Problem Resolutions Research Articles

Klausul Arbitrase dan Kewenangan Absolut Lembaga Arbitrase dalam Praktek Penyelesaian Sengketa di Luar Pengadilan

In Indonesia, the settlement of disputes through arbitration is regulated by Law no. 30 of 1999 concerning Arbitration and Alternative Problem Resolutions. Article 7 Law no. 30 of 1999 stipulates that the parties can agree to an agreement on a dispute that has occurred or will occur between them to be resolved through arbitration with a written agreement agreed upon by the parties. In the selection of arbitral settlement there is a link between the arbitration clause and the selection of settlement through arbitration as well as the implementation of absolute authority and the selection of arbitral institutions in the practice of dispute resolution outside the court. The approach method used is normative juridical. The results of the study state that the choice of arbitration as a dispute resolution is based on a contract in accordance with what is implied in Article 7 and Article 9 paragraph (1) of Law Number 30 of 1999, and in this case the parties to the agreement agree to include an arbitration clause, The court is bound by the agreement made by the parties, with the provisions of the article, the absolute competence of arbitration is born when the parties expressly choose to resolve disputes through an arbitration forum where this has been accommodated in Article 3, Article 4, Article 10 and Article 11 paragraphs (1) and (2) in Law Number 30 of 1999 concerning Arbitration and Alternative Dispute Resolution, which negates the authority of court institutions to examine cases that are already bound by an arbitration clause.

Novel approach to energy consumption estimation in smart homes: application of data mining and optimization techniques

Buildings account for a significant portion of total energy consumption, and the introduction of intelligent buildings represents a significant step forward in efficiently managing energy utilization. The proposed solutions represent a significant step forward in the development of intelligent residential environments. Beginning the process of achieving improved building intelligence necessitates a thorough evaluation and prediction of the necessary heating and cooling energy requirements, taking into account all relevant influencing factors. This study describes methodologies for using data mining models to predict the heating and cooling energy requirements of intelligent buildings during the construction phase. Data mining techniques, specifically Support Vector Machines (SVM) and Random Forest, are used, demonstrating their superior efficiency over alternative methods. Metaheuristic algorithms, particularly the Owl Search Algorithm (OSA), are described as effective tools for optimizing results across a wide range of problem resolutions. OSA is described and proposed alongside novel data mining methods, demonstrating that this combination of algorithms improves the performance of Random Forest and SVM-based models by 11% and 24%, respectively. The proposed models can generate predictions with a small number of parameters, eliminating the need for complex software and tools. This user-friendly approach makes the prediction process more accessible to a wider audience. While specialized equipment and professional-grade tools will be used, the proposed models are accessible to a wide range of individuals interested in participating in the prediction process.

FRACTURE ANALYSIS AND SHIELDING EFFECTS IN ADVANCED MATERIALS

Due to their ability to interconnect electrical and mechanical domains, piezoelectric materials are increasingly finding applications in advanced electromechanical systems. Notably, magneto-electric composites like BaTiO3-CoFe2O4 have emerged as vital materials for the next generation of devices. Exploring this realm is a complex and significant endeavor, demanding the attention of the scientific community and further research. Over recent decades, the scope of formulating and executing computational models for continuous media has substantially broadened, encompassing a diverse array of material properties and fields in computational models. This article centers on the utilization of asymptotic analysis as a mathematical tool for constructing approximate equations and assessing the relevance of various hypotheses. It delves into the utilization of the perturbation method, pioneered by Kagadiy T. S. and others, to tackle two-dimensional contact problems in electropelasticity, particularly in the context of materials with linear anisotropy. The extensive applicability of this asymptotic approach underscores its efficacy in simplifying intricate problems by breaking them down into a sequence of boundary problem resolutions grounded in the theory of potentials. The collaborative effort of the authors in this research underscores that employing the mentioned method opens up avenues for formulating pertinent boundary problems for the fundamental equations. This, in turn, allows for the representation of the initial electropelasticity problem as a superposition of more manageable boundary problems. While mechanical and electrical components can be treated separately, they still interact via boundary conditions. To conduct a numerical analysis, the article examines scenarios where one crack surface slides parallel to the crack front against another and selects relevant materials with known characteristics. Calculations reveal that, even in the absence of mechanical load, crack surfaces undergo relative sliding due to non-zero electrical or magnetic fields. The study of the shielding effect, which mitigates crack motion by altering magnetic field distribution, holds particular significance. This effect reduces the overall stress intensity factor and impedes crack propagation. Conducting such a comprehensive analysis is pivotal for comprehending and foretelling the strength and reliability of structural components composed of piezoelectric and piezomagnetic materials. It is imperative to conduct a thorough examination of the mechanisms governing their failure.

Industry 4.0 and Chemical Industry: The Technology Enablers behind Strategic Growth of Chemical Companies

Abstract: Industry 4.0, also known as the fourth industrial revolution, focuses on various digital transformations within manufacturing units that help them improve their connections and networks, leading to better product evaluation according to the diversified and changing market. Connections are at the heart of the golden age: the link between a company and its related departments, people and products, and global relationships between consumers, suppliers, and producers. All stakeholders must communicate effectively and agree on best practices to ensure smooth daily operations and prompt problem resolutions to maximise the power and potential of such connections. Inculcating and reviewing the applications of Industry 4.0 aspects in a Chemical Industry is the subject of this paper. The paper would assist enterprises in understanding how digitalisation will help them increase production efficiency and integrate their business. It also explains the various enabling technologies under Industry 4.0 that help capture process data from industrial devices, connectivity for data captured, and business intelligence tools to convert that data into impact. This paper also emphasises the challenges associated with promoting Industry 4.0. Methodologies for putting the fourth revolution strategy into action in the chemical industry would be efficiently carried out as a result of this.

Environmental pollutants and their impact on COVID‐19 spread: Current problem and future resolutions

AbstractCOVID‐19 is the greatest crucial universal health issue of the century and the extreme challenge that came after the 2nd World War faced by humankind. In 2019, different strains of the coronavirus have emerged drastically, that as severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) which is the causative agent of corona disease. As far as human civilization history, there have been occurrences of severe diseases and outbreaks of various viruses. According to World Health Organization reports, throughout the world, the present outbreak of COVID‐19 has engulfed more than 200 countries affecting 241,471,559 individuals and more than 4,914,092 people lost their lives. SARS‐CoV‐2 outbreak is severely disturbing the worldwide economy at present. The urgent need of recent times is to understand the environmental aspect of COVID‐19 disease. Hence to fulfill this point, the present review article is compiled with a brief discussion about all the minute points of the COVID‐19 pandemic related to the environment: origin and present scenario, the occurrence of SARS‐CoV‐2 in environmental habitats, the effect of COVID‐19 on human health, and environment, environmental factors influencing the transmission and spreading of SARS‐CoV‐2. This review explains micro and macro pollutants in hospital and urban wastewater influencing COVID‐19, detection of SARS‐CoV‐2, current global drug strategies to control replication and spread of SARS‐CoV‐2 from the environment, future approaches, and guidelines to prevent and control upcoming pandemics. The SARS‐CoV‐2 structural details and their effect on humans have been already well presented but the research about environmental factors affecting COVID‐19 could be important points to fight present and future pandemics.

Detection and Localization of Closely Spaced Pipelines Using a 3-D Multistatic Subsurface SAR

Detection and localization of buried pipelines is an important problem for oil and water distribution industries as well as for excavation and construction companies. A novel 3D forward scattering model and dynamic grid search-based inversion algorithm of multiple buried pipelines using multistatic synthetic aperture radar (SAR) configuration is demonstrated in this article. Traditional imaging algorithms that focus the SAR signals by compensating only for the phase work well when the targets are far away from each other. By considering both the phase and amplitude of the scattered field and casting the inversion problem as an optimization problem, the detection and localization resolutions are improved for extended targets. A forward scattering model for multiple adjacent pipes is developed to track the scattering phase centers of each pipeline as the receiver location is changed. The model is used to calculate the resulting propagation phase and amplitude attenuation due to propagation in lossy media. The misfit between the measured data and the forward model is used as the cost function. The cost function is minimized by the dynamic grid search algorithm that starts with an initial focusing and then performs a more careful search to detect closely spaced pipelines. The forward model and inversion algorithm are validated and compared to a basic focusing algorithm using full-wave simulations as well as experimental data for both metallic as well as dielectric pipes. The results show improvement in range and cross range detection and localization resolutions over the basic SAR focusing algorithm.

Book Review: Challenges in Language Testing around the World: Insights for Language Test Users

Language testing has developed as a field that broadly extends to educational, societal and economic contexts (Yildiz, 2019). However, the past edited volumes grappling with the main themes in language testing are primarily exclusive and typically limited. Most insights are either heavily dominant to Western English-speaking countries or focused on problem resolutions. There is rarely any publication that unveils human infallibilities or misinterpretations in various contexts across countries. To address these gaps, Betty Lanteigne, Christine Coombe, and James Dean Brown jointly co-edit this book. These renowned scholars aim to focus on a broader view of conventional policy, test development, practice, and research. Against this backdrop, the insights-driven can be more meaningful and applicable to wider audiences. Indeed, this is an extraordinary book that highlights multiple perspectives in terms of choosing the authors, themes, and chapters.

Designing and Evaluating a Collaborative Knowledge Management Framework for Leaf Disease Detection

Knowledge Management (KM) has become a dynamic concept for inquiry in research. The management of knowledge from multiple sources requires a systematic approach that can facilitate capturing all important aspects related to a particular discipline, several KM frameworks have been designed to serve this purpose. This research aims to propose a Collaborative Knowledge Management (CKM) Framework that bridges gaps and overcomes weaknesses in existing frameworks. The paper also validates the framework by evaluating its effectiveness for the agriculture sector of Pakistan. A software LCWU aKMS was developed which serves as a practical implementation of the concepts behind the proposed CKMF framework. LCWU aKMS served as an effective system for rice leaf disease detection and identification. It aimed to enhance CKM through knowledge sharing, lessons learned, feedback on problem resolutions, help from co-workers, collaboration, and helping communities. Data were collected from 300 rice crop farmers by questionnaires based on hypotheses. Jennex Olfman model was used to estimate the effectiveness of CKMF. Various tests were performed including frequency measures of variables, Cronbach’s alpha reliability, and Pearson’s correlation. The research provided a KMS depicting KM and collaborative features. The disease detection module was evaluated using the precision and recall method and found to be 94.16% accurate. The system could replace the work of extension agents, making it a cost and time-effective initiative for farmer betterment.

An Approach to Determining the Need for Integrating Quality Management into Industrial PLM Implementation

In practice, companies use different tools and systems to plan and manage product and process quality. Most of these tools and systems are disconnected from product data/information management systems. The downside of disconnected tools for quality management is that the repeating issues that appear in multiple systems can obscure root cause investigations by isolating related data elements, with no means to understand relationships among them. Redundant work identifying and resolving quality issues can happen in multiple tools without an automated way to communicate knowledge learnt to other teams. This leads to inconsistent and incomplete problem resolutions that impede, not improve, product and process quality. In the recent development of new technologies, many IT tools have become available on the market and among them are the PLM systems proving very popular among companies which enable the creation and maintenance of complex industrial products. A comprehensive solution in the PLM Platform is presented in this paper that aims to link quality to product design, manufacturing planning, and business-critical processes such as change management. The approach provides cross-disciplinary teams and the extended supply chain with powerful closed-loop capabilities to identify and manage risk, improve quality, meet customer requirements, and attain environmental, safety, and information management compliance.

Simulation of Teacher Interventions in a Training Course of Mathematics Teacher Educators

This work aimed to characterize simulated teacher interventions to manage a didactic configuration in which students solve problem situations using an ICT resource. We also aimed to identify patterns of interaction between the teacher and the students that make it possible to characterize styles of interaction and assess both their interactional and their ecological suitability. To do this, we used the tools of the Onto-semiotic Approach to Mathematical Cognition and Instruction to analyze the level of reflection of 102 educators of preservice teachers of mathematics, about hypothetical problem resolutions of their students and the types of interactions simulated by them to manage the students’ learning. The educators were participants of a Teacher Training of the Teacher Specialization in Education and ICT in Argentina. The results show that there are three levels of reflection and four types of interaction (maieutic, falsificationist, dogmatic and paternalistic). We did not find a high interactional suitability in their proposals of dialogues, and participants do not consider aspects of the ecological suitability, such as the adaptation to the official curriculum. We conclude that the type of interventions that teacher educators propose is closely related to their level of reflection about the reasons why their students respond to problems in one manner or another.

Economic Impacts of Violent Conflicts in Nasarawa State, Nigeria

The study analysed the impacts of violent conflicts on the economies of rural communities in Nasarawa State, Nigeria. Primary data were collected from the respondents using a structured interview schedule, while focus group discussions (FGD) sessions were employed to assess effects of conflicts on communities. Data were analysed using simple descriptive statistics, alternative resource cost estimation (ARCE) and content analysis while the Likert scale was used to measure the perception of respondents towards the causes of conflicts. There were six (6) major categories of conflicts identified in the area. These categories were communal conflicts, ethnic conflicts, resource conflicts (most often land conflicts), politically motivated conflicts, conflicts due to traditional chieftaincy, and the conflicts between state forces and militia groups. Expansion of agro-pastoralism (4.6) and Extensive sedentism (4.5) were very serious factors that were perceived to lead to conflicts. A total of ₦2,289,859,549 worth 30.28% of the State’s 2018 IGR (Internal Generated Revenue) were lost in these conflicts. It was recommended that laws regarding people with diverse backgrounds and socioeconomic needs and population growth in relation to limited resources should be developed with great care and attention paid to all the parties involved in the process. Participatory approaches to problem identification, conflict management and resolutions need to be established in the communities with regular interactions between and among locals periodically and frequently.

Decluttering the problem list in electronic health records.

The purpose of this study was to evaluate the current state of problem list maintenance at an academic medical center. We included problem list data for patients who had at least 2 face-to-face encounters at Vanderbilt University Medical Center or its clinics between January 1, 2018, and December 31, 2019. We used the frequency of problem list additions, resolutions, deletions, duplicate problems (exact and SNOMED CT duplicates), inconsistencies (contradicting stages of disease state), and items that could be documented elsewhere in the electronic health record as surrogate markers of problem list maintenance. Descriptive statistics were used to summarize the results. A total of 546,510 patients met inclusion criteria. There were 3,762 (0.7%) patients who had the exact same active problem listed more than once. SNOMED CT code duplications occurred in the records for 56,399 (10.5%) patients. Of the patients with asthma, 2.5% (223/8,779) had contradicting asthma stages active on their problem list, and 6.4% (950/14,950) of patients with chronic kidney disease (CKD) had contradicting CKD stages. In addition, 17,205 (3.1%) patients had 20,365 active family history problems and 39,464 (7.2%) patients had an allergy documented on their problem list. On average, there were 43.7 (95% confidence interval [CI], 14-73.4) additions, 8.7 (95% CI, 0.1-17.4) resolutions, and 2.1 (95% CI, 0-4.6) deletions of problems per 100 face-to-face encounters, inpatient or outpatient. Our study suggests areas for improvement for problem list maintenance. Further studies into semantic duplication and clinical decision support tools to encourage problem list maintenance and deduplication are needed.

IBM Predictive Analytics Reduces Server Downtime

IBM has deployed its Predictive Analytics for Server Incident Reduction (PASIR) solution to more than 360 information technology (IT) environments worldwide since 2013. These environments, covering sectors from banking to travel to e-commerce, are serviced by IBM support groups. Incidents occurring on servers, including problem descriptions and resolutions, are documented in client account-specific ticket management systems. PASIR uses machine learning to classify the incident tickets within an IT environment and identify high-impact incidents that involve server outages by using the respective ticket descriptions and resolutions. It then correlates these high-impact tickets with server properties and utilization measurements to identify problematic server configurations. Finally, for such configurations, PASIR uses statistical multivariate analysis and simulation methods to prescribe improvement and modernization actions. In this paper, we present the results achieved from deploying this solution. We describe the PASIR approach, from ticket classification to the recommendations of remediation actions (e.g., hardware and software upgrades). We demonstrate the model’s effectiveness by comparing predictions on the impact of prescriptive actions with actual system improvements. Since 2013, we have applied PASIR to more than 840,000 client servers, resulting in more precise upgrade spending and environmental stability, thus saving our clients an estimated $7 billion.

Exploring Coordinative Mechanisms for Environmental Governance in Guangdong-Hong Kong-Macao Greater Bay Area: An Ecology of Games Framework

To solve regional environmental problems, there is a trend of establishing urban agglomerations and formulating cooperative policy institutions in China. The extant studies on policy institutions largely focus on the coordinative mechanisms of multiple actors within one single institution. Only a few studies have tried to understand how different policy institutions are interlinked and mutually affected to influence actors’ decisions and problem resolutions. This article applies a network-based analytical approach and adopts the Ecology of Games Framework to explore how regional environmental governance is coordinated in the Guangdong-Hong Kong-Macao Greater Bay Area. It was found that coordinative mechanisms in regional environmental governance can happen around three elements: policy institutions, policy actors, and policy issues. Policy institutions tend to serve as an umbrella for many diverse and interdependent activities and actors within individual institutions. Additionally, positive externalities emerging between different policy institutions perform as coordinators across institutions. For actors, state-level actors usually play as facilitators of policy institutions while they are not active in participating in policy games in later phases; it is regional actors, particularly from Guangdong, that are active in the operation of policy institutions. For policy issues, they emerge because they are often tied with each other, and some of them play as the common ground for seemly separating policy institutions.

Embracing the Complexity: Surfacing Problem Situations with Multiple Actors of the Pineapple Value Chain in Uganda

The complexity of local situations in which agricultural value chains are enacted requires a systemic understanding when seeking to improve interlinked livelihoods. Studying the fresh pineapple value chain in Uganda offers an illustrative example. Individually negotiated and context-specific actor relationships, along with their connected activities can be revealed by conceptualizing the chain as a purposeful human activity system. We followed a systems learning approach to elicit value chain actors’ perspectives on factors influencing their activities while surfacing relevant problem situations, resolutions and constraints. Participatory methods, including cognitive mapping, were used to spark dialogue during meetings with only farmers, traders and brokers and also with mixed groups. The results present the multiple natural, technical and social factors identified by value chain actors leading to losses and benefits to their income. System driving and shaping influences included infrastructure, seasonality, perishability and weather conditions. Process-oriented analysis of multi-stakeholder discussions revealed feedback cycles related to fragmentation of the chain. This resulted from and contributed to problematic communication, price fluctuations and challenges in actor relations. For example, actors proposed uniform pricing and debated the implications. Although the systemic perspective brought forward actors’ awareness of potential benefits of improved collaboration and recognition of interdependent activities, it also exposed barriers. Participatory systems learning helped to capture actors’ room of maneuver, and can support processes towards actor-driven change.

The enduring challenge of ‘wicked problems’: revisiting Rittel and Webber

There is, in the twenty-first century, an intense interest in the nature of wicked problems and the complex tasks of identifying their scope, viable responses, and appropriate mechanisms and pathways towards achieving improvement. This preoccupation is timeless, but the discussion over several decades has benefited from Rittel and Webber’s (Policy Sci 4(2):155–169, 1973) path breaking conceptualisation of wicked problems and the political argumentation needed to resolve them. This review revisits Rittel and Webber’s work and its enduring significance, reflecting upon its broad uptake and impact in the policy sciences, an impact that continues to grow over time. We revisit how the classic 1973 paper came to be published in Policy Sciences, its innovative depiction of social problems, its rejection of rationalistic design, its acknowledgement of the subjectivities involved in problem identification and resolutions, and the consequent need for argumentative-based solution processes. We find great resonance in the paper with contemporary problem solving preoccupations, not least that the political context is crucial, that argumentation must be transparent and robust, and that policy interventions may have consequences that cannot be easily controlled in open and highly pluralised social systems.

Checklist of Gymnotiformes (Osteichthyes: Ostariophysi) and catalogue of primary types

ABSTRACT A list of all valid names of species of Neotropical electric fishes (Gymnotiformes) is presented herein. The list is arranged by family and genus and includes all available synonyms. The list is comprehensive through 2016 and includes 240 valid species distributed among 34 genera and five families, including one monotypic genus known only from the fossil record. The presented classification reflects recently published interpretations about the validity of the included names which, in general, are widely accepted. When the validity of a particular name is disputed in recent literature, we followed one of the published interpretations and provide relevant information on the alternate interpretation(s) in the remarks section of that name. Synonymies of some names need to be considered tentative, inasmuch as the types underlying those names are either absent or appear to be based on more than one taxon. First reviser actions (e.g., lectotype and neotype designations, resolution of simultaneous synonyms, etc.) are reported and include erroneous subsequent attempts at problem resolutions. Herein, we include one new first reviser action by selecting Gymnotus aequilabiatus Humboldt, 1805, as type species of Sternopygus because previous attempts to select a type did not follow the provisions of the Code of Zoological Nomenclature.

Resolution Recommendation for Event Tickets in Service Management

In recent years, IT service providers have rapidly achieved an automated service delivery model. Software monitoring systems are designed to actively collect and signal event occurrences and, when necessary, automatically generate incident tickets. Repeating events generate similar tickets, which in turn have a vast number of repeated problem resolutions likely to be found in earlier tickets. In this paper, we develop techniques to recommend appropriate resolution for incoming events by making use of similarities between the events and historical resolutions of similar events. Built on the traditional k-nearest neighbor algorithm (KNN), our proposed algorithms take into account false positives often generated by monitoring systems. An additional penalty is incorporated into the algorithms to control the number of misleading resolutions in the recommendation results. Moreover, as the effectiveness of the KNN heavily relies on the underlying similarity measurement, we proposed two other approaches to significantly improve our recommendation with respect to resolution relevance. One approach uses topic-level features to incorporate resolution information into the similarity measurement; the other uses metric learning to learn a more effective similarity measure. Extensive empirical evaluations on three ticket data sets demonstrate the effectiveness and efficiency of our proposed methods.

A review of two-sided assembly line balancing problem

Assembly line balancing (ALB) is concerned with assigning tasks within an assembly line to meet the required production rate for optimization purposes. On the other hand, two-sided ALB performs double-sided assembly operation on a single assembly line. In this paper, we have focused the survey on two-sided assembly line balancing (2S-ALB) research problems. The numerous factors mentioned in 2S-ALB literature were actually based on problem resolutions, and this paper will quote any preferred literature considering the frequent citation. In particular, this review explores in detail the ALB problems, optimization methods, objective functions, and specific constraints used in solving 2S-ALB problems. Among the purposes of ALB problems is that it traditionally focuses on simple ALB with various engaging approaches. General ALB comes second because of its complexity and nondeterministic polynomial (NP)-hard-classified problems. However, due to the current manufacturing issues, GALB problems, such as 2S-ALB, are forced to be examined and this comprehensive literature will specify anything necessary for the optimization purposes. Finally, future research direction has been discovered and put forward as the suggestion.

Customers experience and problem resolutions in retail banking. Some empirical evidence from Italian banking

Currently, few studies have investigated how bank-specific determinants affect customer experience in retail banking. The objective of this paper is twofold: to provide a literature review about customer dissatisfaction in retail banking and to shed more light on different behaviours of banks regarding customer complaints. Our hypotheses are tested on a large sample of Italian banks on problem resolutions performance measured from 2012 to 2014, using bank-level balance sheets and appeals to Arbitro Bancario e Finanziario. We detected differences in the complaints management of different types of banks during turbulent financial market conditions. We compared bank size and bank legal form as possible sources of organisational friction studying their impact on the likelihood of customer dissatisfaction. Our findings highlight that, the small banks and cooperative banks are less inclined to have retail customers with dissatisfaction than large banks and joint-stock banks.