Deductive Model Research Articles

Applying Lessons from Early-Stage Voluntary Counseling and Testing Services to End the HIV/AIDS Epidemic in Nigeria by 2030

Nigeria has waded through the HIV/AIDS epidemic for more than 35 years now since 1986. Response efforts are down-grading the epidemic from a peak of 5.8% prevalence in 2010 to a decline of 1.4% prevalence in 2019. Nigeria is desirous of ending the HIV/AIDS epidemic by 2030, but the terrain is challenged by bleak economic outlook and socio-political shocks that impose vulnerability including insurgency. This study explores the feasibility of Nigeria ending the HIV/AIDS epidemic by the year 2030, applying evaluation, management by objective (MBO), content analysis and the deductive model to assess early stage Voluntary Counseling and Testing (VCT) services in Anambra State, South-East Nigeria for the period 2006 - 2011. Secondary data were collected comprising summary of client flow activities of all 117 VCT centers in the State. Content analysis and deductive model were applied on the data to derive lessons learnt. The study found that: (i) VCT services were beneficial to about 1.9% of the State population, though with gross capacity under-utilization of VCT centers at 2.7 clients/day and the under-utilization of counselors at 0.6 clients served/day arising from low client flow; (ii) counseling process was effective and efficient in persuading consent to test; (iii) routine and mass HIV testing were cost-effective in detecting HIV positive sero-status; (iv) the synergy arising from counseling, testing and referral effectively mobilized Persons Living with HIV/AIDS for improved knowledge, attitude and practice (KAP) including formation of support groups averaging approximately 2 support groups per Local Government Area. The study recommends that VCT be adapted to a universal counseling and testing paradigm that includes, among others, outreach counseling and testing sessions, on-line counseling, and help-line supported self-testing. The study concludes that with necessary adjustment in counseling and testing, as well as necessary adjustments in other HIV/AIDS prevention, care and support services, the objective of ending the HIV/AIDS epidemic in Nigeria by 2030 will be attained.

The Scheduling Research of a Wind-Solar-Hydro Hybrid System Based on a Sand-Table Deduction Model at Ultra-Short-Term Scales

Establishing a wind-solar-hydro hybrid generation system is an effective way of ensuring the smooth passage of clean energy into the grid, and its related scheduling research is a complex and real-time optimization problem. Compared with the traditional scheduling method, this research investigates and improves the accuracy of the scheduling model and the flexibility of the scheduling strategy. The paper innovatively introduces a sand-table deduction model and designs a real-time adaptive scheduling algorithm to evaluate the source-load matching capability of the hybrid wind-solar-hydro system at ultra-short-term scales, and verifies it through arithmetic examples. The results show that the proposed adaptive sand-table scheduling model can reflect the actual output characteristics of the hybrid wind-solar-hydro system, track the load curve, and suppress the fluctuation of wind and solar energy, with good source-load matching capability.

Demand response method considering multiple types of flexible loads in industrial parks

With the rapid development of the energy internet, the proportion of flexible loads in smart grid is getting much higher than before. It is highly important to model flexible loads based on demand response. Therefore, a new demand response method considering multiple flexible loads is proposed in this paper to character the integrated demand response (IDR) resources. Firstly, a physical process analytical deduction (PPAD) model is proposed to improve the classification of flexible loads in industrial parks. Scenario generation, data point augmentation, and smooth curves under various operating conditions are considered to enhance the applicability of the model. Secondly, in view of the strong volatility and poor modeling effect of Wasserstein-generative adversarial networks (WGAN), an improved WGAN-gradient penalty (IWGAN-GP) model is developed to get a faster convergence speed than traditional WGAN and generate higher quality samples. Finally, the PPAD and IWGAN-GP models are jointly implemented to reveal the degree of correlation between flexible loads. Meanwhile, an intelligent offline database is built to deal with the impact of nonlinear factors in different response scenarios. Compared with Fourier, SVM, and BP-NET, the root mean square error is reduced by 2.854MW, 3.576MW, and 3.507MW, respectively. The relative error of the amount of unresponsiveness has been reduced significantly by over 25% compared to the traditional methods. Numerical examples have been performed with the results proving that the proposed method is significantly better than the existing technologies in reducing load modeling deviation and improving the responsiveness of park loads.

FACTORS INFLUENCING CUSTOMER SATISFACTION OF BANGLADESHI LEATHER PRODUCTS MANUFACTURING INDUSTRY

This research has been undertaken to find if product, service and information qualities influence customers satisfaction with Bangladeshi leather products in Bangladesh. Bangladesh s leather product industries are the second largest contributor to the national GDP. The country itself has a large consumer. Customer satisfaction has increasingly become in concern of the business conglomerates in Bangladesh. Previous research has empirical evidence that product, service and information quality influence customer satisfaction. This research is a benchmark to understand how these factors together impact customer satisfaction. Research shows that all these exogenous latent constructs have a significant positive impact on customer satisfaction. The article theoretically contributes to the existing literature by testing a hypothetic deductive model among 384 customers in Dhaka City. Variance-based statistical tools (particle least squared equation model) were used to test the hypotheses. The result of the study arises a convincing case for the entrepreneurs of Bangladeshi leather products manufacturing industries regarding taking due attention to improving the product, service and information quality. KEYWORDS: Customer satisfaction, Leather industries, Product quality, Information quality, Service quality, Bangladesh.

Characterisation for spatial distribution of mining-induced stress through deep learning algorithm on SHM data

ABSTRACT The study of mining-induced stress is essential to ensure the safety production of coalmine. Due to the limited number of monitoring points and local monitoring area, the perception of structure status is insufficient. This study aims to present a deep learning (DL) model to derive the stress distribution characteristics of the overall coalmine roof. First, the framework of spatial deduction model termed as transferring convolutional neural network (TCNN) is presented, where the convolutional neural network is transferred on different datasets. According to this framework, the spatial correlations of structural mechanical responses at different heights above roadway roof are learned through numerical simulation. Subsequently, the learned results are transferred to monitoring data to derive the actual state of the overall roof. In order to verify the reliability of the TCNN model, the stress sensor is installed in the derived plane to collect the actual data, and two indicators are adopted to evaluate the reasonability of deduction results. Experimental results indicated that 92.25% features of mining-induced stress distribution are captured by the TCNN model and the deduction error is 2.037 MPa. Therefore, the presented model is reliable to obtain the overall mechanical state of the coalmine roof, and it is supposed to promote the application of DL in underground construction.

A Reinforcement Learning Intelligent Deductive Model with Pretrained Sequence Information

A Reinforcement Learning Intelligent Deductive Model with Pretrained Sequence Information

A reinforcement learning intelligent deductive model with pre-trained sequence information

A reinforcement learning intelligent deductive model with pre-trained sequence information

Improving Children’s Literacy Through Indonesian Fairy Tales at Rumah Pintar Yafsi

Rumah Pintar YAFSI is one of the programs managed by Yayasan Fajar Sejahtera Indonesia to help develop character education and child protection programs in the community. Increasing literacy interest in children is an important aspect of character education that must be instilled. Improving children's literacy requires adequate facilities and education of high quality. As a result, in this service activity, the team has provided goods and services to the Rumah Pintar YAFSI, namely the assistance of Indonesian fairy tale books and storytelling training services for Rumah Pintar YAFSI volunteers to further strengthen children's interest in literacy. This is also an effort to achieve inclusive education for children of all socioeconomic backgrounds. The lecture method approach, question and answer or discussion, and deductive model training methods are used in the implementation. This community service improves Rumah Pintar YAFSI volunteers' storytelling skills, which in turn increases children's literacy interest in Rumah Pintar YAFSI. The outcomes of this activity have also been documented in written reports and videos. Furthermore, activities are reported in national online newspapers.

A Research on the Adaptive Dynamic Scheduling Based on Scenario Deduction

Aiming at the uncertainty of the intelligent manufacturing system, this paper reveals the evolution mechanism of the manufacturing system and its internal and external environment from a data-driven perspective. And it proposes an adaptive dynamic scheduling method based on scenario deduction, which provides the basis for the intelligent manufacturing support in an uncertain environment. Firstly, the paper uses the ontology to describe the scenario status, production activities, market environment and production subject of manufacturing system. And then builds the scenario deduction model based on the dynamic fuzzy cognitive map, establishing the data-driven manufacturing scenario network structure. Through the dynamic fuzzy cognitive map, it presents the market and production scenario evolution and accordingly guides the adaptive choice of dynamic scheduling strategy in uncertain production environment. The results show that the scenario deduction model is basically consistent with the manufacturing system evolution process in terms of time inference and demand prediction, and it verifies the adaptability and effectiveness of the proposed dynamic dispatching method through examples.

Deduction of sudden rainstorm scenarios: integrating decision makers' emotions, dynamic Bayesian network and DS evidence theory

Event scenarios serve as the basis for emergency decision making after sudden disasters, and the accuracy of scenario deduction directly determines the effectiveness of emergency management implementation. On July 20, 2021, an exceptionally heavy rainstorm disaster occurred in Zhengzhou, Henan Province, China, causing serious urban waterlogging, river floods, flash floods and landslides and resulting in major casualties and property losses:14.79 million people affected, 398 people killed or missing (380 people in Zhengzhou) and a direct economic loss of 120.06 billion RMB. In order to investigate the complex evolution process of this disaster, a dynamic Bayesian network, evidence theory and emotion update mechanism are integrated to develop an efficient and effective scenario deduction model, with an emphasis on combining subjective and objective factors. In this model, more attention is given to subjective factors such as decision makers' emotions. The elements of scenario deduction are classified into the situation status, meteorological factor, emergency activities, decision makers' emotions and emergency goals, the coupling relationship between the elements are comprehensively analyzed, and the influence of these elements on the evolution mechanism of the rainstorm disaster is investigated, so as to facilitate targeted emergency management measures for the rescue operations. The empirical results show that the proposed dynamic Bayesian network can effectively simulate the dynamic change process of scenario deduction, the improved Dempster–Shafer evidence theory can reduce the subjectivity of the model in dealing with the uncertainty of the evolution process, and the emotion update mechanism can adequately quantify and decrease the influence caused by the emotional changes of decision makers. The model may better replicate actual events, and it may apply to the scenario deduction of other disasters, making an impact on the study of sudden catastrophes.

QUANTUM DIGITAL-ANALOGUE COMPUTING

Context. Nature is the relation among processes and phenomena. Nothing exists in the universe without relations. Computer is transactions of relations between data with the help of control and execution mechanisms. Quantum relations are a superposition of particles and their states. Superposition and entanglement are equivalent concepts. Entanglement is a non-local superposition of deterministic states. A quantum computer is unconditional transactions of relations between qubit data. Quantum computer is an analog device for parallel solution of combinatorial problems. Practically oriented definitions of the quantum computer concepts are the path to development of scalable quantum parallel algorithms for combinatorial problems solving. Any algorithm can be reduced to a sequence of operations without conditions, because any truth table is a collection of a complete system of conditions-states. Any sequence of actions can always be reduced to one parallel operation. Conditions and sequences arise only when the developer wants to use previously created primitive constructs to build an always non-optimal computing unit. The paradigm of quantum computer creation is determined through the use of photonic transactions on the electrons of an atom may exclude the use of quantum logic. The evolutionary path of a quantum computer from the classical one: “memory-address-transaction” (MAT) → “electron-addresstransaction” → “electron-address-quantaction” (EAQ) → state-superposition-logic. The meeting point of classical and quantum computers is photon transactions on the structure of electrons. Everything that is calculated on a quantum computer can be calculated in parallel on a classical one on account of memory redundancy. The given example is a memory-driven algorithm for modeling digital products based on qubit-vector forms of functionality description for significant performance boost of computing processes by parallel execution of logical operations.
 Objective. Simulation of the correct SoC-component behavior based on vector representation of the logic. Formation of the triggering development of a computing based on the superposition of the classical, quantum and analog computing process, which in its development should be based on technological qubit, tabular and vector data structures for the parallel solution of combinatorial problems.
 Method. MAT-computing implements any algorithms on account of transactions (read-write) in memory. Qubit-vector models for describing functionalities, which differ from known truth tables in compactness of description and manufacturability for the implementation of parallel algorithms of the synthesis and analysis of digital devices and SoC-components.
 Results. 1) The metric of the technological data structures, focused on parallel troubleshooting in digital systems based on the usage of two logical vector operations, was proposed for the first time. 2) The metric of relations between the individual components of QC, allowing organizing a quantum deterministic computer, has been further developed. 3) Quantum architectural solutions, that allow solving coverage problems in a quasi-parallel mode, were proposed for the first time. 4) Architectural solutions based on an analog-to-digital computing, which can be used to solve the problems of the digital systems parallel analysis, have been further developed. 5) Vector-qubit structures of the logic data, that allow a quasi-parallel simulation of digital circuits, were proposed.
 Conclusions. Qubit models, quantum methods and combinatorial algorithms for technical diagnostics of digital devices have been implemented, which can significantly (up to 25%) reduce the time of test synthesis, deductive modeling of faulty and correct behavior, search for defective states by introducing an innovative idea of using qubit-vector data structures for describing logical components. Comparative assessments of qubit models and methods usage show an increase in the efficiency of algorithms for modeling digital devices compared to tabular ones. The superposition of a classical, quantum and analog computer is integrally represented, which allows to find the best solutions for recognition and decision making.

Target anisotropic scattering deduction model using multi-aspect SAR data

Typical targets in SAR observing scenes are characterized by anisotropy, which represents backscattering information changing with the observing angle. Anisotropic scattering can be used to study the structural characteristics of targets and the response differences between structures. In actual situations, due to flight conditions and other reasons, only partial observation information can be obtained, so it is important to use limited data to deduce remaining backscattering information for target analysis. In our article, the scattering deduction model based on matrix completion is established, including scattering characteristic analysis. The multi-aspect data is transferred from range and azimuth in conventional SAR image to pixel dimension and angle dimension for analysis. At the same time, the pixel similarity matrix is used as a feature in pixel dimension, and one-dimension back-amplitude scattering curve with angle is established as a feature matrix in angle dimension. In the process of modeling existing data, two corresponding decomposition matrices are generated with the help of collaborative filtering idea. Finally, a four-matrix combination for anisotropy deduction is formed. Ku-band multi-aspect data from autonomous experimental flights is used for algorithm. In the experiment, the scattering deduction of the remaining aspect sequence was carried out based on obtaining partial aspect sequence images, and the strong scattering regions of the target point and sub-aperture details were compared. The edge information and structure map of the target were reconstructed using scattering deduction results.

How Ethics Liberates Experience: Insights from Pragmatist Theory and Contemporary Research

ABSTRACTEthics is often viewed as the elaboration of and compliance to norms, a.k.a. as the deductive model of ethics. This is well illustrated by the mainstream development of codes of ethics and ethics committees in the healthcare setting and beyond. Drawing upon a recent synthesis of pragmatist insights on the nature of ethics as well as contemporary scholarship on human flourishing, I explain how ethics is not primarily about the compliance of experience and agency to preset norms but about liberation and empowerment within a process of existential meaning-making. This point is made in the context of two important tasks of ethics: (1) understanding moral problems and (2) providing guidance for solving such problems.

Double Bark Thickness Estimation Models of Common European Broadleaved Species for Harvester Timber Volume Estimation in Czechia

The share of the annual volume of harvester-produced timber in Czech forest bioeconomy has increased in the last decades. To estimate under-bark timber volume, harvester systems allow choosing between two different bark deduction models – diameter band (DBM) and linear model. However, linear models were not calibrated for the conditions of Czech forestry. Therefore, the objective of this research was to develop, for local conditions in Czechia, linear functions for estimating the double bark thickness of two groups of broadleaved species (beech and oak) and to test their viability based on real harvest data. To create the linear functions, official Czech cubing tables were used. Data from real harvests were gathered from fifteen harvesters. A sample containing 4995 logs belonging to the beech group was analyzed using descriptive statistics and the Paired Wilcoxon tests. The mean double bark thickness for beech group was 15.1 mm (polynomial and linear model). For oak group, it was 15.48 mm (polynomial) or 15.49 mm (linear). The results of real harvests for beech group revealed that the mean double bark thickness estimated by the polynomial function was 7.08 mm. The linear function estimates were closer to the value estimated by the polynomial (6.84 mm) than DBM estimates (6.68 mm). Therefore, we can state that the newly developed linear models can be used in fully mechanized harvesting instead of manual bark deduction methods in Czechia.

The impact of posterior corneal astigmatism on the surgical planning of toric multifocal intraocular lens implantation

PurposeTo investigate the influence of posterior corneal astigmatism on the prediction accuracy of toric multifocal intraocular lens (IOL) calculation. MethodsThe keratometric astigmatism measured by Lenstar LS 900 (KCAL), keratometric astigmatism (KCAP) and total corneal astigmatism (TCA) measured by Scheimpflug camera (Pentacam HR) were documented and analyzed accordingly. Three deduction models using different parameters were compared. Model 1: KCAL ​+ ​keratometric corneal surgically induced astigmatism (KCSIA, 0.30 D @ 50°); Model 2: KCAP ​+ ​KCSIA); Model 3: TCA ​+ ​total CSIA (TCSIA, 0.23 D @ 50°). The prediction errors of each model as the difference vector between the actual and the intended residual astigmatism were compared. ResultsSeventy-six eyes implanted with toric multifocal IOLs were included in this study. The vector differences of the actual KCSIA and TCSIA were statistically significant in the total sample and against-the-rule (ATR) subgroup (both P ​< ​0.05). Model 1 deduced the smallest mean values of prediction error, while that of Model 3 were smaller than that of Model 2, both in the total sample and the ATR subgroups (all P ​< ​0.05). Meanwhile, in the total sample and ATR subgroups, the centroid vector magnitudes of Model 3 were smaller than that of Model 1 (0.31 ​± ​0.76 D and 0.39 ​± ​0.76 D). ConclusionsThe calculation of toric multifocal IOL should be individualized especially in the ATR eyes for the impact of PCA on the estimation of the preoperative corneal astigmatism and the CSIA.

Management of Student Independence Development in Pesantren

This research is a field research with a qualitative approach. Data collection techniques using observation, documentation and interviews. Data analysis using induction and deduction models. After the data is grouped by type, the researcher re-checks the data, so that the data has no errors and can be presented in writing in the form of a research report. The results showed that the management of developing the independence of students at the Daruttauhid Al-Alawi Islamic Boarding School was carried out in three stages, namely (1) Planning was in place before the independence program was implemented such as holding meetings, selecting independence programs, and others. The planning stage includes: curriculum planning, teaching materials, personnel, facilities and infrastructure, and program planning; (2) The implementation of the program is carried out in several stages including carrying out teaching and learning activities, organization, routine compulsory Islamic boarding school activities, daily student activities, supporting activities, and boarding school discipline rules; (3) Supervision and evaluation of the program, caregivers and administrators as well as the community participate in evaluating these activities. If there are weaknesses, then input will be given for improvements in the future.

Coordinating supply and demand in ride-sourcing markets with pre-assigned pooling service and traffic congestion externality

This paper proposes an equilibrium model to describe a ride-sourcing market with both ride-pooling (RP) and non-pooling (NP) services considering traffic congestion externality. In particular, we develop a deductive model to approximate the pool-matching probability and passengers’ expected waiting time under a pre-assigned pool-matching mechanism with meeting points, which is being used in products like Uber Express Pool. Using the model, we derive the equilibrium properties and examine the optimal operating strategies for achieving two market scenarios, including the monopoly optimum and social optimum. In contrast to the traditional wisdom, we find that the market could exist in one or multiple equilibria, depending on the trip fare difference between RP and NP services. Additionally, we show that average sojourn time first decreases in the vehicle fleet size (when traffic congestion is mild) and then increases in the vehicle fleet size (when traffic congestion is heavy), exhibiting a “smiling curve”. It is found that the monopoly optimum solution is always located in the downward side of the “smiling curve”, which implies the ride-sourcing platform will self-regulate its fleet size to avoid heavy traffic congestion. We also discuss the impacts of potential labor supply and background traffic on the platform’s optimal operating strategy and its optimal profit. This study gains interesting managerial insights that help understand how ride-sourcing platforms determine optimal operating strategies for both RP and NP services by considering traffic congestion externality.

Phenomenological models versus deductive models: The stochastic limit of quantum theory

After discussing in general the advantages, for the applications to physics, of deductive models with respect to phenomenological ones, we concentrate on open systems and describe the main ideas of the stochastic limit approach to open systems. We discuss the various levels of the stochastic limit (in increasing order of complexity of the interaction Hamiltonian) describing the new features that emerge at each level and their applications to different branches of physics. We illustrate some examples which highlight how, using the stochastic limit approach, one can answer long-standing questions on various physical behaviors of the composite system solving problems that cannot even be formulated in the reduced evolution (master equation) scheme. In the second part of the paper, we outline the main ideas of the proofs of some of the new features described in the first part. For lack of space, we focus our attention on Level 1 and we have to omit most physical applications. These topics will be the object of a future publication.

Analisis Strategi Marketing Mix Dalam Meningkatkan Pengiriman Barang dan Jasa:

The purpose of this research is to study how the marketing strategy of PT.JNE Express Patumbak Branch was developed and how the marketing strategy of PT.JNE Express Patumbak Branch was implemented. This research is a descriptive field study with a deductive model, conducted through structured and unstructured interviews. In addition to collecting data through observation, data management is carried out through methods of organization, organization, and analysis. This research is a quantitative research. Based on the results of a survey conducted by PT.JNE Express Patumbak Branch on products, prices, locations, promotions, people, physical assets, and strategic processes. The product strategy is assisted by the availability of flexible products such as Yes, Normal, and Economic Status (OK) that are tailored to customer needs. JNE Express has 14 products and services, with prices based on quantity and quality. Packages of socialization, expansion of partnerships, franchising, promotion of law and order training, online advertising and internet marketing, strategies for community empowerment programs (HR for employees), and employee benefits in materials and information. Have a good communication, writing, and information strategy physically, as well as a good process strategy, good communication channels, and good technology-oriented services.&#x0D; Keywords: marketing strategy, internet marketing, JNE

Analisis Strategi Marketing Mix Dalam Meningkatkan Pengiriman Barang dan Jasa:

The purpose of this research is to study how the marketing strategy of PT.JNE Express Patumbak Branch was developed and how the marketing strategy of PT.JNE Express Patumbak Branch was implemented. This research is a descriptive field study with a deductive model, conducted through structured and unstructured interviews. In addition to collecting data through observation, data management is carried out through methods of organization, organization, and analysis. This research is a quantitative research. Based on the results of a survey conducted by PT.JNE Express Patumbak Branch on products, prices, locations, promotions, people, physical assets, and strategic processes. The product strategy is assisted by the availability of flexible products such as Yes, Normal, and Economic Status (OK) that are tailored to customer needs. JNE Express has 14 products and services, with prices based on quantity and quality. Packages of socialization, expansion of partnerships, franchising, promotion of law and order training, online advertising and internet marketing, strategies for community empowerment programs (HR for employees), and employee benefits in materials and information. Have a good communication, writing, and information strategy physically, as well as a good process strategy, good communication channels, and good technology-oriented services.&#x0D; Keywords: marketing strategy, internet marketing, JNE