therapy problems across all medication therapy problem categories compared to patients in the pre-PCT period. Additionally, patients receiving CMM had significantly more conditions and medications and higher hospitalizations and emergency department use compared to the general clinic population. Reach is an important implementation outcome to determine the representativeness of individuals participating in a given service. This study illustrates that pharmacists providing CMM see complex patients with a high propensity for medication therapy problems. However, opportunities exist to improve the reach of CMM and, in turn, enhance team-based care.

Enhanced Hyper-Cube Framework Ant Colony Optimization for Combinatorial Optimization Problems

Solving of combinatorial optimization problems is a common practice in real-life engineering applications. Trusses, cranes, and composite laminated structures are some good examples that fall under this category of optimization problems. Those examples have a common feature of discrete design domain that turn them into a set of NP-hard optimization problems. Determining the right optimization algorithm for such problems is a precious point that tends to impact the overall cost of the design process. Furthermore, reinforcing the performance of a prospective optimization algorithm reduces the design cost. In the current study, a comprehensive assessment criterion has been developed to assess the performance of meta-heuristic (MH) solutions in the domain of structural design. Thereafter, the proposed criterion was employed to compare five different variants of Ant Colony Optimization (ACO). It was done by using a well-known structural optimization problem of laminate Stacking Sequence Design (SSD). The initial results of the comparison study reveal that the Hyper-Cube Framework (HCF) ACO variant outperforms the others. Consequently, an investigation of further improvement led to introducing an enhanced version of HCFACO (or EHCFACO). Eventually, the performance assessment of the EHCFACO variant showed that the average practical reliability became more than twice that of the standard ACO, and the normalized price decreased more to hold at 28.92 instead of 51.17.