Reviewerly/exHarmony huggingface dataset:
Perbandingan Metode Convolutional Neural Network Pada Klasifikasi Sel Darah Putih Menggunakan Sistem Cpu Dan Gpu

Abstrak Saat ini penggunaan metode Deep Learning dapat menjadi salah satu metode yang sering digunakan pada penelitian. Salah satunya adalah klasifikasi menggunakan metode Convolutional Neural Network. Banyak penelitian yang telah dilakukan mengenai bidang pemrosesan gambar yang digabungkan dengan berbagai teknik klasifikasi dan segmentasi untuk mendapatkan hasil alternatif pada klasifikasi. Penelitian ini menerapkan metode CNN untuk klasifikasi sel darah putih. Penetapan jumlah dan klasifikasi sel darah putih sangat penting dalam deteksi suatu penyakit pada tubuh seseorang, yang dapat mengakibatkan komplikasi pada suatu sistem kekebalan tubuh sehingga mengarah ke berbagai jenis penyakit. Klasifikasi sel darah putih dengan menerapkan metode CNN digunakan untuk membedakan 4 jenis sel darah putih antara lain Neutrofil, Eosinofil, Monosit, dan Limfosit. Untuk mengetahui kinerja klasifikasi yang paling optimal dengan waktu eksekusi yang paling cepat, penelitian ini membandingkan antara performansi proses klasifikasi menggunakan CPU dan GPU. Hasil yang diperoleh pada proses klasifikasi ini yaitu penggunaan GPU lebih unggul dengan nilai Speedup hingga 29 kali dan nilai akurasi hingga 99,93%. Kata kunci : Convolutional neural network, CPU, deep learning, GPU, sel darah putih. Abstract Nowadays, the use of the Deep Learning method can be one method that is often used in research. One of them is the classification using the Convolutional Neural Network method. Much research has been done on the field of image processing combined with various classification and segmentation techniques to obtain alternative results in classification. This study applies the CNN method for the classification of white blood cells. Determination of the number and classification of white blood cellsis very important in the detection of a disease in a personâ€™s body, which can lead to complications in an immune system that leads to various types of diseases. Classification of white blood cells by applying the CNN method is used to distinguish 4 types of white blood cells, including Neutrophils, Eosinophils, Monocytes, and Lymphocytes. To find out the most optimal classification performance with the fastest execution time, this study compares the performance of the classification process using CPU and GPU. The results obtained in this classification process are the use of GPU is superior with Speedup values up to 29 times and accuracy values up to 99.93%. Keywords: Convolutional neural network, CPU, deep learning, GPU, white blood cell.
A calibration method on 3D measurement based on structured-light with single camera

The 3D shape measurement technology based on structured-light with a single camera has many advantageous aspects on usability, such as non-contact, high precision, high speed etc. There are various kinds of software accepting its measurement results readily. That is why it has been widely used in reality. System calibration is the key step before it begins normal scanning, and the setting of parameters in calibration directly affects the accuracy of the measurement. Some problems exist in the process of its calibration, such as the process is complicated and hard to operate, always taking low accuracy for the scanning result. This paper aims to find methods to solve the problems. The 3D scanning system used in the research is composed of a Canada-made Point Grey CMOS industrial camera (FL3-U3-13Y3M-C) with a China-made lens, a Texas instrument projector DLP LightCrafter 4500 EVM. The parameters that can be set in the process of system calibration are discussed in the paper, and the scanning results with parameter change are evaluated based on the indicators of camera and projector’s reprojection error, scanning resolution and point cloud’s uniformity. The research concludes that the distance between the projector and the calibration board is a key factor needs to be controlled. It can be set up properly based on the indicators for the quality of scanned data, which improves the speed of system calibration and keep the collected point cloud data more stable.
Real-World Considerations for Deep Learning in Wireless Signal Identification Based on Spectral Correlation Function.

This paper proposes a convolutional neural network (CNN) model which utilizesthe spectral correlation function (SCF) for wireless radio access technologyidentification without any prior information about bandwidth and/or the centerfrequency. The sensing and classification methods are applied to the basebandequivalent signals. Two different approaches are elaborated. The proposedmethod is implemented in two different settings; in the first setting, signalsare jointly sensed and classified. Sensing and classification are conducted ina sequential manner in the second setting. The performance of both approachesis discussed in detail. The proposed method eliminates the threshold estimationprocesses of classical estimators. It also eliminates the need to know thedistinct features of signals beforehand. Over-the-air real-world measurementsare used to show the robustness and the validity of the proposed method andvarious wireless signals are successfully distinguished from each other withoutany a priori knowledge. The over-the-air real-world measurements are alsoshared in the format of SCF. The performance of SCF-based identification iscompared with the cases when fast Fourier transform and amplitude-phaserepresentation are used as the training inputs for CNN. The comparativeperformance of the proposed method is quantified by precision, recall, andF1-score metrics. Moreover, a setup to compare the performance of the proposedapproach with classical cyclostationary features detection (CFD) is prepared.Measurement results indicate the superiority of the proposed method againstCFD, especially at the low signal-to-noise ratio regime.
Design and modification of smart stick for visually impaired with stick finder

To improve navigation of visually disabled people we have designed an innovative stick using Arduino. This stick uses advanced technology to navigate with ease. The stick which we have modified is lighter in weight, affordable and easy to handle. This stick first uses ultrasonic sensors and detects obstacles. On sensing obstacles, the sensor passes this data to Arduino. Arduino uses C programming. It then processes this data and calculates the distance of obstacles from the person. If an obstacle is not close to the person then the circuit stays steady. If the obstacle is close to the person then the circuit sends a signal to the sound buzzer and vibrator. As the distance between person and obstacle gets reduced the sound of buzzer and vibrator goes on increasing. This system is even made for blind-deaf people as they have only sense as a way to understand any process with the help of vibration they can sense the obstacle. This system has one more feature i.e. A stick finder. This helps the blind person find the stick where they might have kept it with the help of a remote. Pressing the remote button sounds a buzzer on the stick which helps the person to find the stick. Thus, this system allows for obstacle detection as well as finding sticks misplaced by visually disabled people.
Cultural approach to the formation of professional competences of the specialist in the realities of modern education

The problem of a cultural approach realization to the specialist professional competences formation in the realities of the modern education is discussed in the article.The present realities which are characterized by the request of the society for a “new type specialist” give new requirements for education. Modern education can be supposed effective only when it, by forming the professional competences which are necessary for human life, will be comprehended from a cultural point of view as a person’s entry into culture. The article reveals the key competences which are necessary for any specialist in the present day realities, thanks to which his socialization and self-realization processes will proceed successfully. The historical background and universal conceptual ideas of the culturological approach realization to the specialist professional competences formation in the realities of the modern education without paying attention to the direction and profile of the specialist training are discovered in the article.The aim of the research is to characterize the essential ideas and opportunities for the cultural approach realization to the specialist professional competences formation in the realities of the modern education. Our research methodology was based on the application of the theoretical and practical methods complex, including such methods as the special cultural, philosophical, psychological, pedagogical and scientific-methodical literature extensive study on the stated problem, as well as educational and methodical documentation study of educational organizations based on analysis, synthesis, theoretical modeling; professional students development observation and analysis (with the help of questionnaires and tests made by the authors of this article). As the research result we made a conclusion that the specialist professional formation in the realities of the modern education goes simultaneously with the process of his humanitarian and personal development. Personal qualities (attitudes, motives, intelligence, emotional and volitional sphere of a person) determine the quality of his professional competences formation. The educational organization task is to create the favourable conditions for the student “entry” into the culture, it means to form a creative, culturologically filled educational environment for making an inimitable and unique professional and personal development of the modern specialist pathway in each case as the Culture Creator.
Cloud Applications for ICT Based Schools

owadays many schools used ICT tools for improving teaching and learning process but there are some challenges like infrastructure, funds etc.so that there is not proper implementation of ICTtools. For this proper implementation there is need of cloud computing. Cloud computing is technique which provides platforms, infrastructure and services .there is no extra cost forinfrastructure and services .school ca
A VMD Based Extreme Learning Machine Approach for Nonlinear System Identification

Now-a-days, most of the techniques applied to indentify the non-linear system are based on machine intelligence. In this work, a new Varitional Mode Decomposition based Extreme Learning Machine (VMD-ELM) is proposed to identify various non-linear systems. The VMD technique helps to denoise the input and output of the unknown non-linear systems before fed to the ELM network. The proposed VMD-ELM method helps to achieve more precise identification result with smaller computation complexity. The superior performance of the proposed VMD-ELM method is verified by comparing it with basic ELM and Emprical Mode Decomposition based ELM (EMD-ELM) for various non-linear systems in MATLAB/script environment. The efficacy of the proposed method is further validated through dSPACE DS1104 for a practical boiler system.
Upper Bounds on Complexity and Algorithms for Construction of Deterministic Decision Trees for Decision Tables. First Approach

In this chapter, for complexity functions having the properties $$\varLambda 1 $$, $$\varLambda 2$$, and $$\varLambda 3$$, upper bounds on the minimum complexity and algorithms for construction of deterministic decision trees for decision tables are considered. These bounds and algorithms are based on the use of so-called difference-bounded uncertainty measures for decision tables.
Künstliche neuronale Netze

No AccessKünstliche IntelligenzMar 2020Künstliche neuronale NetzeUwe Lämmel, Jürgen CleveUwe LämmelSearch for more papers by this author, Jürgen CleveSearch for more papers by this authorhttps://doi.org/10.3139/9783446463639.005SectionsAboutPDF ToolsAdd to FavoritesDownload CitationTrack CitationsCopy LTI LinkPDF key 'share (en)' returned an object instead of string.FacebookTwitterEmailLinkedIn previous chapternext chapter FiguresReferencesRelatedDetails 2020Pages: 189-201Print ISBN: 978-3-446-45914-4eISBN: 978-3-446-46363-9 Copyright & Permissions© 2020 Carl Hanser Verlag GmbH & Co. KGPDF downloadLoading ...
Web-based Parts Inventory Information System at Rizal Auto Workshop Palembang

This study aims to make it easier to find the availability of spare parts, after using the inventory information system can facilitate employees in collecting data on purchase transactions, can help in documenting indent data and consumer data information, data entry goods, transaction data, streamline time and provide solutions and accuracy in the report on incoming and outgoing goods. This system development method uses the Waterfall method, while it uses the system design method of Data Flow Diagrams (DFD), the test system used is a graphical user interface (GUI). The system is made based on web, using the PHP programming language. The results of this study can help leaders and employees to facilitate transaction activities and recap the report at the Rizal Auto Workshop Palembang.
Sistem Pendukung Keputusan Pemilihan Anggota Terbaik Pemadam Kebakaran Dengan Menggunakan Metode Analitycal Hierarchy Proses (AHP)

Fire is a threat to human safety, property and the environment. Increasingly dense population, the construction of office buildings, residential areas, industries that are increasingly developing causing vulnerability in the event of a fire that requires special handling. The fire brigade or BPBD (Regional Disaster Management Agency) is a government implementing element that is given responsibility in carrying out the tasks of handling fire and disaster problems which are included in the emergency department or Rescue (Rescuers) such as Ambulance and the National SAR Agency. AHP (Analitycal Hierarchy Process) is a method for solving an unstructured complex situation into several components in a hierarchical arrangement, by giving a subjective value of the relative importance of each variable, and determining which variable has the highest priority to influence the outcome of the situation . The decision making process is basically choosing the best alternative. Such as structuring the problem, determining alternatives, determining the likelihood value for the aleatori variable, setting the value, the preference requirements over time, and the specification of risk. The results of the study show that the use of AHP as a model of decision support systems for selecting the Best Members of the Fire Department can help the admin in determining the Best Member with a multi-criteria weighting process and selection more quickly, accurately and more effectively.
Comparative Analysis of Cultural Factors in TOPIK and JLPT Reading Text.

This paper is designed to make a comparison review of the Test of Proficiency in Korean(TOPIK) and the Japanese Language Proficiency Test(JLPT) to give an indication in the direction of language proficiency evaluation. From now on, in the overall comparison of the two tests, this paper started with the study of cultural factors. This is because cultural factors are the main mechanism that works throughout language education. In order to know how much cultural factors are included, this paper focuses on reading comprehension text. This is based on a deep correlation between reading comprehension and cultural understanding. TOPIK classifies cultural types by extracting intermediate readings from the 10th(2006) to 34th (2014). The JLPT, which does not provide the previous questions, extracted the readings from the nine textbooks for hands-on trial tests selected arbitrarily. As a result of the classification, we were able to confirm texts that included cultural factors in readings. TOPIK included cultural factors in approximately 25% (155) of 600 cases, and JLPT included approximately 93% (311) of 335 in total. In addition, TOPIK had the highest proportion of informational culture with 54% (83), while JLPT had the highest behavioral culture with 82% (255). The two linguistic abilities included a number of cultural factors in both ‘daily life’ and ‘society’. From these results, we were able to quantitatively measure the cultural factors included in the reading evaluation question.
AI for Nephrology Using Electronic Medical Records

Analysis of electronic medical record data, which is clinical real-world data, is expected to create new knowledge including new drug discovery targets. In LINC, projects such as stratification of diseases, detection of adverse events and discovery of unmet medical needs are in progress using electronic medical record data in collaboration with academia, life companies and IT companies. In this presentation, we will introduce an example of data analysis for renal disease using hospital-scale data conducted at Kyoto University Hospital, and discuss the possibility of using clinical real-world data for future drug discovery.
Fitness Club Customer Body Condition Detection System Based on Internet of Things

With the development of society and the improvement of people’s living standards, people pay more and more attention to the state of the body, choose to go to the gym to rely on special equipment to achieve the purpose of strengthening the body more and more people. In order to meet the needs of fitness clubs for customers’ comprehensive physical status assessment, this paper will design a system for fitness club customers’ physical status detection based on the Internet of things technology based on the Internet of things technology. This system will meet the needs of fitness club customers for body composition detection, body fat detection, obesity evaluation and other detection, and obtain continuous, long-term and real physical status of the customer index, with strong practicality. The design of the system is composed of data acquisition terminal, Web server and data base station. The data base station and the Web server communicate and transmit by wired connection. In the application terminal, the management staff of the health club can log in the management account in the Web interactive interface to view the test data of all customers, and can realize the analysis and statistics of a large number of customer data.
Edge Weight Differential Privacy Based Spectral Query Algorithm

The macro nature of social networks has always been a hot topic of scientific research, which is of great help in studying the characteristics of human social behavior. The spectrum is closely related to the nature of the network and determines certain information, including community division, loop, diameter, degree and so on. To ensure the security of data, the differential privacy security framework is used to propose three algorithms for privacy protection of edge weights in spectrum query. Firstly, the basic concepts of edge weight neighbor graph and edge weight difference privacy are given. For the single singular value query, the L1 global sensitivity of the function is proved, and an algorithm satisfying ε-differential privacy is designed by using Laplace mechanism. It can guarantee the privacy of edge weights when we query someone singular value. However, it cannot provide reasonable privacy protection for multiple singular value queries. So the L2 global sensitivity of the query for multiple singular values is further proved, and the Gaussian mechanism is used to design an algorithm that satisfies (ε, δ)-differential privacy. Finally, to combine with multi-singular values query strategy and spectral decomposition, a novel graph data publishing algorithm which can guarantee edge weight (ε, δ)-differential privacy is proposed. To verify the availability of these methods, experimental tests have been carried out in both model networks and actual networks, which shows that the algorithm can better guarantee the availability of data.
Successful Project Consulting

Successful project consulting is both an art and a science, combining project planning and project management, communicating the vision of the work while tending to details, and satisfying the needs of executive stakeholders as well as those impacted by the change. Successful project consulting requires that pitfalls are avoided. A consensus and categorized list of seven common pitfalls experienced by consultants identifies scope creep, failure to identify stakeholders, misaligned expectations, miscommunications, lack of ownership, and changing priorities. While pitfalls can happen at each phase of a consulting project, these pitfalls may be avoided through purposeful communication, cooperation, supportive stakeholders, alignment with business objectives, a well-defined and approved project scope, and well-established processes for implementation. Typically, the five phases of a consulting project include 1) relationship building in the initial client meeting, 2) developing a conceptual agreement, 3) creating a scope of work document, 4) implementing the project work, and 5) identifying the completed results and next steps. During the first phase, the consultant and the client must identify the key stakeholders and a plan to build an ongoing communications pathway with the stakeholders. Before implementing the project, the consultant must develop the conceptual agreement and create a scope of work document. The conceptual agreement allows for planning the objectives and measures of success. The scope of work clarifies expectations including the selection of project team members, ensuring that skillsets match the project scope and the organization continues to be developed with a culture that remembers how to avoid common pitfalls.
Identity Technologies: A Transaction Cost Approach

Identity is an input into economic exchange and contracting. The modern industrial economy has relies on cheap political identity to create trust and lower transaction costs. Market economies, however, have different identity needs than an administrative state. Economic efficiency in a digital economy requires high-quality economic identity to facilitate co-production of value on platforms, and to enable market competition through product-quality discrimination. Blockchain technologies and related advances are bringing innovation to economic identity technology. In this paper we explore state-produced identity and market-produced identity, the dynamics that exist in their demand and supply, how these categories are being shaped by technological change, the implications for privacy and secrecy, and the role of the state in market-produced identity.
Использование технологии веб-квест в процессе обучения кибербезопасности

The need for schoolchildren to develop safe behavior skills in cyberspace is justified in the article. One way is to use web-quest technology. The article contains a brief description of this technology and an example of its use in teaching the basics of cybersecurity.
Detection of Head Motion from Facial Feature Points Using Deep Learning for Tele-operation of Robot

We propose an interface for the tele-operation of a laparoscope-holder robot via head movement using facial feature point detection.Fourteen feature points on the operator's face are detected using a camera.The vertical and horizontal rotation angles and the distance between the face and the camera are estimated from the points using deep learning.The training data for deep learning are obtained using a dummy face.The root-mean-square error (RMSE) between the estimated and directly measured values is calculated for different numbers of nodes, layers, and epochs, and suitable numbers are determined from the RMSE values.The trained data are evaluated with four subjects.The effectiveness of the proposed method is demonstrated experimentally.