Assignment Methods Research Articles

Sensitivity Analysis and Robust Assignment of Natural Frequencies for Vibrating Systems Using the Receptance Method

This paper presents a new receptance-based method for the robust assignment of natural frequencies. This method aims to address the deviation of the actually achieved natural frequencies for target natural frequencies when assigning natural frequencies, which usually arises due to uncertainties in passive structural modifications (i.e. mass and stiffness modifications). The mathematical expression is derived for the sensitivity of the target natural frequency to the uncertainties in modification parameters, which are subsequently employed to characterize the potential deviations of the target natural frequencies in the total differential form. The obtained deviation expression is integrated into the optimization calculation of the natural frequency assignment as an extra penalty term to boost the acquisition of highly robust modification parameters. The proposed robust assignment method, as a non-probabilistic technique, can be employed without any knowledge of the probabilistic distribution of uncertainty in modification parameters. Moreover, it uses only the measured frequency response functions (FRFs), preserving the advantage of the receptance method not needing a numerical model. Two numerical examples and a comparison with a typical eigenstructure assignment method (reported in the literature) demonstrate that the proposed method can provide highly robust modification parameter solutions. The application of the proposed method to the natural frequency assignment of a laboratory water-filled pipeline system gives experimental evidence of its effectiveness.

An allocation approach for external truck tasks appointment in automated container terminal

Ports are the key connection of sea and land transportation. The coordination of container collection and distribution directly affect the handling efficiency of port in the entire supply chain. The optimization of tasks appointment for external trucks is crucial to improving the efficiency of container collection and distribution. The layout of the interchange points of external trucks are streamlined in automated container terminals where external trucks are commonly affected by the seaside operations. The traditional methods of external trucks assignment are inadequately applicable. In this paper an optimization model for the tasks appointment of external trucks is established for the joint optimization of external truck appointment and automated rail mounted gantry crane (ARMG) scheduling in the yard. Multiple objectives are generated including the balance of appointment among periods of time and between blocks. In this model the capacity constraints of the loading operations of external truck and moving operations of ARMGs between the seaside and landside are comprehensively considered. The model is solved by CPLEX and verified through sensitivity analysis. Different task appointment modes and various scenarios are compared and suggestions for selecting an optimization strategy are proposed. The experimental results show that the task appointment solutions effectively prevent the queuing of trucks, and balance the ARMG handling in automated container terminals, and herein the port efficiency is enhanced and the satisfaction of the carriers is promoted accordingly. It is also suggested that terminal managers should consider yard operations, operation capacity and the length of appointment period when considering the optimization of a task appointment schedule. While keeping optimize the appointment modes according to the operational conditions to improve the balance between the seaside and landside operations and reduce the idle of the ARMGs.

Deep-Learning-Based Automatic Detection of Photovoltaic Cell Defects in Electroluminescence Images

Photovoltaic (PV) cell defect detection has become a prominent problem in the development of the PV industry; however, the entire industry lacks effective technical means. In this paper, we propose a deep-learning-based defect detection method for photovoltaic cells, which addresses two technical challenges: (1) to propose a method for data enhancement and category weight assignment, which effectively mitigates the impact of the problem of scant data and data imbalance on model performance; (2) to propose a feature fusion method based on ResNet152-Xception. A coordinate attention (CA) mechanism is incorporated into the feature map to enhance the feature extraction capability of the existing model. The proposed model was conducted on two global publicly available PV-defective electroluminescence (EL) image datasets, and using CNN, Vgg16, MobileNetV2, InceptionV3, DenseNet121, ResNet152, Xception and InceptionResNetV2 as comparative benchmarks, it was evaluated that several metrics were significantly improved. In addition, the accuracy reached 96.17% in the binary classification task of identifying the presence or absence of defects and 92.13% in the multiclassification task of identifying different defect types. The numerical experimental results show that the proposed deep-learning-based defect detection method for PV cells can automatically perform efficient and accurate defect detection using EL images.

Empirical content of classic assignment methods: jungle and market economy

Empirical content of classic assignment methods: jungle and market economy

Variation in stress distribution modified by mandibular material property: a 3D finite element analysis

BackgroundTemporomandibular joint disorder (TMD) is a common oral and maxillary facial disease. Finite element method (FEM) has been widely used in TMD studies. Material assignment significantly affects FEM results. The differences in the methods of material assignment used in previous studies have not been comprehensively assessed for further calculations. MethodsThe mandible material modelling approaches were of four types, namely: uniform modelling with (A) cortical bone; and (B) cancellous bone; (C) semi-uniform modelling with division of cortical and cancellous bone; and (D) non-uniform modelling with Computed tomography (CT) gray value related modulus. Meanwhile, the Young's modulus of values ranging from 20 to 300 GPa were considered for the teeth. Ten modellings were used to analyze and discuss the differences in contact pressure and contact force. Results(1) The increase in teeth elastic modulus increased the maximum contact pressure on the alveolar bone and contact force on teeth, but induced insignificant stress variation on the temporomandibular joint; (2) The location of the maximum contact pressure was steady for all four modelling approaches of the mandibular material. However, the maximum contact pressure and contact force exhibited an insignificant difference. ConclusionsTeeth with a higher elastic modulus significantly enhanced the stress concentration in the alveolar bone; in contrast, it induced minor variations in the temporomandibular joint stress states. The extreme stress regions predicted by the four mandibular models were consistent with the actual damaged regions. However, non-uniform modellings based on CT values could better describe the mechanical properties of the human bone, which should be primarily considered.

Analisis Kesesuaian Kompetensi Manajerial Dosen Perguruan Tinggi X

Competent human resources will support the achievement of the university's vision and mission, while incompetent human resources will hinder the achievement of short, medium and long-term work targets, so that in the end it will hinder universities from developing and may even experience a decline. Lecturers as the spearhead of academic activities are faced with high job demands, apart from carrying out teaching, community service, and research, some lecturers also occupy structural positions which of course require managerial competence in order to carry out their duties optimally. This study aims to see the suitability of the competencies possessed by lecturers as structural position holders with the competencies required for the position. This study uses a competency assessment method consisting of tests and non-tests. The test form of assessment uses the CFIT, DISC, Kraeplin, Graphic and Warteg tests, while the non-test form uses interviews, observation, case studies and Leaderless Group Discussion. The subject of this study was a lecturer who served as head of the study program, male, 50 years old. The research results show that Mr. M has competencies that meet the requirements, namely integrity, interpersonal skills, customer focus, building business partnerships and driving execution. Meanwhile, the 4 competencies that still need to be improved to fulfill the position requirements as chair of the study program, namely change leadership, achievement orientation, empowering and innovation creativity. Steps that can be taken to improve these competencies include job assignment and mentoring methods.

Strategies to Strengthen the Affective Domain in Learning Pancasila and Citizenship Education for Class XII Students of MAN 4 Pandeglang

This study aims to determine the strategies to strengthen the affective domain in Civics learning in class XII students and to determine the inhibiting and supporting factors in implementing the affective domain strengthening strategy in Civics learning in class XII students at MAN 4 Pandeglang. This research uses a type of qualitative approach with descriptive methods. The results found were that the strategy of strengthening the affective domain of students used learning models and methods aimed at improving the affective domain of students for the better, such as the habituation model in the form of assignment methods and monitoring good attitudes and behavior of students, exemplary models in the form of method of displaying good attitude and behavior. The strategy to strengthen the affective domain can run well and students can follow and be able to achieve the goals of strengthening the affective domain. Then the way to overcome the obstacles experienced in implementing the strategy to strengthen the affective domain in Civics learning is to use a personal approach to students, especially students whose affective domain or attitude is lacking and also students who experience difficulties in learning.

An objective assignment method for siting new energy plants

This paper proposes a multi-criteria decision-making method for new energy power station site selection based on a fuzzy comprehensive analysis method. It is applied to make multi-criteria analysis decisions on the target location when selecting the address for building a new energy power station, to ensure the reasonableness of the corresponding weights of each index, and to give reasonable and scientific suggestions for decision-makers to obtain the expected results. We analyze the mechanism of the sequential relationship analysis method and fuzzy inverse entropy weighting method from the perspective of the index assignment method, and combine the two assignment methods by linear weighting, so as to lay the foundation for further construction of a multi-attribute hybrid index system with the coexistence of qualitative and quantitative indexes.

REFLECTIONS, PERCEPTIONS AND PRACTICES IN FORMULATING AND EVALUATING HOMEWORK IN PRIMARY EDUCATION

Homework is a controversial topic that frequently attracts the attention of teachers and researchers, who are looking to identify ways to make it as attractive and enjoyable as possible, relevant, and formative as well. There are various points of views and data, empirically based, concerning the utility, scope, impact of homework on students’ development. The aim of the study was to identify the reflections, perceptions, and stated practices of primary school teachers regarding the assignment and assessment of homework. Thus, 10 primary education teachers completed reflection diaries on homework, between May 26 and June 25, 2021 (a period of the schooling year with consolidations, evaluations, and gradual relaxation towards ending/summer holiday). The teachers were asked to record each two days their reflections. The coding of the entries in the reflection diaries was done and analyzed with MAXQDA, and it covered aspects like the purpose and role of homework, methods for effective assignment of homework, parental involvement, appropriate completion time, volume, etc. The results, informative for teachers and educational experts as well, reveal teachers’ perceptions regarding the degree of involvement of children and parents, the appropriate dosage of effort and the appropriate time for solving homework, practices of assigning and evaluating students’ homework.

PROTOMORPHISMS IN THE THEORY OF MARKOV ALGORITHMS AND BIG DATA OF SOCIO-ECONOMIC SYSTEMS

Protomorphisms known in category theory are investigated together with the theory of Markov algorithms. Protomorphisms are considered as an element extending the theoretical provisions of the theory of Markov algorithms. Protomorphisms are investigated in the big data of socio-economic systems in the tasks of countering money laundering and terrorist financing. Methods of assignment for protomorphisms of the absence of a preorder are considered. A synthesized method for recording protomorphism in a data cycle when entering input sample sets into a big data classification algorithm is considered. A method of writing a protomorphism using the alphabet M = λιτφп/αβδγχκμ for the N-scheme of the Markov algorithm is presented, by entering a new nonterminal symbol into it. Examples of protomorphisms in big data are considered. Protomorphisms are divided into those about the truth, which can be asked, and those for which it is impractical to make a judgment about truth or falsity. The Hempel paradox with protomorphisms is considered. For Hempel’s paradox with “classes”, the method of bringing the number of inductive observations to the total number of observations is specified. An example of filling an artificial intelligence database with protomorphism is considered. A practical example of the use of protomorphism in the task of countering money laundering and terrorist financing of the socio-economic system is given. It is shown that it is permissible to expand the alphabet M with new letters for some morphisms, separating them. It is concluded that in the task of countering money laundering and terrorist financing, it is advisable to use protomorphisms, since they can increase the level of completeness, reliability, and efficiency of the subsystem for countering money laundering and terrorist financing when making decisions.

Pelatihan Multimedia Pembelajaran al-Islam dan Kemuhammadiyah (AIK) berbasis website pada MGMP ISMUBA SMP/MTs Kabupaten Banyumas

Educators always strive to present learning materials optimally and are supported by adequate learning resources so students can master them completely. This is intended to equip partners by a) instilling awareness in training participants about the importance of developing learning multimedia; b) providing an understanding and insight into the multimedia concept of AIK learning for educators as a special feature of Muhammadiyah schools; 3) providing capabilities and skills in developing web-based learning multimedia to improve the quality of learning and teaching. Partners involved in this training activity are Ismuba teachers of SMP/MTs Muhammadiyah Kab. Banyumas with representatives of each school as many as 20 people. Implementation method with lecture, practice, and assignment methods. The steps of this training activity are divided into two theoretical, drill and demontration sessions, namely: the first theory, the urgency of PAI learning media (curriculum analysis). The second is the concept of AIK learning multimedia. And practice sessions, making website-based AIK learning multimedia using the Canva for Education platform. The results of the service, a) understanding of the learning media showed the pretest value of 88.9% increased to 94.4% for the post-test value. The training instills a common awareness that teachers' enthusiasm to find creative ideas about media designs or plans regarding the material needs to be trained on an ongoing basis. b) Mastering participants' abilities in website-based learning media using the Canva for Education platform has a tendency to increase activity and seriousness, making 22.2% more frequent in use. Supported by the success of the multimedia training, it is also proven by the increase in knowledge and skills by as much as 94.4%.

Pelatihan Supervisi Berbasis Kategori Guru Bagi Kepala Sekolah Dasar Kota Solok

Efforts to improve and improve the quality of the learning process cannot be separated from the role of professional teachers and principals. In the context of efforts to improve the quality of educational resources, especially teachers, it is necessary to carry out programmed and continuous supervision by school principals who also have competence in carrying out supervision. The purpose of this training is to provide knowledge and skills to school principals in implementing teacher category-based supervision. The method of implementing this training is through lectures, discussions, case studies, and assignment methods (recitation). Supervision competency improvement training in this proposal is grouped into 2 major activities, namely the delivery of material and guided assignments. Supervised assignments are carried out for three months after the training is given. In this guided assignment the school principal implements the supervision program documents that have been prepared at the training stage. During its implementation, the principal is guided by the service team and resource persons with an agreed schedule. Activity evaluation is carried out 3 times, namely before the main activity, during the process, and after the activity. Evaluation prior to core activities is carried out in the form of a pre-test. The results of the Pre-test and Post-Test of Solok city school principals showed that there was an increase in the principal's understanding of 27.5% in the aspects of: (1) supervisory competence, (2) understanding of curriculum content, approaches, and assessment based on literacy and numeracy, and (3) understanding related to the psychology of communication in the implementation of supervision.

PENYUSUNAN KURIKULUM OPERASIONAL PADA SATUAN PAUD BERBASIS KURIKULUM MERDEKA

Curriculum is dynamic and it needed to change to adjust to the context and goals of the society, however it is also not always easy for teachers who implement the curriculum. This community service activity aims to help PAUD teachers, especially Kindergarten (TK) levels in understanding the existence of curriculum changes, namely the Kurikulum Merdeka so that teachers can understand, plan, and implement learning at the kindergarten level. The target of this community service (PKM) activity is 25 kindergarten teachers in Mojokerto City. The PKM design carried out were: socialization of the independent curriculum and training in preparing activity plans in learning in kindergarten. This community service uses the lecture, discussion, assignment, and simulation methods, this PKM is carried out both online and offline to provide experience in compiling and implementing learning in kindergarten. The results of this PKM can be seen from the results of the pre-test and post-test. Kindergarten teachers in the City of Mojokerto already have knowledge of the Independent Curriculum but not in its entirety. Based on the results of a questionnaire filled out by 25 kindergarten teachers in Mojokerto City, it was found that only 8.7% of institutions had used the Kurikulum Merdeka. 52.2% use a mixed curriculum (50% PAUD 2013 Curriculum and 50% Kurikulum Merdeka). As many as 39.1% still use the 2013 PAUD Curriculum, so it can be concluded from this PKM is the creation of the ability of kindergarten teachers in preparing, planning and implementing Kurikulum merdeka appropriately.

MENGGUGAH KREATIFITAS MENGGAMBAR POSTER MELALUI PENUGASAN, PRESENTASI DAN APRESIASI UNTUK MENINGKATKAN HASIL BELAJAR MATA PELAJARAN SENI BUDAYA SISWA KELAS VIII A SMPN 1 SAWOO PONOROGO

One way so that the implementation of Cultural Arts learning can be carried out effectively, namely by assignment, presentation of appreciation as an alternative step in order to streamline and streamline the learning process. The assignment method, appreciation presentation was chosen because in this method students are required to express a lot of ideas freely, of course with the supervision and guidance of the class teacher. The formulation of the problem in this study is: Can learning by exploring ideas / ideas improve students' ability to visualize the form of poster images in the Cultural Arts? This research was conducted at SMP Negeri 1 Sawoo Ponorogo with the object of research being class VIII A students, totaling 40 students. From the results of this study, it can be concluded that learning with the assignment method and presentation of appreciation can improve students' ability to give opinions about the results of creative poster drawings in the subjects of Cultural Arts. This can be seen from the graph calculation. The results of the assessment of the appreciation presentation before and at the end of each class cycle for class VIII A showed a significant increase in learning outcomes in cycle 1 to cycle 2 (71.58-80.0), namely 8.42 points, or 11.76 %. From the data, the percentage increase it can be explained that it turns out that the assignment and presentation methods in this study can improve students' abilities in making creative works and appreciating them

The Implementation of Character Education Based on Bugis Local Wisdom in Social Science Subjects

This study aims to analyze three sub-problems, namely (1) the implementation of Bugis local wisdom-based character education in social studies subjects, (2) the role of Bugis local wisdom values in shaping student character in social studies subjects, and (3) the factors that influence the implementation character education based on local wisdom in social studies subjects. This type of research is descriptive qualitative. The informants consisted of 3 social studies teachers and 9 students of SMP Negeri 1 Patimpeng, Bone Regency who were selected using the cluster stratified random sampling technique. The results showed that the implementation of Bugis local wisdom-based character education in social studies subjects was carried out by the teacher designing character education material through classroom management first before starting learning, cooperation between schools and families, and making behavior guidelines in class. Character education is implemented using various learning models and methods, such as the STAD model, lecture, and assignment methods. The role of Bugis local wisdom values in shaping student character in social studies subjects is carried out by the teacher rewarding students who behave honestly, respect each other during discussions, and are responsible for the assignments given. Factors that influence local wisdom-based character education implementation in social studies include external (parents and teachers) and internal (students' ability to socialize) factors.

YoloXT: A object detection algorithm for marine benthos

In recent years, the marine economy has developed rapidly, and human demand for marine resources has increased greatly. At present, target detection technology has a wide range of applications and prospects in seabed observation and ocean engineering. However, the accuracy and robustness of existing target detection methods are low due to the complex underwater environment, poor lighting, and poor quality of undersea images and videos. To solve these problems, this paper proposes YoloXT, a new quantitative identification method for marine benthos. YoloXT introduces the DECA (Deformable Coordinate Attention) module, which expands the spatial awareness in feature extraction and can learn image features more effectively. Meanwhile FPST-PAN (Feature Pyramid S2win Transformer, Improved Path Aggregation Network) was proposed to deal with the problem of marine benthic target diversity. It further integrates deep and shallow features through multi-scale skip-connection and Transformer and improves the model's ability to deal with complex and changeable marine environments. Finally, the positive and negative sample assignment strategy OAA (Optimal Anchor Assignment) applied to the detection head is proposed. It effectively avoids the problem of unbalanced distribution of positive and negative samples caused by traditional sample assignment methods and marine benthos image noise. Experiments on the IOC-URPC dataset show that the mAP of YoloXT is 3.9% higher than that of YoloX, reaching 70.9%. YoloXT has demonstrated excellent performance in quantitative identification task of marine organisms, which can effectively contribute to the exploitation and conservation of marine resources. The source code is publicly available at https://github.com/F1veZhang/YOLOXT.

Collection of economic data using UB-04s: Is it worth the effort? Evidence from two clinical trials.

Cost collection using UB-04 forms for economic evaluation is challenging, as UB-04 collection is time and effort intensive and compliance is imperfect. Alternative data sources could overcome those challenges. The objective of this study is to determine the usefulness of UB-04 data in estimating hospital costs compared to clinical case report form (CRF) data. Health care utilization costs were compared from financial information in UB-04s and from an assignment process using CRF data, from the WRAP-IT (23 infections) and the Micra IDE trials (61 adverse events and 108 implants). Charge-based costs were calculated by multiplying charges in UB-04s and hospital-specific Cost-to-Charge ratios from the Centers for Medicare and Medicaid Services cost reports. The cost assignment process used clinical information to find comparable encounters in real world data and assigned an average cost. Paired difference tests evaluated whether both methods yield similar results. The mean difference in total infection related costs between methods in the WRAP-IT trial was $152 +/-$22,565. In the Micra IDE trial, the mean difference in total adverse event related costs between methods was -$355 +/-$8,298 while the mean difference in total implant related costs between methods was $-3,488 +/-$13,859. Wilcoxon tests and generalized linear models could not reject the difference in costs between methods in the first two cases. Cost assignment methods achieve results similar to costs obtained through UB-04s, without the additional investment in time and effort. The use of UB-04 information for services that are not mature in a health care system may present unexpected challenges, necessitating a tradeoff with other methods of cost assignment.

A machine learning-based framework for forecasting sales of new products with short life cycles using deep neural networks

Demand forecasting is becoming increasingly important as firms launch new products with short life cycles more frequently. This paper provides a framework based on state-of-the-art techniques that enables firms to use quantitative methods to forecast sales of newly launched, short-lived products that are similar to previous products when there is limited availability of historical sales data for the new product. In addition to exploiting historical data using time-series clustering, we perform data augmentation to generate sufficient sales data and consider two quantitative cluster assignment methods. We apply one traditional statistical (ARIMAX) and three machine learning methods based on deep neural networks (DNNs) – long short-term memory, gated recurrent units, and convolutional neural networks. Using two large data sets, we investigate the forecasting methods’ comparative performance and, for the larger data set, show that clustering generally results in substantially lower forecast errors. Our key empirical finding is that simple ARIMAX considerably outperforms the more advanced DNNs, with mean absolute errors up to 21%–24% lower. However, when adding Gaussian white noise in our robustness analysis, we find that ARIMAX’s performance deteriorates dramatically, whereas the considered DNNs display robust performance. Our results provide insights for practitioners on when to use advanced deep learning methods and when to use traditional methods.

A validation study on the factors affecting the practice modes of open peer review

In this paper we conduct a validation study on the factors affecting the practice modes of open peer review. Taking the Open Access Journals (OAJ) in Directory of Open Access Journals (DOAJ) as the research objects, we crawled the internet to gather their relevant data. Based on the method of categorical variable assignment, a quantitative analysis was performed on the qualitative factors that affect the practice modes of open peer review. A multi-dimensional analysis chart is used to illustrate the relationships between the factors. Optimal scale regression modeling and discriminant analysis were also employed to reveal the degrees of influences by the factors. The public categories of “type of open peer review” and “reviewer identity” are closely related to each other. “Reviewer identity” has evident positive influence on “type of open peer review”, and the degree of influence is the highest. Therefore, “reviewer identity” is the primary and most crucial factor affecting open peer review practice modes. “Review report” and “order of review report and publication” are the secondary ones. Whether or not the identities of review experts are open has become the most important factor affecting the practice modes of open peer review. Transparent peer review is currently the most effective practice mode of open peer review. Technologies like block chain can be used to address the psychological uneasiness for the peer review experts who are concerned with privacy issues. The fact that most OAJs use “pre-publication review” shows that open peer review still plays the traditional role of “academic goalkeeper”. Publication of peer review reports actually helps peer review experts augment their reputation, which in turn practically promotes the development of open peer review.

A Novel Algorithm for Scenario Recognition Based on MEMS Sensors of Smartphone.

The scenario is very important to smartphone-based pedestrian positioning services. The smartphone is equipped with MEMS(Micro Electro Mechanical System) sensors, which have low accuracy. Now, the methods for scenario recognition are mainly machine-learning methods. The recognition rate of a single method is not high. Multi-model fusion can improve recognition accuracy, but it needs to collect many samples, the computational cost is high, and it is heavily dependent on feature selection. Therefore, we designed the DT-BP(decision tree-Bayesian probability) scenario recognition algorithm by introducing the Bayesian state transition model based on experience design in the decision tree. The decision-tree rules and state transition probability assignment methods were respectively designed for smartphone mode and motion mode. We carried out experiments for each scenario and compared them with the methods in the references. The results showed that the method proposed in this paper has a high recognition accuracy, which is equivalent to the accuracy of multi-model machine learning, but it is simpler, easier to implement, requires less computation, and requires fewer samples.