Classical Training Research Articles

Pelatihan Komunikasi Assertif (Assertive Training) Pelajar SMP IT Insan Mulia Surakarta

This community service activity aims to provide an inculcation of an effective communication style, namely assertive communication at SMP IT Insan Mulia Surakarta.Online elearning causes students to have difficulty communicating, especially students of SMP IT Insan Mulia Surakarta. Some students still do not dare to refuse friends to play on the sidelines of study group activities or assignments, do not dare to ask the teacher during the learning process, are passive when they have arguments or ideas in organizational forums at school. If this is left without any preventive measures, it will have an impact on the development of student communication at SMP IT Insan Mulia Surakarta. The purpose of this activity is to provides training on effective communication styles, namely assertive communication. The method used in the delivery of communication styles is to use classical and group methods. This training was held for two days. On the first day of classical training in the form of materials and assignments, while the second day in small groups, namely the practice of assertive communication. The data collection instrument used an open questionnaire and observation. Based on the analysis of the instrument students showed changes in communication, namely students to convey their ideas or openly tell the conditions they are experiencing.

A MILP model for quasi-periodic strategic train timetabling

In railways, the long-term strategic planning is the process of evaluating improvements to the railway network (e.g., upgrading a single track line to a double track line) and changes to the composition/frequency of train services (e.g., adding 1 train per hour along a certain route). The effects of different combinations of infrastructure upgrades and updated train services (also called scenarios), are usually evaluated by creating new feasible timetables followed by extensive simulation. Strategic Train Timetabling (STT) is indeed the task of producing new tentative timetables for these what-if scenarios. Unlike the more classic train timetabling, STT can often overlook (or at least give less importance to) some complementary aspects, such as crew and rolling stock scheduling. On the other hand, the different scenarios are likely to lead to very different timetables, hindering the common and effective practice of using existing timetables to warm start the solution process. We introduce the concept of quasi-periodic timetables, that are timetables where certain subsets of trains need to start at almost (rather than precisely) the same minute of every period. The additional flexibility offered by quasi-periodic timetables turned out to be crucial in real-life scenarios characterized by elevated train traffic. We describe a MILP based approach for strategic quasi-periodic train timetabling and we test it on 4 different realistic what-if scenarios for an important line in Norway. The timetables produced by our algorithm were ultimately used by the Norwegian Railway Directorate to select 3 out of the 4 scenarios for phasing the progressive expansion of the JȪren line.

PELATIHAN WRITING SKILL DALAM PENULISAN ARTIKEL ILMIAH BERSAMA PERSEKUTUAN PELAJAR RIRING-RUMAHSOAL AMBON (PRRA)

Writing scientific papers is considered an important skill to be mastered by students. This relates to the writing of scientific papers as part of the tridharma of higher education. On the other hand, writing scientific papers can stimulate the growth of critical, analytical, and new ideas. However, many students complain that they lack ideas and can't find anything interesting to write about. In fact, many of them have to extend their study period because they have not finished their thesis. This is all constrained by the low ability of writing scientific papers among students. Therefore, the community service that the author does is training in writing skills (writing skills) in writing scientific papers at the Riring-Rumasalah Ambonese Student Association (PRRA). This training is carried out with a classical training pattern and focus group discussions in small groups. The results of this training show that the students' ability to write scientific articles is quite low, so they need further assistance

Using the Concept of Precedence as an Approach to Explain the Logical Interaction and Interrelationships among Corporate Social Responsibilities: Battal's CSR Train VS. Carroll ′s CSR Pyramid

Purpose: The model of CSR devised by the American scientist ″Archie B. Carroll in 1991″ - which became well- known in academic circles as Carroll′s CSR pyramid, has been criticized by academics and researchers. The researcher firmly believes that one of the most important reasons that led to the emergence of these criticisms was Carroll's adoption of the idea of the pyramid as a form to illustrate his idea of CSR. The content of the pyramid does not match the accompanying explanations given by Carroll. Carroll's CSR pyramid does not reflect the concept of simultaneous CSRs. Also, Carroll's CSR pyramid does not reflect the logical interaction and interrelationships among CSRs. It is also noted that, Carroll's pyramid reflects the expectations of stakeholders and does not reflect the expectations of companies from their commitment to their social responsibilities. This study aimed to design a model for CSR, in which the content of its figure matches the explanations attached to it, and reflects the concept of simultaneous CSRs, in addition to the logical interaction and the interrelationship among those responsibilities. Method: The researcher used the concept of precedence as an approach to explain the logical interaction and interrelationships among CSRs. The idea of precedence is clearly found only in the railway industry. The interaction of CSRs with each other can be likened to the interaction of the components of a classic train (a cockpit and coaches). Therefore, the researcher adopted the idea of the classic train as an innovative model to address some of the shortcomings of Carroll ′s pyramid. Battal's CSR train as an innovative model- in this study, can reflect the notion of simultaneous CSRs, the logical interaction and interrelationships among CSRs, and expectations and aspirations of both stakeholders and companies. Result: By adopting the idea of the classic train work and its components, this study was able to produce a model of CSR as an alternative model for Carroll′s pyramid (1991). Originality/Value: Battal ′s CSR train is an educational model that is designed to address some of the shortcomings of Carroll's CSR pyramid "as a figure and content." The content of Battal′s CSR train matches the attached explanation, and this will help to understand how CSRs interact with each other, as well as the concept of simultaneous CSRs. It is an enrichment of the thought of CSR.

PENDAMPINGAN GURU DALAM PEMAHAMAN KONSEP LOCAL WISDOM DAN PENYUSUNAN SOAL BERBASIS HOTS SEBAGAI UPAYA MENGEMBANGKAN BERPIKIR KREATIF SISWA SMP KOTA AMBON

Assessment is an important component in the learning process. The type of assessment provided must be in accordance with the characteristics of the subject and learning outcomes. Teachers' understanding of science concepts and preparation of HOTS questions is needed in the process of assessing student achievement. Learning in the small islands of Maluku requires teacher strategies in understanding the concept of local wisdom and preparing HOTS-based science questions as an effort to develop students' creative thinking skills in understanding local wisdom concepts and preparing HOTS-based science questions to develop students' creative thinking skills. The training and mentoring is carried out with a classical in-service training pattern, and on the job learning. The results of the service show that the ability of teachers to analyze local wisdom materials varies and needs to be assisted because they do not understand developing HOTS questions, and are used as guidelines for the success of the learning process for local wisdom materials

Numerical scheme for the generalised Serre–Green–Naghdi model

A numerical scheme for solving the recently derived generalised Serre–Green–Naghdi equations which produce a family of equations modelling waves in shallow water with varying dispersion relationships, is described. The numerical scheme extends schemes applied to the classical Serre–Green–Naghdi equations written in conservation law form and is the first validated scheme for all admitted dispersion relationships. The consistency of the described numerical scheme for all members of the family of equations is in contrast to other numerical schemes which require specialised modifications for individual members of the family of equations. A typical second-order implementation of this numerical scheme is then demonstrated and validated using known analytic solutions; the travelling solitary wave and the dam-break problem. The numerical method is further validated for general members of the family of equations using forced solutions. Select members of this family are then used to simulate the evolution of rectangular waves of depression for which there are experimental results. The numerical method is shown to be conservative, robust and second-order accurate for the entire family of equations. The validated numerical solutions support a classification of the family of equations based on their linear dispersive properties which includes advancing dispersive wave trains in contrast to classical trailing dispersive wave trains.

Trajectory Optimization for High-Speed Trains via a Mixed Integer Linear Programming Approach

This paper proposes a trajectory optimization approach for high-speed trains to reduce traction energy consumption and increase riding comfort. Besides, the proposed approach can also achieve energy-saving effects by optimizing the operation time between stations. First, an optimization model is developed by defining the objective function as a trade-off function of the traction energy consumption and riding comfort. In addition to constraints in the classic optimal train control model, three new factors–the discrete throttle settings, neutral zones, and sectionalized tunnel resistance–are considered. Then, the model is discretized and turned into a multi-step decision optimization problem. All the nonlinear constraints are approximated using piecewise affine (PWA) functions, and the trajectory optimization problem is turned into a mixed integer linear programming (MILP) problem which can be solved by existing solvers CPLEX and YALMIP. Finally, some case studies with real-world data sets are conducted to present the effectiveness of the proposed approach. The simulation results are compared with the practical running data of trains, which shows that the proposed model and the optimization approach save energy and improve the riding comfort.

Artificial Neuron-Based Model for a Hybrid Real-Time System: Induction Motor Case Study

Automatic Machine Learning (AML) methods are currently considered of great interest for use in the development of cyber-physical systems. However, in practice, they present serious application problems with respect to fitness computation, overfitting, lack of scalability, and the need for an enormous amount of time for the computation of neural network hyperparameters. In this work, we have experimentally investigated the impact of continuous updating and validation of the hyperparameters, on the performance of a cyber-physical model, with four estimators based on feedforward and narx ANNs, all with the gradient descent-based optimization technique. The main objective is to demonstrate that the optimized values of the hyperparameters can be validated by simulation with MATLAB/Simulink following a mixed approach based on interleaving the updates of their values with a classical training of the ANNs without affecting their efficiency and automaticity of the proposed method. For the two relevant variables of an Induction Motor (IM), two sets of estimators have been trained from the input current and voltage data. In contrast, the training data for the speed and output electromagnetic torque of the IM have been established with the help of a new Simulink model developed entirely. The results have demonstrated the effectiveness of ANN estimators obtained with the Deep Learning Toolbox (DLT) that we used to transform the trained ANNs into blocks that can be directly used in cyber-physical models designed with Simulink.

Effects of a Novel Proprioceptive Rehabilitation Device on Shoulder Joint Position Sense, Pain and Function.

Background and Objectives: Shoulder disorders are associated with pain, restricted range of motion and muscular strength, moderate disability and diminished proprioception. This study aimed to compare the effectiveness of an innovative technology-supported and a classical therapist-based proprioceptive training program in addition to conventional physiotherapy, on joint position sense (JPS), pain and function, in individuals with different musculoskeletal shoulder disorders, such as rotator cuff tear, subacromial impingement syndrome and superior labrum anterior and posterior tear. The innovative element of the proprioceptive training programme consists of the use of the Kinesimeter, a device created for both training and assessing shoulder JPS. Materials and Methods: The shoulder JPS test and the DASH outcome questionnaire were applied to fifty-five individuals (28 females, 27 males, mean age 56.31 ± 6.75), divided into three groups: 17 in the conventional physiotherapy group (control group); 19 in the conventional physiotherapy + classical proprioceptive training program group (CPT group); and 19 in the conventional physiotherapy + innovative proprioceptive training program group (KPT group). Assessments were performed before and after a four-week rehabilitation program, with five physiotherapy sessions per week. Results: When baseline and post-intervention results were compared, the value of the shoulder JPS and DASH outcome questionnaire improved significantly for the KPT and CPT groups (all p < 0.001). Both KPT and CPT groups showed statistically significant improvements in JPS, pain and function, compared to the control group which received no proprioceptive training (all p < 0.05). However, the KPT group showed no significant benefits compared to the CPT group. Conclusions: Our findings indicate that using the Kinesimeter device as a novel, innovative proprioceptive training tool has similar effects as the classical proprioceptive training programs among individuals with different non-operated musculoskeletal shoulder disorders such as: rotator cuff tear, subacromial impingement syndrome, and superior labrum anterior and posterior tear.

Peculiarities of Teaching Manual Surgical Skills at the Stages of Training a Surgeon at Academician E.A. Wagner Perm State Medical University

In the training of experienced surgeons, one of the priority and difficult to master areas is teaching manual skills. The classical training system does not allow you to repeatedly repeat certain manipulations that allow you to consolidate manual skills. At the moment, in order to increase the effectiveness of the educational process in teaching the manual skills of surgeons, it is necessary to use simulation training technologies, and it is necessary to clearly divide the educational process into training stages depending on the subject being studied and the level of the surgeon’s training.

Method of Transformation of Image Classification Labels into Segmentation Masks

Semantic image segmentation plays a crucial role in a wide range of industrial applications and has been receiving significant attention. Unfortunately, image segmentation tasks are notoriously difficult and different industries often require human experts. Convolutional neural networks (CNNs) have been successfully applied in many fields of image segmentation. But all of them still require a huge amount of hand-labeled data for training. A lot of research was conducted in the field of unsupervised and semi-supervised learning, which studies how to shrink the amount of training data at the same time preserving the quality of the model. But still another field of research - transformation of “cheap” (in terms of time, money and human resources) markup into “expensive” is novel. In this work a new approach of generating semantic segmentation masks, using only classification labels of the image, was proposed. Proposed method is based on the GradCam algorithm, which can produce image activation heatmap, using only class label. But GradCams’ heatmaps are raw for final use, so additional techniques and transforms should be applied in order to get final usable masks. Experiments were conducted on the task of detecting defects on steel plates — Kaggle- Severstal: Steel Defect Detection. After that Dice metric was computed using a classical training approach and proposed method: classical approach - 0.621, proposed method - 0.465. Proposed approach requires much less human resources compared to the classical approach. Moreover, after visual inspection of results it is obvious that the proposed approach has successfully completed the task of defect localization.

Classical paradigms versus complexity thinking in engineering education: an essential discussion in the education for sustainable development

PurposeThis paper aims to discuss how the theory of complex thinking can be considered an interesting element in engineering education, especially in the context in which challenges toward sustainable development are multidisciplinary.Design/methodology/approachThis viewpoint synthesizes the main reflections and discussions generated during a process of debate, research and creation of a proposal for an undergraduate engineering course at a higher education institution in Brazil. The literature on engineering education, sustainability and complexity was considered in an integrated way. Debates were conducted considering the authors’ knowledge and experience as professors of engineering courses and researchers in the field of sustainability. A qualitative and reflexive approach was used to organize the main discussions.FindingsThe prevailing classical engineering paradigm trains professionals to think from a Cartesian, reductionist perspective, appropriate for solving well-structured problems with known solution paths and convergent answers. However, addressing sustainability challenges requires a different kind of thinking capable of dealing with situations characterized by uncertainty, emergence and incompleteness of knowledge. Complexity thinking can be useful for this purpose as it provides a broad system approach to deal with ill-defined, ill-structured and unpredictable problems. This study can be understood as a call to researchers and professionals to consider the value and importance of complexity thinking to advance engineering education for sustainability.Originality/valueThe need to overcome the limits of the classical engineering paradigm is emphasized in the context of sustainability. Complex thinking is considered as a path toward a paradigm shift in engineering education for sustainability. It can contribute to the training of professionals to face pressing challenges now and in the future. This viewpoint provides some insights to enhance debates on education engineering.

Effects of classical olfactory training in patients with COVID-19-related persistent loss of smell.

PurposeThe management of post-COVID-19 persistent olfactory dysfunction (OD) is uncertain. Currently, olfactory training is the only evidence-based therapy for post-viral OD. In this study, we evaluated the effectiveness of classical olfactory training (COT) in the treatment of post-COVID-19 persistent OD.Materials and methodsPatients with persistent OD after COVID-19 were assessed using the Sniffin’ Sticks test. Fifty-one patients were then divided into two groups based on personal preference: the COT group (n = 31) included subjects who performed COT over 12 weeks, and the control group (n = 20) included subjects who did not receive any treatment. After the exclusion of eight patients, the olfactory performances of 43 patients were re-evaluated and compared to the baseline values.ResultsA significantly higher proportion of patients in the COT group improved their olfactory scores above the clinically important difference compared to the control group (40% versus 6%) (p = 0.014). The subjective smell improvement by COT was independent of age, gender, OD duration, presence of parosmia, or the initial olfactory score (all p > 0.05).ConclusionTwelve weeks of COT appears to increase the olfactory sensitivity in patients with persistent OD following COVID-19.

Training deep material networks to reproduce creep loading of short fiber-reinforced thermoplastics with an inelastically-informed strategy

Deep material networks (DMNs) are a recent multiscale technology which enable running concurrent multiscale simulations on industrial scale with the help of powerful surrogate models for the micromechanical problem. Classically, the parameters of the DMNs are identified based on linear elastic precomputations. Once the parameters are identified, DMNs may process inelastic material models and were shown to reproduce micromechanical full-field simulations with the original microstructure to high accuracy. The work at hand was motivated by creep loading of thermoplastic components with fiber reinforcement. In this context, multiple scales appear, both in space (due to the reinforcements) and in time (short- and long-term effects). We demonstrate by computational examples that the classical training strategy based on linear elastic precomputations is not guaranteed to produce DMNs whose long-term creep response accurately matches high-fidelity computations. As a remedy, we propose an inelastically informed early stopping strategy for the offline training of the DMNs. Moreover, we introduce a novel strategy based on a surrogate material model, which shares the principal nonlinear effects with the true model but is significantly less expensive to evaluate. For the problem at hand, this strategy enables saving significant time during the parameter identification process. We demonstrate that the novel strategy provides DMNs which reliably generalize to creep loading.

Vascular education through e-Learning.

Background: The COVID-19 pandemic has changed everyday life and work in many ways. As travelling to meetings and conferences was almost completely suppressed for most of healthcare professionals, e-Learning became increasingly prominent. The overall utility of e-Learning during the COVID-19 pandemic as well as its shortcomings in the international community of vascular surgery were assessed through the EL-COVID study. Regional variability was observed amongst participating nations, which is currently being addressed through several ongoing subgroup analyses. Our study completes the aforementioned efforts and aims to investigate the adherence and adoption of vascular e-Learning in Germany. Methods and participants: Using an online survey, EL-COVID gathered answers from 856 vascular surgeons, of whom 70 were located in Germany. We analyzed the answers of 62 German responders that attended at least one e-Learning activity and compared them with the remaining worldwide data. Results: Out of all European countries, Germany was best represented and ranked second worldwide after Mainland China (n=109). 30.6 percent of the German responders were female (vs. 20% worldwide; p=0.048) and 56.4% were vascular surgeons with >5 years of practice (vs. 56.3; p=0.975). The international cohort generally engaged in more e-Learning. Most German participants attended less than 4 online activities, while only 24.2% took part in more than 4 such events (vs. 56.3; p<0.0001). While the overall impression of e-Learning activities during the COVID-19 pandemic was positive, German employers were less supportive of participation during working hours (30.6% vs. 44%; p=0.042). The main reason for not attending was lack of time due to increased workload (56.5% vs. 50%; p=0.328). National and international societies played a lesser role in promoting such activities in Germany (22.6% vs. 39.2%; p=0.010), the same accounts for social media (16.1 vs. 30.3; p=0.017). Conclusions: E-Learning complements the classical training methods and has been embraced as a relevant alternative in the time of the COVID-19 pandemic. The results of this survey appeal to German employers and national societies to improve support and dissemination of e-Learning activities in the vascular medicine community.

Investigating the Effects of Am rap and Classic Cross-fit Training in Freestyle Wrestlers on Physical Fitness Parameters

This study aims to investigate anaerobic strength alterations of wrestlers who perform AMRAP (As many reps as possible) and Classic CrossFit pieces of training. The research was implemented on 32 male wrestlers who were challenged in the Turkish Wrestling 1st League in the season of 2018-2019. The volunteer participants taken part in test groups performed CrossFit models in the preseason for 8-weeks; Group I (Classic CrossFit) and Group II (CrossFit AMRAP). Bodyweight, height, and age values were recorded respectively by creating measuring parkour and arranged on MS Excel spreadsheet program. Two-factor variance analysis was used in repetitive measurements for identifying the differences between pre and final measuring anaerobic strength values of the participants. As findings, it was observed there was a significant difference in terms of group x time interaction dimension in back squat movement, 1 min on behalf of AMRAP. According to the simple effect test results, there were significant values in both groups. The numerical increase in some performance values of the AMRAP CrossFit training group after 8-weeks of training was more prominent than the classic CrossFit training group. In addition, AMRAP CrossFit training was effective in reducing body weight. Both models were found to have a positive effect on their physical capacities effectively. Although there are studies on CrossFit in the literature, there is no significant study on AMRAP and thus this study might be the pioneer in terms of contributions to the literature and lead to further comments on sports science as well. Thus, this study is significant to reveal the effectiveness of Amrap and CrossFit training on physical fitness parameters.

The efficacy of balance and proprioception exercises in female patients with knee osteoarthritis: A randomized controlled study

Objective Loss of proprioception and balance disorders are commonly observed in patients with knee osteoarthritis. In this study, we aimed to investigate the effects of balance and proprioception exercises in patients with knee osteoarthritis. Design A single-center randomized trial with three parallel arms. Setting A tertiary health care facility in Turkey. Participants Female patients with knee osteoarthritis aged 40–70 years. Interventions Ten-week exercise program in Biodex training, classical balance training and isometric strengthening groups. Main measures Dynamic balance (overall stability index and the modified Clinical Test of Sensory Interaction and Balance), pain (visual analogue scale), physical function (30-s chair stand test and 40-meter fast-paced walk test) and quality of life (Knee Injury and Osteoarthritis Outcome Score). Results Eighty-nine patients enrolled in the study. The Biodex training group, the classical training group, and the control group had overall stability index values of 1.0 ± 0.07, 1.4 ± 0.07 and 1.4 ± 0.07, and the Modified Clinical Test of Sensory Interaction and Balance – Condition-3 values of 0.7 ± 0.04, 0.9 ± 0.04 and 0.9 ± 0.04 respectively, at the end of treatment. In terms of pain scores on movement, each group showed significant improvement compared to their baseline, and the classical balance training group had better scores than the control group. No other significant difference was found between the groups. Physical function and quality of life outcomes showed significant main effects only in the time factor. Conclusions Balance and proprioception exercises may have positive effects on dynamic balance and pain. The effects on physical function and quality of life should be investigated in further studies with larger sample.

Training in “reasoned handling care”: (Re)discovering meaning in work

Patient handling has had adverse health effects on nursing staff for many years. In order to prevent these effects, training programs using a demonstration-based pedagogy, aiming at promoting “good” handling practices, are often proposed. To develop a training program that enhances learners’ reasoning abilities and allows them to formulate situation-appropriate handling practices that emancipate the professional and respect the patient’s autonomy and well-being. A training program targeting nurses and nursing students was designed and implemented. Learners were requested to design the simulation scenarios themselves. The training sessions were recorded and analyzed. The scenarios designed by learners were pedagogically and subjectively relevant. Interactions during the different phases—design, simulation, and debriefing—allowed learners to assess acceptable and adapted solutions and to discuss their own practice, considering patient handling as a care activity in its own right. The training program appears as an efficient alternative to classic training programs. It develops learners’ reasoning abilities and restores meaning to nursing work.

PELATIHAN DAN PENDAMPINGAN PENGEMBANGAN HIDAYATULLAH TAHFIDZ GLOBAL ISLAMIC SCHOOLS

Abstract– This social service was based on the need assessment of the Hidayatullah Masjid Foundation for developing Hidayatullah Tahfidz Global Islamic Schools. This training was aimed at giving strategic management knowledge enhancement and capacity building for the so-called dewan Asatidz and Asatidziah or Islamic teachers of Play Group, Raudhlatul Atfal (Kindergarten), Madrasah Ibtidaiyah (Islamic Primary School), and Madrasah Tsanawiyah (Islamic Middle School). The training materials consisted of sector analysis, vision and mission unification, milestone, and implementation strategies and control. This training involved focus-grouped discussion, classical training, mentoring, and academic consultation. This training was evaluated by using 4 levels of Kirk Patrick assessment. Results of this training showed that the increase in the participants’ knowledge level reached 53.30%, and the perceptions of materials suitability, trainer performance, committee performance, and facilities are positive. Results of The evaluation showed that the participants had strong commitments to implement the training results. The participants had strong beliefs about the positive impact of the training on individuals, madrasah institutions, and the Hidayatullah Masjid Foundation. There needs improvement of time management for the next training. It is advised that this training is followed up by research and further training.

A Van Der Waals Photo‐Ferroelectric Synapse

AbstractFor hardware artificial intelligence, the central task is to design and develop artificial synapses with needed characteristics. Here, the design and experimental demonstration of a van der Waals (vdW) photo‐ferroelectric synapse are reported. In the photo‐ferroelectric synapse, the synaptic memory is extracted by reading the photocurrent, and written or edited by electrical pulses. The semiconducting vdW organic‐inorganic halide perovskite ((R)‐(–)‐1‐cyclohexylethylammonium)PbI3 (R‐CYHEAPbI3) photo‐ferroelectric serves as the model photo‐ferroelectric channel. Here, the vdW organic layer provides ferroelectric dipole and the PbI6 octahedron is responsible for photon absorption and charge transport. The R‐CYHEAPbI3 photo‐ferroelectric synapse show a writing/reading dynamics with &gt;200 synaptic states, close to 103 on/off ratio, and reasonable endurance and retention characteristics. With the experimentally measured weight dynamics (parallel reading through ferroelectric photovoltaic effect and writing by electrical pulses) of R‐CYHEAPbI3 synapses, the feasibility of using a crossbar circuit to implement classic training and inference of hand‐written digits is presented. An image recognition accuracy of up to 90% is obtained. The demonstration of such a vdW photo‐ferroelectric synapse opens a window in the design of advanced devices for artificial intelligence.