Building a Business and Strategic Intelligence Policy as a Strategy for Promoting Congolese Business Progress and Healthy Economic Development in Eastern DRC

The aim of this study was to verify the existence of business and strategic intelligence policies at the level of Congolese companies and at the state level, likely to foster progress and healthy development in the east of the DRC. The study was based on a mixed perspective consisting of objective analysis of quantitative data and interpretative analysis of qualitative data. The results showed that business and strategic intelligence policies have not been established at either company or state level, as this is an area of activity that is not known to the players in companies and public departments, and there are no units or offices in their organizational structures responsible for managing strategic information for competitiveness on the international market. In addition, there is a real need to establish strategic information management units within companies, upstream, and to set up a national strategic information management department or agency to help local companies compete in the marketplace, downstream. This reflects the importance and timeliness of building business and strategic intelligence policies to ensure economic progress and development in the eastern DRC. Business and strategic intelligence provides companies with an appropriate tool for researching, collecting, processing and disseminating information useful for decision-making among stakeholders, in order to cope with a crisis or competitive situation. The study suggests a number of key recommendations based on its findings. To the government, it is recommended to establish the national policy of business and strategic intelligence by setting up a national agency of strategic intelligence in favor of local companies;and to companies to establish business intelligence units in their organizational structures in favor of stakeholders to foster advantageous decision-making in the competitive market and achieve progress. Finally, the study suggests that studies be carried out to fully understand the opportunities and impact of business and strategic intelligence in African countries, particularly in the DRC.

Crossing the Achilles Heel of Algorithms:Identifying the Developmental Dilemma of Artificial Intelligence-Assisted Judicial Decision-Making

In the developmental dilemma of artificial intelligence(AI)-assisted judicial decision-making,the technical architecture of AI determines its inherent lack of transparency and interpretability,which is challenging to fundamentally improve.This can be considered a true challenge in the realm of AI-assisted judicial decision-making.By examining the court’s acceptance,integration,and trade-offs of AI technology embedded in the judicial field,the exploration of potential conflicts,interactions,and even mutual shaping between the two will not only reshape their conceptual connotations and intellectual boundaries but also strengthen the cognition and re-interpretation of the basic principles and core values of the judicial trial system.

Beyond Algorithms: A Comprehensive Analysis of AI-Driven Personalization in Strategic Communications

This comprehensive study investigates the multifaceted impact of AI-powered personalization on strategic communications, delving deeply into its opportunities, challenges, and future directions. Employing a rigorous mixed-methods approach, we conduct an in-depth analysis of the effects of AI-driven personalization on audience engagement, brand perception, and conversion rates across various industries and communication channels. Our findings reveal that while AI-powered personalization significantly enhances communication effectiveness and offers unprecedented opportunities for audience connection, it also raises critical ethical considerations and implementation challenges. The study contributes substantially to the growing body of literature on AI in communications, offering both theoretical insights and practical guidelines for professionals navigating this rapidly evolving landscape. Furthermore, we propose a novel framework for ethical AI implementation in strategic communications and outline a robust agenda for future research in this dynamic field.

DECISION-MAKING OF SLICING SCHEME IN FUSED DEPOSITION MODELING PROCESS BASED ON ANALYTICAL HIERARCHICAL PROCESS

Based on analyzing the influences of a slicing scheme on stair-stepping effect, supporting structure, efficiency and deformation, etc. , analytical hierarchical process （AHP） combining with fuzzy synthetic evaluation is introduced to make decision in slicing schemes for a processing part. The application in determining the slicing scheme for a computer mouse during prototyping shows that the method increases the rationality during decision- making and improves quality and efficiency for the prototyping part.

Aspect based sentiment analysis using multi-criteria decision-making and deep learning under COVID-19 pandemic in India

The COVID-19 pandemic has a significant impact on the global economy and health.While the pandemic continues to cause casualties in millions,many countries have gone under lockdown.During this period,people have to stay within walls and become more addicted towards social networks.They express their emotions and sympathy via these online platforms.Thus,popular social media(Twitter and Facebook)have become rich sources of information for Opinion Mining and Sentiment Analysis on COVID-19-related issues.We have used Aspect Based Sentiment Analysis to anticipate the polarity of public opinion underlying different aspects from Twitter during lockdown and stepwise unlock phases.The goal of this study is to find the feelings of Indians about the lockdown initiative taken by the Government of India to stop the spread of Coronavirus.India-specific COVID-19 tweets have been annotated,for analysing the sentiment of common public.To classify the Twitter data set a deep learning model has been proposed which has achieved accuracies of 82.35%for Lockdown and 83.33%for Unlock data set.The suggested method outperforms many of the contemporary approaches(long shortterm memory,Bi-directional long short-term memory,Gated Recurrent Unit etc.).This study highlights the public sentiment on lockdown and stepwise unlocks,imposed by the Indian Government on various aspects during the Corona outburst.

STRATEGIC ENVIRONMENTAL ASSESSMENT FOR SUSTAINABLE DEVELOPMENT IN URBANIZATION PROCESS IN CHINA

This paper reviewed the development of Strategic Environmental Assessment (SEA) in China, expounded its functions and regional characteristics, and discussed the targets of SEA in the process of urbanization,and the main assessment indicators, procedures, techniques and methodologies of SEA. It concluded that SEA could be improved by the following recommendations: incorporating SEA in decision-making process, selecting experimental units for SEA trial run, and developing strategic evaluation tools and techniques. SEA can provide appropriate and up-to-date information on the impact of human activity on environment in the process of urbanization, and develop a plan of action targeting implementation of intervention for the rehabilitation and preservation of the ecological stability of a city. Therefore, SEA can be a supporting tool for decision-making toward achieving sustainable development.

COLLISION AVOIDANCE DECISION-MAKING MODEL OF MULTI-AGENTS IN VIRTUAL DRIVING ENVIRONMENT WITH ANALYTIC HIERARCHY PROCESS

Collision avoidance decision-making models of multiple agents in virtual driving environment are studied. Based on the behavioral characteristics and hierarchical structure of the collision avoidance decision-making in real life driving, delphi approach and mathematical statistics method are introduced to construct pair-wise comparison judgment matrix of collision avoidance decision choices to each collision situation. Analytic hierarchy process （AHP） is adopted to establish the agents＇ collision avoidance decision-making model. To simulate drivers＇ characteristics, driver factors are added to categorize driving modes into impatient mode, normal mode, and the cautious mode. The results show that this model can simulate human＇s thinking process, and the agents in the virtual environment can deal with collision situations and make decisions to avoid collisions without intervention. The model can also reflect diversity and uncertainly of real life driving behaviors, and solves the multi-objective, multi-choice ranking priority problem in multi-vehicle collision scenarios. This collision avoidance model of multi-agents model is feasible and effective, and can provide richer and closer-to-life virtual scene for driving simulator, reflecting real-life traffic environment more truly, this model can also promote the practicality of driving simulator.

Decision-Making in a Governmental Healthcare Organization by Analytic Hierarchy Process

This paper contains research on strategic decision-making in a local government. In a profit-oriented organization, the option that maximizes profits tends involve reaching an agreement between stakeholders. However, there is tendency for stakeholders to differ in their beliefs as to what is desirable particularly in a non-profit organization. In a local government, it is especially difficult for the interests of a stakeholder group to be completely in agreement. This research considers the use of the analytical hierarchy process （Saaty, 1971） as a solution for one of the difficulties of decision-making in a local government. This research is a case study to explore the strategy of a local Japanese healthcare management organization. The conclusion was drawn to decide which strategic option should be taken by using the analytical hierarchy process. Also, it was found what to work on a countermeasure that prevents the negative effects that are generated by selecting the strategic option.

Studies on Multi-Criteria Decision-Making-Based Healthcare Systems Using the Machine Learning

There is a lot of information in healthcare and medical records.However,it is challenging for humans to turn data into information and spot hidden patterns in today’s digitally based culture.Effective decision support technologies can help medical professionals find critical information concealed in voluminous data and support their clinical judgments and in different healthcare management activities.This paper presented an extensive literature survey for healthcare systems using machine learning based on multi-criteria decision-making.Various existing studies are considered for review,and a critical analysis is being done through the reviews study,which can help the researchers to explore other research areas to cater for the need of the field.

Process Auxiliary Decision-making Based on Rough Sets and Regulation Distance Computing

Computer aided process planning（CAPP） is an important content of computer integrated manufacturing, and intelligentizing is the orientation of development of CAPP. Process planning has characters of empirical and time-consuming to finalize, and the same technical aim always can be achieved by different process schemes, so intelligentizing of process decision making always be a difficult point of CAPP and computer integrated manufacturing （CIM）. For the purpose of intelligent aided process decision making and reuse of process resource, this paper proposed a decision making method based on rough sets（RS） and regular distance computing. The main contents and methods of process planning decision making are analyzed under agile response manufacturing environment, the concept of process knowledge granule is represented, and the methods of process knowledge granule partitioning and granularity analysis are put forward. Based on the theory of RS and combined the method of process attributes importance identification, the paper brought forward a computing model for process scheme regulation distance under the same attribute conditions, and conflict resolution strategy was introduced to acquire process scheme fit for actual situation of enterprise＇s manufacturing resources, so as to realize process resources＇ conflict resolution and quick excavate and reuse of enterprises＇ existing process knowledge, to advance measures of process decision making and improve the rationality and capability of agile response of process planning.

A decision-making model of gear process for green manufacturing

A decision-making model of gear process for green manufacturing is presented, which integrates the five objectives including the time, quality, cost, resource consumption and environmental impact of gear process together into the development of a strategy. Mathematical description is provided for the multi-objectives decision-making model. The expert judgment and the multi-fuzzy assessment theory are introduced to do sensible comparisons and give quantitative results. A case study on practical cutting tool selection in gear machining demonstrates that the proposed model is applicable.

The Decision-Making Processes of the Agents Belonging to the Biodiesel Production Chain in Southern Brazil

The aim of this paper is to present and analyze the factors, motivations and criteria considered in the decision-making processes of the actors belonging to the biodiesel production chain in Brazil. The biodiesel production chain consists of three main agents： the farmers, the soybean processing plants and the oil refinery/distributor. For the farmers organized in cooperatives the central decision is whether to sell oil-bearing crops for the production of biodiesel. In contrast, for the soybean processing plants that convert the crops into vegetable and/or biodiesel, the decision to produce this fuel is based on the wish to expand their market portfolio. Government tax incentives strongly influence both decisions regarding which oil-bearing crop to use and the amount of vegetable oil to be transformed into biodiesel. Finally, the oil refinery/distributor is obliged by law to mix the biodiesel with the mineral diesel and perceives this as a liability. The results show the existence of different characteristics linked to the decision-making process and a significant lack of synchronicity in the aims and motivations behind the agents＇ decisions. This state of decisional misalignment leads to heightened uncertainty regarding the sustainability of the Brazilian biodiesel production program.

Analyzing the Roles of Agricultural Extension Agents in Hybrid Rice Technology Decision-Making Process of Farmers

The study determined the roles of agricultural extension in hybrid rice technology decision-making process by extension agents,Nay Pyi Taw,Myanmar.The specific objectives were:to study personal characteristics of agricultural extension agents,experiences and their roles,to identify extension agents’opinion on hybrid rice technology decision-making process,and to determine relationship between the roles of agricultural extension agents and decision-making process of hybrid rice production.One hundred and eight extension agents were collected who were working in Department of Agriculture,Nay Pyi Taw area and surveyed and interviewed by questionnaires.The study revealed that majority of agricultural extension agents(65.7%)were female staffs and most of extension agents(40.7%)were under 30 years as young staffs.Majority of extension agents(81.5%)were educated only Agri-Diploma.More than half(54.6%)had one to five-year experiences in employment and 58.3%had no hybrid rice training experience and source of information regarding the hybrid rice production was received 63.9%from Department of Agriculture(DOA).Study found that there was highly significant relationship between most of the roles of agricultural extension agents and hybrid rice technology decision-making process of stages 4 and 5.And then most of the extension agents’roles singnificantly related with stage 2 except role of conducting introduction of hybrid seeds and distribution through by Seed Co.Ltds which was highly significant.Beside,most of the roles of extension agents significantly related with stage 3.However stages 1 and 6 were no singnificantly related.Finally above all,a well structure seed business,Good Agricultural Practices and farm level mechanization and quality extension service are very important to increase the adoption of hybrid rice in Myanmar.

Policy Developments and Politics in Brazil： The Digital TV Decision-Making Process

Using an analytical narrative approach to understand policy change, this paper explores the Brazilian government decision to create a digital TV policy initiating major reforms in this sector. The analysis is centered on the actors, preferences, and choices. The article is divided into three parts： （1） We address the historical institutionalism assumptions; （2） We focus on the politics of digital TV policy in Brazil; and （3） The results are highlighted, and ＂winners＂ and ＂losers＂ are identified. Actors, preferences, and choices are historically observed and related to the government decision about rules of digital TV exploitation. It provides configurational evidence that makes it possible to associate major changes to two presidential decrees （n° 4.901/2003 and n° 5.820/2006） that reflect the preferences and behavior of the main actor （broadcasters, social movements, and federal government） around the new digital TV issues. The Brazilian case shows an institutional model in which federal government＇s decisions are strongly connected with the preferences of the actor broadcasters and goes against the actor social movements.

Decision-Making Process in Japanese Board Room. Audit ＆ Supervisory Board as a Source of Information to Outside Board Members： A Systematic Review

I the context of the Corporate Governance Code enactment in Japan, we examine how newly introduced outside directors in Japanese boards obtain information to take part in the decision-making process. We conducted a systematic review of the literature and found 18 peer-reviewed publications in a time span between 2000 and 2016 that described the asymmetry of information between the insider group of board directors （including the CEO） and the outside board members. Our fmdings show that for the course of more than a decade, despite all changes and reforms, the role of board directors, whether insiders or outsiders, is still supplementary. They are treated more as advisors than active part in the decision-making process. We reveal different insider sources of information as forming social ties with the CEO and/or inside board directors and collaboration with Audit ＆ Supervisory Board （Kansayaku）, which can help reduce this asymmetry and improve the decision-making process. We assume that it will be easier for the outsiders to establish contacts and form social ties with the Audit ＆ Supervisory Board members because of their unspoken lower status and thus to obtain more information about the company internal affairs and discussions that take place during the informal meetings, where only insiders （including the CEO） are present.

Analysis on decision-making model of plan evaluation based on grey relation projection and combination weight algorithm

In military service joint operations, when there are more operational forces, more multifarious materials are consumed, the support is more complex and fuzzy, the deployment of personnel is more rapid, and the support provided by wartime military material support powers can be more effective. When the principles,requirements, influencing factors and goals of military material support forces are deployed in wartime, an evaluation indicator system is established. Thus, a new combined empowerment method based on an analytic hierarchy process（AHP） is developed to calculate the subjective weights, and the rough entropy method is used to calculate the objective weights. Combination weights can be obtained by calculating the weight preference coefficient error, which is determined by combining the cooperative game method and the minimum deviation into objectives. This approach can determine the grey relation projection coefficient and synthesize the measure scheme superiority to finally optimize the deployment plan using the grey relation projection decision-making method. The results show that the method is feasible and effective;it can provide a more scientific and practical decision-making basis for the military material support power deployment in wartime.

Brain areas activated by uncertain reward-based decision-making in healthy volunteers

Reward-based decision-making has been found to activate several brain areas, including the ven- trolateral prefronta~ lobe, orbitofrontal cortex, anterior cingulate cortex, ventral striatum, and mesolimbic dopaminergic system. In this study, we observed brain areas activated under three de- grees of uncertainty in a reward-based decision-making task （certain, risky, and ambiguous）. The tasks were presented using a brain function audiovisual stimulation system. We conducted brain scans of 15 healthy volunteers using a 3.0T magnetic resonance scanner. We used SPM8 to ana- lyze the location and intensity of activation during the reward-based decision-making task, with re- spect to the three conditions. We found that the orbitofrontal cortex was activated in the certain reward condition, while the prefrontal cortex, precentral gyrus, occipital visual cortex, inferior parietal lobe, cerebellar posterior lobe, middle temporal gyrus, inferior temporal gyrus, limbic lobe, and midbrain were activated during the ＇risk＇ condition. The prefrontal cortex, temporal pole, inferior temporal gyrus, occipital visual cortex, and cerebellar posterior lobe were activated during am- biguous decision-making. The ventrolateral prefrontal lobe, frontal pole of the prefrontal lobe, orbi- tofrontal cortex, precentral gyrus, inferior temporal gyrus, fusiform gyrus, supramarginal gyrus, infe- rior parietal Iobule, and cerebellar posterior lobe exhibited greater activation in the ＇risk＇ than in the ＇certain＇ condition （P 〈 0.05）. The frontal pole and dorsolateral region of the prefrontal lobe, as well as the cerebellar posterior lobe, showed significantly greater activation in the ＇ambiguous＇ condition compared to the ＇risk＇ condition （P 〈 0.05）. The prefrontal lobe, occipital lobe, parietal lobe, temporal lobe, limbic lobe, midbrain, and posterior lobe of the cerebellum were activated during deci- sion-making about uncertain rewards. Thus, we observed different levels and regions of activation for different types of reward processing during decision-making. Specifically, when the degree of reward uncertainty increased, the number of activated brain areas increased, including greater ac- tivation of brain areas associated with loss.

Multi-Objective Optimization for an Industrial Grinding and Classification Process Based on PBM and RSM

The grinding and classification process is one of the key sub-processes in mineral processing, which influences the final process indexes significantly and determines energy and ball consumption of the whole plant. Therefore, optimal control of the process has been very important in practice. In order to stabilize the grinding index and improve grinding capacity in the process,a process model based on population balance model(PBM) is calibrated in this study. The correlation between the mill power and the operating variables in the grinding process is modelled by using the response surface method(RSM), which solves the problem where the traditional power modeling method relies on some unobservable mechanism-related parameters. On this basis, a multi-objective optimization model is established to maximize the useful power of the grinding circuit to improve the throughput of the grinding operation and improve the fraction of –0.074 mm particles in the hydrocyclone overflow to smooth the subsequent flotation operation. The elite non-dominated sorting genetic algorithm-II(NSGA-II) is then employed to solve the multi-objective optimization problem. Finally, subjective and objective weighting methods and integrated multi-attribute decision-making methods are used to select the optimal solution on the Pareto optimal solution set. The results demonstrate that the throughput of the mill and the fraction of –0.074 mm particles in the overflow of the cyclone are increased by 3.83 t/h and 2.53%, respectively.

A STUDY ON DECISION-MAKING OF ENVIRONMENTAL IMPACTS FOR REGIONAL WATER RESOURCES DEVELOPMENT

On the basis of overall analysis, this Paper, taking Beijing-Tianjin-Tangshan region as an example, tries to find out main environmental problems caused by water resources development and to discuss the mitigaive measures of the environmental impacts. The Paper, by means of Analytical Hierarchy Process (AHP, builds a multiple-hierarchy decision-making model including godl, water resources, environmental impact factors and mitigative measures. This study is very significant for alleviating and solving the problems of water resources-environmental system in the region.

Theories behind a nursing intern’s error in terms of clinical decision-making

Clinical decision-making and judgment is an essential skill that should be acquired by nursing interns.However,many studies reveal that a large proportion of nursing interns have difficulty in meeting the basic expectation of clinical decision-making.This article begins with a brief review of some theories related to clinical decision-making.Then it takes a case,for example,to show how the wrong decision is made.Furthermore,it makes a general analysis on the case drawing on the concept of bounded rationality,dual-process model,and skills acquisition theory.This article ends with some reflections from the case,to improve the consciousness and skills in decision-making for nursing interns.