Pair Model Research Articles

Прогнозирование продовольственной безопасности региона в контексте экономической доступности продуктов питания

Purpose. The study consists in the development and substantiation of forecast scenarios for ensuring the food security of the region in the context of food affordability. Materials and methods. The research technique is based on the development of predictive econometric models of the food affordability, including trend, simulation modeling and paired non-linear correlation-regression models, which not only makes it possible to identify the impact on the consumption level of two multidirectional factors at the same time (price changes and income), but also reflects the real purchasing power of the monetary income of the population. The empirical basis for forecast calculations was an assessment of trends in ensuring food security in the region for the period 2007–2019. Results. The results of the study indicate that during the period of fundamental changes in the modern agro-food policy of Russia, including the adoption of the Food Security Doctrine, the implementation of accelerated import substitution measures, it was not possible to significantly improve the quality and living standard of the population. It is substantiated that the degree of differentiation of population of Rostov region in terms of income, together with the Engel coefficient, approaches a critical level and does not allow ensuring the food affordability at the proper level. Predictive scenarios of food affordability have been developed: basic (inertial) and pessimistic. It is argued that the existing mechanism for ensuring food security in the long term is insufficient to improve the quality of life of population. Conclusions. Difficult macroeconomic conditions in the country against the backdrop of sanctions confrontations and a pandemic can significantly aggravate food affordability. In particular, meat consumption by 2030 may reach 82.2 % of the rational consumption rate, milk and fruits 76.7 and 65.2 %, respectively. A methodology for predicting the economic food affordability within the framework of ensuring food security is proposed, which can be used by public authorities at all levels to adjust key areas of agrarian socio-economic policy.

Energy Efficient Hop-by-Hop Retransmission and Congestion Mitigation of an Optimum Routing and Clustering Protocol for WSNs

In the past few decades, wireless sensor networks, which take a growing number of applications in the surroundings further than the human reach, have risen in popularity. Various routing pseudo codes have been suggested for network optimization, emphasizing energy efficiency, network longevity, and clustering processes. To the existing load balancing energy-efficient sleep awake, aware smart sensor network routing protocol, the modified load-balancing efficient-energy sleep active alert smart routing system for wireless sensor networks is presented in this paper, which takes network homogeneity into account. The modified protocol is the optimum clustering and routing protocol in wireless sensor networks (OCRSN), which simulates an enhanced network coupled node pair model. Our suggested modified approach studies and enhances factors such as network stability, network lifetime, and cluster monitor mechanism choice. The significance of typically combining sensor endpoints is applied to maximize energy efficiency. The proposed protocol significantly improved network parameters in simulations, showing that it could be a valuable option for WSNs. In wireless sensor networks, in addition to memory considerations and dependable transportation, this paper presents a hop-by-hop re-transmission strategy and congestion mitigation, which is the major contribution of this paper. It is a very consistent method based on a pipe flow model. After performing additional optimized overhead to improve the network lifespan of wireless sensors networks, the current algorithm can be paralleled to the less energy adaptive clustering hierarchy protocol. The optimal clustering in multipath and multihop technique intends to minimize the energy consumption highlighted for a circular area enclosed by a sink by replacing one-hop communication with efficient multihop communication. The optimum quantity of clusters is determined, and the energy consumption is reduced by splitting the network into clusters of nearly equal size. The obtained simulation results will demonstrate the increase in the network lifetime compared to previous clustering strategies such as Low Energy Adaptive Clustering Hierarchy.

Colonial Metaphor, Colonial Metaphysics: On the Poetic Pairing of Blackness and Indianness

This essay performs an anticolonial and poetic methodology of combining Black and Native feminists' deconstruction of metaphor and metaphysics in order to argue for the centrality of colonial metaphor to colonial metaphysics. I combine their analyses of the separate gendered metaphors of Blackness and Indianness and the centrality of these metaphors to the development of a global metaphysics as well as the transference of the terms of metaphysics to whiteness. I then apply this method of combined terms and readings to white colonial writing that compares Black and Native America, which transforms both communities not only into individually potent, gendered metaphors but into an essential poetic pairing, a poetic couplet. Drawing on the work of Black and Native feminists, I further argue that when we take this paired model to evaluate the political concerns of Black and Native America, we come to a more complete and global understanding and refutation of whiteness. The creation, connection, and comparison of the gendered metaphors and archetypical figures of the "African Slave" and "Indian Savage" are important to each other and to the creation of a Western conception of the globe. Colonialism uses gender to compound metaphor's ability to create, by combining metaphors of gender with metaphors of race and colonialism to develop new symbolic amalgamations. This gestalt of metaphors comes together in order to create a fictive European metaphysics used to ameliorate white fears of the diversity of life on planet Earth and to satisfy white desires to control it. In this coupled metaphoric form, Blackness and Indianness are not connected by analogy but by the open-ended cut, the caesura, of poetry and the violence of slavery and conquest. I offer this anticolonial and poetic pairing as a model for political imagining between Black and Native theory.

Analysis of the Impact of the Covid-19 Pandemic on Stock Exchange Indices in Italy

The present paper investigates the impact of the COVID-19 pandemic on the prices of the Italian stock exchange indices. During the pandemic, the global economy as well as financial markets suffered due to isolation and social distancing. Paired models of the dependence of the key indices of the Italian stock exchange on the number of patients, recovered and died were analysed using the least squares method. Further, various tests were performed to verify the feasibility of the Gauss-Markov conditions by applying Gretl tools: White Test for heteroskedasticity of residues, Durbin-Watson test for autocorrelation of residuals and normality of distribution of residuals. Statistically significant regression models were constructed that characterise the impact of morbidity and mortality in the Italian population during the COVID-19 pandemic on the price of 11 key stock exchange indices. Based on this, the study examined the COVID-19 pandemic period in the spring of 2020 in Italy, the results of which revealed a loss in stock returns and high volatility in stock returns during this period compared to the normal study period. The econometric model shows that COVID-19 had a negative impact on stock returns and a number of other stock market indicators in Italy. It was revealed that the number of deaths from coronavirus is statistically significantly interconnected with all key stock exchange indices.

Image quality evaluation of multimodal imaging of muon

Both the information about the scattering of muons due to their interaction with material and the information about the material-stopped muons generating secondary induced neutrons effectively are used for multimodal imaging of muon. In order to evaluate the image quality of multimodal imaging of muon, the detection model is established based on Geant4 and the reliability of the detection model is verified. Both the multiple Coulomb scattering module and the muon induced neutron module prove to be reliable. The multimodal imaging simulation program is developed, and the images are reconstructed on the basis of the simulated data. Four imaging models are developed. The first model is a line pair model used to study the spatial resolution of reconstructed images with imaging time ranging from two hours to two weeks. The line pair model is composed of <sup>235</sup>U and the length of each line pair is set to be 100 mm. The cross sections are set to be 4<sup>2</sup>, 4<sup>2</sup>, 6<sup>2</sup>, 6<sup>2</sup>, 10<sup>2</sup>, 10<sup>2</sup>, 20<sup>2</sup>, and 20<sup>2</sup> mm<sup>2</sup>, respectively. The second model is a cube model used to study the material resolution of reconstructed images with imaging time ranging from one hour to twelve hours. The side length of each cube is 100 mm. The third model is the cladding model used to test the reliability of multimodal imaging images in complex shielding situations. The outermost layer is of lead, with the side length being 140 mm and the thickness 40 mm. The middle layer is of iron, with the side length being 100 mm and the thickness 40 mm. The innermost layer of <sup>235</sup>U, with the side length being 60 mm. The last letter model is used to calculate the structural similarity of reconstructed images, with imaging time ranging from half an hour to twelve hours. The letter model is made of <sup>235</sup>U and consists of cubes with side length of 50 mm. The letters “E” and “P” are made up of 16 cubes and 15 cubes respectively. The spatial resolution reaches 4 mm when imaging time is within 12 hours. The <sup>235</sup>U and other common high-z, medium-z, and low-z material can be distinguished when imaging time is on the order of hours. Muon scattering imaging image of the cladding model will cause misjudgment. However, the multimodal imaging image can correctly reflect the existence of <sup>235</sup>U. The structure similarity between the reconstructed image and the reference image in different imaging times proves that multimodal imaging has higher quality than single imaging method. The study indicates that the multimodal imaging of muon has better imaging quality, can adapt to more complex imaging scenes and has more advantages in the detection and recognition of special nuclear material than muon imaging method with single interaction information.

Quartz mid-temperature thermoluminescence configurational coordinate model

We present a configurational coordinate model to explain a number of optical bleaching features displayed by the ultraviolet mid-temperature thermoluminescence peaks (110 °C, 160 °C and 220 °C) in quartz. Within our analysis, we find that the defect pair model for quartz luminescence needs to be extended to include a thermally-assisted optical stimulation path for each of the peaks. By incorporating this extension within an appropriate configurational coordinate framework, we have been able to develop an analytical explanation for known optical bleaching characteristics.

Quartz Defect Pair Model for Exo-Electron Emission

Quartz Defect Pair Model for Exo-Electron Emission

Novel Technique for Estimation of Cell Parameters Using MATLAB/Simulink

The main source of power in Electric Vehicles (EVs) is derived from batteries. An efficient cell model is extremely important for the development of complex algorithms like core temperature estimation, State of Health (SOH) estimation and State of Charge (SOC) estimation. In this paper, a new methodology for improving the SOC estimation using Equivalent Cell Model (ECM) approach is proposed. The modeling and simulations were performed using MATLAB/Simulink software. In this regard, a Li polymer cell was modeled as a single Resistor-Capacitor (RC) pair (R0, R1 and C1) model using PowerTrain blockset in MATLAB/Simulink software. To validate the developed model, a NASA dataset was used as the reference dataset. The cell model was tuned against the NASA dataset for different currents in such a way that the error in the terminal voltages (difference in terminal voltage between the dataset and the ECM) is <±0.2 V. The mean error and the standard deviation of the error were 0.0529 and 0.0310 respectively. This process was performed by tuning the cell parameters. It was found that the cell parameters were independent of the nominal capacity of the cell. The cell parameters of Li polymer and the Li ion cells (NASA dataset) were found be almost identical. These parameters showed dependence on SOC and temperature. The major challenge in a battery management system is the parameter estimation and prediction of SOC, this is because the degradation of battery is highly nonlinear in nature. This paper presents the parameter estimation and prediction of state of charge of Li ion batteries by implementing different machine learning techniques. The selection of the best suited algorithm is finalized through the performance indices mainly by evaluating the values of R- Squared. The parameters were trained using various Machine Leaning (ML) techniques for regression data analysis using Simulink. A study on Support Vector Machine (SVM) technique was carried out for the simulated and tuned data. It is concluded that the SVM algorithm was best suited. A detailed analysis on the errors associated with the algorithms was also carried out. Later, these parameters were trained using various Machine Leaning (ML) techniques for regression data analysis using Simulink. A study on SVM technique was carried out for the simulated and tuned data. It is concluded that the SVM algorithm was best suited. A detailed analysis on the errors associated with the algorithms was also carried out.

Promoting Sustainability through Regional Food and Wine Pairing

Sustainable development has been growingly recognized as important in the scope of tourism and hospitality industry practices. Gastronomic tourism associated with regional food-and wine pairing helps the emerging of higher quality services and contributes to the sustainability of tourist destinations. This study presents a pairing model based on three Real-Time Delphi (RTD) questionnaires to allow experts to select and pair regional wines with regional foods. In the first questionnaire, the experts were asked to choose, by category, the most representative regional dishes from the Algarve region (Portugal). In the second questionnaire, for each dish, experts voted on the best regional wines for the dish. In the third questionnaire, experts made quantitative and qualitative analyses for each of the three most voted wines for each dish. The resulting pairing model of regional food and wines will be communicated to tourism professionals and the general public. By promoting the consumption of these pairings, we promote an efficient, socially fair, and ecologically sustainable local economy. At the same time, we stimulate the circular economy in tourism.

Functional Tensor-Train Chebyshev Method for Multidimensional Quantum Dynamics Simulations.

Methods for efficient simulations of multidimensional quantum dynamics are essential for theoretical studies of chemical systems where quantum effects are important, such as those involving rearrangements of protons or electronic configurations. Here, we introduce the functional tensor-train Chebyshev (FTTC) method for rigorous nuclear quantum dynamics simulations. FTTC is essentially the Chebyshev propagation scheme applied to the initial state represented in a continuous analogue tensor-train format. We demonstrate the capabilities of FTTC as applied to simulations of proton quantum dynamics in a 50-dimensional model of hydrogen-bonded DNA base pairs.

Identification of an Autophagy-Related Pair Signature for Predicting Prognoses and Immune Activity in Pancreatic Adenocarcinoma.

BackgroundPancreatic adenocarcinoma (PAAD) spreads quickly and has a poor prognosis. Autophagy research on PAAD could reveal new biomarkers and targets for diagnosis and treatment.MethodsAutophagy-related genes were translated into autophagy-related gene pairs, and univariate Cox regression was performed to obtain overall survival (OS)-related IRGPs (P<0.001). LASSO Cox regression analyses were performed to construct an autophagy-related gene pair (ARGP) model for predicting OS. The Cancer Genome Atlas (TCGA)-PAAD cohort was set as the training group for model construction. The model predictive value was validated in multiple external datasets. Receiver operating characteristic (ROC) curves were used to evaluate model performance. Tumor microenvironments and immune infiltration were compared between low- and high-risk groups with ESTIMATE and CIBERSORT. Differentially expressed genes (DEGs) between the groups were further analyzed by Gene Ontology biological process (GO-BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and used to identify potential small-molecule compounds in L1000FWD.ResultsRisk scores were calculated as follows: ATG4B|CHMP4C×(-0.31) + CHMP2B|MAP1LC3B×(0.30) + CHMP6|RIPK2 ×(-0.33) + LRSAM1|TRIM5×(-0.26) + MAP1LC3A|PAFAH1B2×(-0.15) + MAP1LC3A|TRIM21×(-0.08) + MET|MFN2×(0.38) + MET|MTDH×(0.47) + RASIP1|TRIM5×(-0.23) + RB1CC1|TPCN1×(0.22). OS was significantly shorter in the high-risk group than the low-risk group in each PAAD cohort. The ESTIMATE analysis showed no difference in stromal scores but a significant difference in immune scores (p=0.0045) and ESTIMATE scores (p=0.014) between the groups. CIBERSORT analysis showed higher naive B cell, Treg cell, CD8 T cell, and plasma cell levels in the low-risk group and higher M1 and M2 macrophage levels in the high-risk group. In addition, the results showed that naive B cells (r=-0.32, p<0.001), Treg cells (r=-0.31, p<0.001), CD8 T cells (r=-0.24, p=0.0092), and plasma cells (r=-0.2, p<0.026) were statistically correlated with the ARGP risk score. The top 3 enriched GO-BPs were signal release, regulation of transsynaptic signaling, and modulation of chemical synaptic transmission, and the top 3 enriched KEGG pathways were the insulin secretion, dopaminergic synapse, and NF-kappa B signaling pathways. Several potential small-molecule compounds targeting ARGs were also identified.ConclusionOur results demonstrate that the ARGP-based model may be a promising prognostic indicator for identifying drug targets in patients with PAAD.

Superconductivity in the bilayer Hubbard model: Two Fermi surfaces are better than one

Fully occupied or unoccupied bands in a solid are often considered inert and irrelevant to a material's low-energy properties. But the discovery of enhanced superconductivity in heavily electron-doped FeSe-derived superconductors poses questions about the possible role of incipient bands (those laying close to but not crossing the Fermi level) in pairing. To answer this question, researchers have studied pairing correlations in the bilayer Hubbard model, which has an incipient band for large interlayer hopping ${t}_{\ensuremath{\perp}}$, using many-body perturbation theory and variational methods. They have generally found that superconductivity is enhanced as one of the bands approaches the Lifshitz transition and even when it becomes incipient. Here we address this question using the nonperturbative quantum Monte Carlo (QMC) dynamical cluster approximation (DCA) to study the bilayer Hubbard model's pairing correlations. We find that the model has robust ${s}^{\ifmmode\pm\else\textpm\fi{}}$ pairing correlations in the large ${t}_{\ensuremath{\perp}}$ limit, which can become stronger as one band is made incipient. While this behavior is linked to changes in the effective interaction, we further find that it is counteracted by a suppression of the intrinsic pair-field susceptibility and does not translate to an increased ${T}_{c}$. Our results demonstrate that the highest achievable transition temperatures in the bilayer Hubbard model occur when the system has two bands crossing the Fermi level.

Model Development of CDK4/6 Predicted Efficacy in Patients With Hormone Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative Advanced or Metastatic Breast Cancer.

Three cyclin-dependent kinase 4/6 inhibitors (CDKIs) are approved by the US Food and Drug Administration for the treatment of patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative advanced or metastatic breast cancer in combination with hormonal therapy (HT). We hypothesized that on an individual basis, efficacy outcomes and adverse event (AE) development can be predicted using baseline patient and tumor characteristics. Individual-level data from seven randomized controlled trials submitted to the US Food and Drug Administration for new or supplemental marketing applications of CDKIs were pooled. Progression-free survival (PFS), overall survival (OS), and AE prediction models were developed for specific treatment regimens (HT v HT plus CDKI). An individual's characteristics were used in all models simultaneously to create a group of predicted outcomes that are comparable across treatment settings. Accuracy of the PFS and OS prediction models for HT were 66% and 64%, respectively, with the strongest predictors being menopausal status and therapy line. The corresponding AE prediction models resulted in an average area under the curve of 0.613. Accuracy of the PFS and OS prediction models for HT plus CDKI were 62% and 63%, respectively, with the strongest predictors being histologic grade for both. The corresponding AE prediction models resulted in an average area under the curve of 0.639. This exploratory analysis demonstrated that models of efficacy outcomes and AE development can be developed using baseline patient and tumor characteristics. Comparison of paired models can inform treatment selection for individuals on the basis of the patient's personalized goals and concerns. Although use of CDKIs is standard of care in the first- or second-line setting, this model provides prognostic information that may inform individual treatment decisions.

Analisis Perbandingan Prediksi Kebangkrutan pada Perusahaan Perbankan di BEI

This study aims to determine the results of predictions for bankruptcy of banking companies listed on the IDX in 2017-2019 using the Altman Z-Score, Springate, Ohlson, Grover, and Zmijewski methods. To analyze and test whether there are differences in the calculation results between the Altman, Springate, Ohlson, Grover, and Zmijewski methods in predicting bankruptcy in banking companies listed on the IDX in 2017-2019. And to find out which method is the most accurate in predicting bankruptcy in banking companies listed on the IDX in 2017-2019. The population used in this study were all banking companies listed on the IDX for the period 2017-2019. The sample in this study were 16 companies selected with certain criteria by purposive sampling method. The data in this study are quantitative data. The data sources in this study are secondary sources obtained from the annual financial statements published from the Indonesia Stock Exchange for the 2017-2019 period. Data collection techniques use documentation techniques. The data analysis method used descriptive statistical techniques, normality tests, hypothesis testing by paired sample t-test and prediction model accuracy tests, the results of the study show that there are significant differences between the Altman, Springate, Ohlson, Grover, and Zmijewski methods and there are methods with the highest level of accuracy, the Grover model of 91.67%.

Nuclear structure of Xe126

Background: The $(N&lt;82)\mathrm{Xe}$ isotopes with only four valence protons are known to be \ensuremath{\gamma} soft and to have the spectrum similar to the O(6) limiting symmetry.Purpose: Study the validity of the $\mathrm{O}(6)\ensuremath{\supset}\mathrm{O}(5)$ symmetry in the various vibrational bands of the $N=72 ^{126}\mathrm{Xe}$ isotope.Methods: Comparison of the $^{126}\mathrm{Xe}$ spectrum with O(6) symmetry. Apply the microscopic theory of dynamic pairing plus quadrupole (DPPQ) model and the interacting boson model (IBM-1). The energy spectrum, absolute $B(\mathrm{E}2)$ values and E2 transition ratios are evaluated. The odd-even spin staggering in the \ensuremath{\gamma} band is displayed, and the potential-energy plot is used to determine the shape of the nucleus.Results: The predictions of the eigenvalues and the $B(\mathrm{E}2)$ values and the interband $B(\mathrm{E}2)$ ratios extended over the five excited bands up to $\ensuremath{\tau}=5$ in the O(6) multiplet view. The O(5) symmetry is well preserved, and the O(6) symmetry is slightly broken.Conclusions: The predictions in the DPPQ model provide an alternative framework to the fluctuations in the O(6) quantum numbers in the IBM framework. The DPPQ model predictions are in fair agreement with experiment. The IBM-1 predictions provide a complementary view.

Bayesian paired comparison with the bpcs package

This article introduces the bpcs R package (Bayesian Paired Comparison in Stan) and the statistical models implemented in the package. This package aims to facilitate the use of Bayesian models for paired comparison data in behavioral research. Bayesian analysis of paired comparison data allows parameter estimation even in conditions where the maximum likelihood does not exist, allows easy extension of paired comparison models, provides straightforward interpretation of the results with credible intervals, has better control of type I error, has more robust evidence towards the null hypothesis, allows propagation of uncertainties, includes prior information, and performs well when handling models with many parameters and latent variables. The bpcs package provides a consistent interface for R users and several functions to evaluate the posterior distribution of all parameters to estimate the posterior distribution of any contest between items and to obtain the posterior distribution of the ranks. Three reanalyses of recent studies that used the frequentist Bradley–Terry model are presented. These reanalyses are conducted with the Bayesian models of the bpcs package, and all the code used to fit the models, generate the figures, and the tables are available in the online appendix.

Methodological Framework for the Development of an English-Lithuanian Cybersecurity Termbase

The aim of the paper is to present a methodological framework for the development of an English-Lithuanian bilingual termbase in the cybersecurity domain, which can be applied as a model for other language pairs and other specialised domains. It is argued that the presented methodological approach can ensure creation of high-quality bilingual termbases even with limited available resources. The paper touches upon the methods and problems of dataset (corpora) compilation, terminology annotation, automatic bilingual term extraction (BiTE) and alignment, knowledge-rich context extraction, and linguistic linked open data (LLOD) technologies. The paper presents theoretical considerations as well as the arguments on the effectiveness of the described methods. The theoretical analysis and a pilot study allow arguing that: 1) a combination of parallel and comparable corpora enable to considerably expand the amount and variety of data sources that can be used for terminology extraction; this methodology is especially important for less-resourced languages which often lack parallel data; 2) deep learning systems trained by using manually annotated data (gold standard corpora) allow effective automatization of extraction of terminological data and metadata, which enables to regularly update termbases with minimised manual input; 3) LLOD technologies enable to integrate the terminological data into the global linguistic data ecosystem and make it reusable, searchable and discoverable across the Web.

Abstract 12648: Improvements In Post-operative Cardiac Surgery Arrhythmia Identification Using The Atriamp Signals

Background: Following cardiac surgery, as many as 60% of patients will experience an arrhythmia. These arrhythmias are associated with increased morbidity and occasional mortality. Therefore, rapid and accurate identification is paramount to the improvement of patient outcome. Unfortunately, until now monitoring was limited by lack of timeliness or clarity. Here we evaluate the confidence and accuracy of rhythm diagnosis using the AtriAmp, a UW device that allows continuous arrhythmia monitoring. Methods: An ongoing IRB approved prospective observational study of children less than or equal to 18 years of age admitted to the PICU with atrial pacing wires following congenital heart surgery. The AtriAmp was connected to atrial pacing wires and the atrial ECG (AEG) was displayed along with a surface ECG on GE monitors. Nine different types of arrhythmias were collected over the course of the first five months of the study. A 20-question online survey was given to critical care and cardiology providers. Ten questions displayed signals from only the surface leads, the other ten showed the same arrhythmias with AtriAmp signal also displayed. Answers were evaluated for confidence and accuracy. Results: 40 providers were given the survey with 72% completing at the time of this abstract submission. Paired t-tests and mixed effects modeling were used to assess the data. The overall accuracy of diagnosis increased when using the Atriamp signals along with the surface ECG, but it was not statistically significant (p=0.07). Improvements in accuracy were most notable with atrial ectopic tachycardia (AET), Ventricular tachycardia (VT) and junctional ectopic tachycardia (JET). Provider confidence in diagnosis increased significantly when using the Atriamp signals (48%) compared to using only the surface ECG (62%) to diagnose arrhythmias (p&lt;0.001). Conclusion: Use of the AtriAmp increased provider confidence in the diagnosis of post-operative arrhythmias when compared to the same arrhythmias seen on surface electrograms. Future research among a larger sample of providers is needed to further evaluate the use of AtriAmp in arrythmia diagnosis.

How does the digital innovation process unfold in practice? A novel third-generation and empirical-based need–solution pairing model

PurposeThere is a lack of empirical-based models derived from practice to explain the digital innovation process. The authors investigate how the digital innovation process unfolds in practice.Design/methodology/approachThe authors undertake an exploratory and phenomenological study of 21 Malaysian small and medium enterprises (SMEs) in the information and communication technology (ICT) sector.FindingsThe findings show that the delineation between digital innovation process and outcome is blurred in practice, due to the process' iterative nature. Under this process, customers' role has changed from being passive receivers of innovative products to active reviewers, testers, influential decision-makers, initiators and co-creators at different review points in the innovation process. Enterprises' role has expanded from being the initiator of the innovation process to being a cogitative actor by seeking and absorbing knowledge from customer reviews into the digital innovation process. Market analysis is often the initiator of the digital innovation process, and the findings shed light on the underlying causative mechanisms of the initiation stage, which are understudied and not well understood in the existing literature.Originality/valueThe study contributes to academic knowledge by answering scholars' call for developing third-generation practice-based innovation models, which accounts for enterprises' context-specificities and internal and external environments, and for exploring the suitability of the need–solution fit approach for the digital innovation process. Such models have only been conceptually advocated in the literature. The study also informs practitioners on the organizational and operational activities involved in managing and strategizing for the digital innovation process.

Upaya Meningkatkan Keterampilan Heading melalui Variasi Latihan Berpasangan di Kelas VIII D MTs Al-khoirot Pagelaran Kab. Malang Tahun Akademik 2021

To improve students' skills in big ball sports, one of which is football, qualified and skilled human resources are needed. For this reason, a good training method is needed to improve achievement, there are several heading training models in the form of pair exercises that can be used in soccer games. The research was conducted using the CAR (classroom action research) method. This study aims to improve heading skills through a variety of paired exercises in class VIIID at Mts Al-Khoirot performances, Malang Regency. variables in this study are divided into 3, namely (1) input variables; (2) process variables; (3) output variables. The research subjects were students of class VIII D Mts Al-Khoirot Pagelaran totaling 33 students. The technique for collecting data in research is the test. Then what is collected is analyzed by triangulation. The test is also guided by the lesson plans that have been made with stages of 2 cycles at the end of each cycle, tests are also held so that the authors know whether the first cycle is going well and the second cycle is to perfect the first cycle. The results showed that this classroom action research (CAR) was as follows: the activity of class VIII D students of Mts Al-Khoirot Pagelaran in performing heading skills with the paired learning model approach effectively experienced a significant increase. The increase in learning outcomes is seen in the acquisition of mastery learning outcomes both classically and individually. It means that the hypothesis which states that if a paired model is used then the ball heading ability in the football game of the students of Mts Al-Khoirot Pagelaran Kab. Malang was well received by students. For the first cycle, there were 9 children who did not complete with 2 children who did not follow because of illness with a score between 70-90, while for the second cycle 33 students passed with all students present and the average score of students was 75-90. Students are declared passed if students have a minimum score of 75 with the highest score of 90.