Reviewerly/exHarmony huggingface dataset:
Implementation of balance scorecard and key performance indicator on customer service employee productivity

This research aims to find out the implementation of balance scorecard and key performance indicator on customer service employee productivity. Participants of this study were customer service employees. This method of research is qualitative. Data collection techniques by means of observation, documentation, and interviews. Qualitative data analysis used includes the stages of data analysis is data reduction, data display, and conclusion drawing. The research concluded that the implementation of Balance Scorecard and Key performance indicator as a Productivity Meter for Customer Service Employees in Larissa Aesthetic Center has been good. This can be proven by the increase in Rupiah Revenue from MVG Customer service in 2019 amounting to Rp. 2,201,831,000. A customer perspective, calculated based on customer retention, shows that the customer retention has increased by 0.7 %. Thus, it can be concluded, that a customer perspective as measured by customer retention is good. This research has contributed to uncovering the influence of Balanced Scorecard on the design of performance management systems in companies and non-profit organizations that are beneficial for corporate evaluation and academic studies. For further research it is recommended, that it extends the observation period by comparison between years, using different organizations or companies, and as well as the addition of research variables.
Cooperative Joint Attentive Network for Patient Outcome Prediction on Irregular Multi-Rate Multivariate Health Data

Due to the dynamic health status of patients and discrepant stability of physiological variables, health data often presents as irregular multi-rate multivariate time series (IMR-MTS) with significantly varying sampling rates. Existing methods mainly study changes of IMR-MTS values in the time domain, without considering their different dominant frequencies and varying data quality. Hence, we propose a novel Cooperative Joint Attentive Network (CJANet) to analyze IMR-MTS in frequency domain, which adaptively handling discrepant dominant frequencies while tackling diverse data qualities caused by irregular sampling. In particular, novel dual-channel joint attention is designed to jointly identify important magnitude and phase signals while detecting their dominant frequencies, automatically enlarging the positive influence of key variables and frequencies. Furthermore, a new cooperative learning module is introduced to enhance information exchange between magnitude and phase channels, effectively integrating global signals to optimize the network. A frequency-aware fusion strategy is finally designed to aggregate the learned features. Extensive experimental results on real-world medical datasets indicate that CJANet significantly outperforms existing methods and provides highly interpretable results.
Improved C-Language Implementation of AES Algorithm for WSN

Various IoT applications use wireless sensor networks (WSN) that require secured communication links in order to avoid cyberattacks. WSN interconnects numerous sensors that acquire specific parameters for different applications such as environment monitoring, health supervising, perimeter security and safety and so on. The sensor node can encrypt data onboard in order to ensure information security. Every sensor node has limited resources and processing capacity. AES is a very powerful encryption algorithm that can use private encryption keys of 128, 192 or 256 bits. For WSN, Arduino is a good option to implement a sensor node with temperature, relative humidity, pressure, light, air quality and/or gas sensors. The sensors acquire the environmental parameter values. Then, they sent them by the communication link to a central node, in order to store and analyze them. It is important to send information encrypted not as a plain text, by the mean of an encryption algorithm. We choose to implement Advanced Encryption Standard (AES) in C programming language, with various improvements of the algorithm itself. The program runs on a dual Arduino Due-based system with multiple sensors for environmental monitoring.
Research on the Practical Teaching of Data Structures and Algorithms Course

The success or failure of practical teaching in data structures and algorithms course determines the success or failure of the course group. The reform of practical teaching in this course takes the course group as the background and aims to meet the needs of students at different levels. It proposes a hierarchical practical teaching mode involving three levels in terms of foundation, design, and synthesis driven by cases throughout the whole course group and a fine process control mechanism based on multi-stage process assessment.
Image mixed gaussian and impulse noise elimination based on sparse representation model

&lt;p&gt;A modified mixed Gaussian plus impulse image denoising algorithm based on weighted encoding with image sparsity and nonlocal self-similarity priors regularization is proposed in this paper. The encoding weights and the priors imposed on the images are incorporated into a variational framework to treat more complex mixed noise distribution. Such noise is characterized by heavy tails caused by impulse noise which needs to be eliminated through proper weighting of encoding residual. The outliers caused by the impulse noise has a significant effect on the encoding weights. Hence a more accurate residual encoding error initialization plays the important role in overall denoising performance, especially at high impulse noise rates. In this paper, outliers free initialization image, and an easier to implement a parameter-free procedure for updating encoding weights have been proposed. Experimental results demonstrate the capability of the proposed strategy to recover images highly corrupted by mixed Gaussian plus impulse noise as compared with the state of art denoising algorithm. The achieved results motivate us to implement the proposed algorithm in practice.&lt;/p&gt;
CFR-MIX: Solving Imperfect Information Extensive-Form Games with Combinatorial Action Space

In many real-world scenarios, a team of agents must coordinate with each other to compete against an opponent. The challenge of solving this type of game is that the team's joint action space grows exponentially with the number of agents, which results in the inefficiency of the existing algorithms, e.g., Counterfactual Regret Minimization (CFR). To address this problem, we propose a new framework of CFR: CFR-MIX. Firstly, we propose a new strategy representation that represents a joint action strategy using individual strategies of all agents and a consistency relationship to maintain the cooperation between agents. To compute the equilibrium with individual strategies under the CFR framework, we transform the consistency relationship between strategies to the consistency relationship between the cumulative regret values. Furthermore, we propose a novel decomposition method over cumulative regret values to guarantee the consistency relationship between the cumulative regret values. Finally, we introduce our new algorithm CFR-MIX which employs a mixing layer to estimate cumulative regret values of joint actions as a non-linear combination of cumulative regret values of individual actions. Experimental results show that CFR-MIX outperforms existing algorithms on various games significantly.
Engineering of Reliable and Secure Software via Customizable Integrated Compilation Systems

Lack of software quality can cause enormous unpredictable costs. Many strategies exist to prevent or detect defects as early in the development process as possible and can generally be separated into proactive and reactive measures. Proactive measures in this context are schemes where defects are avoided by planning a project in a way that reduces the probability of mistakes. They are expensive upfront without providing a directly visible benefit, have low acceptance by developers or don't scale with the project. On the other hand, purely reactive measures only fix bugs as they are found and thus do not yield any guarantees about the correctness of the project.In this thesis, a new method is introduced, which allows focusing on the project specific issues and decreases the discrepancies between the abstract system model and the final software product. The first component of this method is a system that allows any developer in a project to implement new static analyses and integrate them into the project. The integration is done in a manner that automatically prevents any other project developer from accidentally violating the rule that the new static analysis checks. The second component is a way to directly integrate system models (e.g. from UML) into the project by treating the model as a direct input to the compiler, just like any other source code. These two components together allow developers to handle complex situations that are only relevant to the given project. The entire project gets analyzed for the correct usage of nontrivial APIs or other hazards which either are bugs or are likely to turn into bugs in future refactorings. Thus, the new method permits the incremental introduction of formal analysis without forcing a project's developers to change to unfamiliar habits or styles. At the same time, it allows preventing classes of defects automatically, yielding immediate gains from the first usage of the new method.
Reinforcement Learning Game Training: A Brief Intuitive

This paper aims to give a simple overview of one of the applications of reinforcement learning that is game training. Game training is actually an application of Artificial Intelligence that combines Reinforcement learning and Deep learning to make a computer program play games just like humans do, but the key idea behind this is reinforcement learning. Deep learning actually plays a supportive yet important role. This paper focuses on reinforcement learning part and summarizes the key concepts one must know and understand before getting into this field. Some additional concepts are also explained along with the main concepts to build a better understanding.
FPGA Synthesis of an AES Encoder Circuit for Vehicular Communication Networks

Data security is essential for all network applications including vehicular communications. Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) wireless communication links are exposed various attacks involving data that are critical for the passenger safety. Therefore we must secure the vehicular data in order to avoid false information to be sent to the drivers and accidents to be produced. We choose Advanced Encryption Standard (AES) to implement as a hardware data encryption module with good performances, focused on low delay and high-speed data processing in defiance of the circuit area. FPGA synthesis of the AES-128 circuit is done and its performances are presented.
Multi-stage Perception, Positioning and Planning for Automatic Wireless Charging of AGVs

The developing wireless charging technology has great potential for application on Automated Guided Vehicles (AGV). However, due to the strict requirements for high-efficiency wireless charging, it is difficult to navigate towards the charging pile at one go, especially under large-scale semi-structured or unstructured scenes where there have not enough features to obtain precise enough global positioning. Furthermore, single-stage planning relies largely on AGV's control performance, which often leads to failed alignment. In this paper, we discuss the factors that impact wireless charging efficiency and determine the required positioning accuracy. Accordingly, a multi-stage perception, positioning and planning method composed of coarse positioning, dynamic adjustment, and end-to-end alignment is proposed. In the coarse positioning stage, the use of iterative closest point (ICP) and simultaneous localization and mapping (SLAM) allows the AGV to relocate and reach the designated area flexibly and quickly. In the dynamic adjustment stage, AprilTag and LiDAR inertial odometry (LIO) is fused to estimate AGV's pose more accurately by addressing problems with AprilTag exceeding camera's field of view (FOV) or large observation errors at long distance. Finally, high-precision positioning information is obtained in the end-to-end alignment stage with coupled monocular camera and 2D LiDAR measurements. In each stage, different path constraint and obstacle avoidance strategy for motion planning are adopted to achieve higher efficiency. We show that with the proposed method, automatic wireless charging tasks could be performed without the need of readjustment, even under unstructured environment.
Curvature-Constrained Vector Field for Path Following Guidance

This paper introduces a new vector field guidance method to generate continuously flyable paths for unmanned air vehicles. The central idea of the proposed vector field approach is imbibed in the commanded course angle, which is expressed as a nonlinear function of the position error with respect to the desired path. Considering straight line and circular paths, the asymptotic behavior of position error is shown to converge to zero. Analysis of path curvature establishes a significantly lower maximum value as compared to a popular existing method. Simulation results are presented considering a two-dimensional kinematic model of the vehicle. Overall, the method presents an easily computable path following solution with superior curvature characteristics.
Analysing the Pragmatic Content in the Conversation Sections in Indonesian ELT Textbooks

Pragmatic competence is a core part of communicative competence and has become the main focus of teaching and learning process in today’s English language teaching. Thus, it is pivotal to have more of pragmatic materials in English textbooks since they are the major references used in the classroom. This study examined the conversation section in the series of Indonesian ELT textbooks to see whether the pragmatic content as required in the curriculum is fulfilled. Using Searle’s speech acts model as the framework, content analysis method was applied by using descriptive approach in analysing the illocutionary acts and forces provided in the textbooks. The findings indicate that despite their occurrences on the textbooks, some of the speech acts provided were low in frequency and lacked variety to develop better pragmatic competence for the students. This has significant implications on the textbook writers in developing content materials for the pragmatic competence.
THE FORMATION OF LEADERSHIP QUALITIES OF THE STUDENTS AS A TASK OF EDUCATIONAL ACTIVITY OF THE STUDENT GROUP CURATOR

The article, based on the analysis of scientific research, clarifies the essence of the concept of «leadership qualities». To analyze the state and effectiveness of the formation of leadership qualities of the students, it is suggested to use the three interrelated criteria: cognitive, motivational and activity. Three levels of the formation of leadership qualities of the students are characterized – high, average and low based on the manifestation of the indicators of the certain criteria. The article substantiates the expediency of attributing the formation of leadership qualities of students to the priority tasks of educational activities of the curator of the student group. The content of the educational work of the curator of the student group on the formation of leadership qualities of students, in particular: promoting the development of leadership knowledge and skills of students, expanding their awareness of leadership in general, and its role for self-realization in future professional activities; stimulating students to develop (self-development) leadership qualities in order to achieve common group goals; cohesion of the student group as an environment of manifestation and formation of leadership qualities of the students; encouraging the student participation in the self-organization of the group, involving students in the activities of student assets, stimulating active participation in community activities; ensuring that students master the methods of effective organizational work and communicative interaction in the group; creating conditions for enriching the experience of leadership behavior of the students. The ways of effective use of innovative methods and forms of education for the formation of leadership qualities of the students are characterized. The support and encouragement of student initiatives to organize the life of the group are considered to be an important pedagogical tool in the activities of the student group curator to stimulate students to show leadership and behavior. It involves the creation of a curator of humane, subject-subject relationships with students, the organization of joint definition of goals and objectives of the group and the planning and distribution of assignments for their implementation.
Optimasi Hyperparameter TensorFlow dengan Menggunakan Optuna di Python: Study Kasus Klasifikasi Dokumen Abstrak Skripsi

In today's rapidly growing digital era, the role of computing in artificial intelligence is needed to be able to help business people. Both in the fields of economy, health, and education. The use of machine learning will help related parties in viewing, analyzing, and making decisions. With machine learning, all problems related to data can be solved quickly and precisely. The problem is that the thesis document will increase every year, it will become a useless document if the data processing is not carried out. Past thesis data can be used for analysis and decision-making in the next thesis era. Python is one of the most popular programming languages used for machine learning. One reason is that there are many python-based libraries. Keras is a python-based machine learning library. TensorFlow can be used when dealing with large amounts of data processing, including thesis abstract data. Thus, this study classified 140 thesis abstract documents using hard-TensorFlow with the aim that based on the abstract content it would be classified into 6 classes, namely Android Applications, Data Mining, RPL, SPK, Digital Image Processing, and Expert Systems. The results of the classification with training data as many as 82 documents with model setting batch size = 12 and epoch = 2 with an Accuracy value of 89.04%. While the test loss test data has a higher value than the Accuracy value obtained by 66.66%. By utilizing maximizing TensorFlow performance by adding a parameter that Scikit Learn has, namely Optuna. The test data was optimized with a trial value of 500, the Accuracy increased to 76.19%
Protocol State Machine Reverse Engineering with a Teaching-Learning Approach

In this work, we propose a novel solution to the problem of inferring the state machine of an unknown protocol. We extend and improve prior results on inferring Mealy machines, and present a new algorithm that accesses and interacts with a networked system that runs the unknown protocol in order to infer the Mealy machine representing the protocol's state machine. To demonstrate the viability of our approach, we provide an implementation and illustrate the operation of our algorithm on a simple example protocol, as well as on two real-world protocols, Modbus and MQTT.
Peningkatan Kecerdasan Verbal Linguistik Melalui Kegiatan Bernyanyi

Increasing Verbal Linguistic Intelligence through Singing Activity( An Action Research in TK Kemala Bhayangkari Kota Ternate). The aims of this research were: the process of increasing Verbal Linguistic through Singing Activity; the result of increasing Verbal Linguistic intelligences through singing activity. This research was applied in TK B Kemala Bhayangkari Kota Ternate, Respondents of this research were 20 childreen with two collaborators.&#x0D; The action research employed Kemmis and Taggart Procedures which consisted four process : Planning, Act; observing and Reflection. The collecting data used qualitative analyses and quantitative analyses. The result of this reseacrh showed that Using Singing activity can increase verbal Linguistic intelligence in early childhood, especially the students’ of TK B Kemala Bhayangkari Kota Ternate.
A General Framework for Teaching Software Engineering and Improving Collaboration Skills in Multidisciplinary Teams

International Engineering Accreditation (IEA) organizations measure, ensure and improve the quality of the engineering education in many colleges and universities worldwide. Multidisciplinary projects are required by the criteria of IEA organizations due to their contribution in students’ learning skills improvement.This paper presents a framework for Software Engineering Education based on the IEA criteria. So, a multidisciplinary project between computer engineers and designers is presented aiming to improve student’s understanding of software processes and increase their communication skills in multidisciplinary teams. The project includes the creation of a game application running on mobile phones. Computer engineer students form multidisciplinary teams, are assigned with distinct responsibilities, follow specific software engineering processes, participate on meetings and communicate via web-based project management tools. Their evaluation is made according to the IEA outcomes.As the results show, a multidisciplinary project structured according to specific IEA outcomes ensures students’ skills in software processes and give them an overall satisfaction. According to students’ surveys and overall project experience, methods and procedures for developing collaboration skills in multidisciplinary projects are necessary. The creation of a profession learning seminar improved student’s communication skills thus showing that additional methods towards this direction need to be further designed and tested.
Is a General Quality Model of Software Possible : Playability versus Usability?

This paper is very exploratory and addresses the issue ‘Is a general quality model of software possible?’. If possible, how specific can/should it be?’ ISO 25000 Series SQuaRE is generally regarded as a general quality model which can be applied to most kinds of software. Usability is one of the 8 characteristics of SQuaRE’s Product Quality Model. It is the main issue associated with SQuaRE’s Quality in Use Model too. it is the most important concept associated software quality since using is the only ultimate goal of software products. Playability, however, is generally regarded as a special type of usability, which can be applied to game software. This common idea contradicts with the idea that SQuaRE is valid for most kinds, at least many kinds, of software. The empirical evidences of this paper show that SQuaRE is too specific to be a general quality model of software.
SUMBER BELAJAR DAN MEDIA PEMBELAJARAN DALAM PELAKSANAAN KURIKULUM 2013 DI SDN 1 PIDODOWETAN

The purpose of this research is to find out the utilization of learning resources and learning media in the implementation of the 2013 curriculum at SDN 1 Pidodowetan in Patebon Subdistrict, Kendal. This research uses a cauldron method. The data source in this research was obtained from principals, teachers, and students in grades I, II, IV and V of SDN 1 Pidodowetan. Data in the form of observations and interviews. The implementation of thematic learning in the 2013 curriculum at SDN 1 Pidodowetan has been running for two years. The use of learning resources and learning media is still not optimal. Teachers are based on teacher and student books and other reference books. Learning becomes less meaningful because teachers do not prepare creative learning tailored to student development. The learning process is still teacher-centered so that students are still the object of education. Students are more interested in learning by using learning media that makes students actively participate.