Reviewerly/exHarmony huggingface dataset:
Bifurcations and chaos in nonlinear Lindblad equations

The Lindblad equation describes the dissipative time evolution of a densitymatrix that characterizes an open quantum system in contact with its environment.The widespread ensemble interpretation of a density matrix requires itstime evolution to be linear. However, when the dynamics of the density matrixis of a quantum system results not only from the interaction with an externalenvironment, but also with other quantum systems of the same type, the ensembleinterpretation is inappropriate and nonlinear dynamics arise naturally. Wetherefore study the dynamical behavior of nonlinear Lindblad equations usingthe example of a two-level system. By using techniques developed for classicaldynamical systems we show that various types of bifurcations and evenchaotic dynamics can occur. As specific examples that display the various typesof dynamical behavior, we suggest explicit models based on systems of interactingspins at finite temperature and exposed to amagnetic field that can change independence of the magnetization. Due to the interaction between spins, whichis treated at mean-field level, the Hamiltonian as well as the transition rates ofthe Lindblad equation become dependent on the density matrix.
CPIA Smart: distanti, ma connessi. Uno studio esplorativo sull'uso dello smartphone tra i migranti frequentanti i corsi del CPIA.

The presence in Italy of an increasing number of students of foreign origin, specifically so-called connected immigrants with strong skills in using electronic devices, requires a rethink of the learning/teaching practices applied in the country’s Provincial Centres for Adult Education (CPIA), including the educational use of digital technologies. This paper presents the results of an exploratory study on the use of smartphones by a sample of 140 immigrants attending Italian language courses at the CPIA in Udine.The preliminary data show that these learners use smartphones extensively not only to keep in touch with their communities of origin, but also to navigate and interact within their new country and learn the target language. Given widespread smartphone use among immigrants, it is believed that the the potential of these tools could be utilized to amplify learning opportunities and foster personalization, integration and in-depth study of linguistic contents in online mode.
THE QUALITY OF ASYNCHRONOUS ONLINE LEARNING ON EDMODO-BASED ENGINE ELECTRICITY SYSTEM COURSE DURING COVID-19 PANDEMIC

The decision of the Minister of Education and Culture concerning the prevention of co-19 which suddenly made at home during the pandemic forced various parties to follow the flow so that learning could take place, one of which was online learning. Measurement of the quality of asynchronous online learning is essential to do, to get a better picture and become a guideline for making improvements. Measurement includes aspects of expert assessment and student satisfaction using survey methods. The type of data collected is the data from the expert assessment and the data from the student satisfaction survey on Edmodo. Data sources included two experts and 58 students as respondents. Data collected by distributing questionnaires. The instrument used in the form of Edmodo asynchronous online learning manuals on engine electricity courses, expert assessment questionnaires and student satisfaction survey questionnaires on Edmodo. Data in the form of numbers were analyzed using descriptive statistical analysis. The conclusion is the quality of asynchronous online learning of Edmodo-based electrical engine subjects during the co-19 pandemic at the State University of Malang in terms of expert perspectives in the Very category and viewed from the satisfaction of students in the High category.
Kapasitör Dizgisine Yönelik Görü Tabanlı Bir Algoritma [No English title provided]

An image processing algorithm was developed to assembly capacitor onto the circuit board. Electronic components which are assembled on the surface are used on the printing circuit board. However, due to need for high capacitance value, through-hole mounted capacitors require to be used. Pressing is performed on the legs to increase the solder surface area of the capacitor. Offsets caused by pressing or production of the capacitor block the assembly process. There-fore, this process is achieved manually. In order to increase the production quality and production rate, it is suggested that the capacitor should be placed on the printed circuit board using a vision algorithm based on the difference between the capacitor legs with the center point of the gripper. Edge detection algorithm was developed to obtain offset value to send information to the robot. In this way, the set point has been defined on the robot workspace. As a result of the study, it is shown that capacitors can be placed on the printed circuit board with the desired sensitivity by measuring the offset values of them. As a result of the error analysis, it is observed that offset values were not within the tolerance range if the developed algorithm usage is not considered.
Efficient Parallelization of a Genetic Algorithm Solution on the Traveling Salesman Problem with Multi-core and Many-core Systems

Efficient parallelization of genetic algorithms (GAs) on state-of-the-art multi-threading or many-threading platforms is a challenge due to the difficulty of scheduling hardware resources regarding the concurrency of threads. In this paper, for resolving the problem, a novel method is proposed, which parallelizes the GA by designing three concurrent kernels, each of which are running some dependent effective operators of GA. The proposed method can be straightforwardly adapted to run on many-core and multi-core processors by using Compute Unified Device Architecture (CUDA) and Threading Building Blocks (TBB) platforms. To efficiently use the valuable resources of such computing cores in concurrent execution of the GA, threads that run any of the triple kernels are synchronized by a considerably fast switching technique. The offered method was used for parallelizing a GA-based solution of Traveling Salesman Problem (TSP) over CUDA and TBB platforms with identical settings. The results confirm the superiority of the proposed method to state-of-the-art methods in effective parallelization of GAs on Graphics Processing Units (GPUs) as well as on multi-core Central Processing Units (CPUs). Also, for GA problems with a modest initial population, though the switching time among GPU kernels is negligible, the TBB-based parallel GA exploits the resources more efficiently.
A survey on sentiment analysis in tourism

Tourism-related websites have turned into an incredible data source that impacts the tourism industry from many points of view. Tourists express their opinions regarding products and services online daily. The interest in understanding and analyzing customer opinions has increased significantly over the past few years as it is vital for the decision making of both customers and companies. Sentiment analysis is the practice of applying natural language processing, statistics and machine learning methods to extract and identify the common opinion behind the text in a review, blog discussion, news, comments or any other document. Sentiment analysis has great potential to directly understand tourists’ opinions. This paper tackles a comprehensive overview of the latest update in this field. The main target of this survey is to give a nearly full image of sentiment analysis approaches, techniques, and challenges in analyzing the correct meaning of sentiments and detecting the suitable sentiment polarity in the field of tourism.
Panduan Kesehatan Bagi Ibu Hamil Dan Anak Berbasis Android Mobile

Background : Health as a basic need for everyone is a determining factor in the quality of Human Resources. But sometimes health is often forgotten due to various factors, and most often it is because of one's own busy schedule. During this time mothers get information about pregnancy and children from Integrated Healthcare Center or at the Public health center and from midwives or doctors in their immediate surroundings. The weakness of the health service facility is the time of its implementation which cannot be done at any time. While the obstacle to get information from midwives, doctors and health centers in their immediate surroundings is the busyness of the person and the distance that is sometimes difficult to get the information. Purpose : To fulfill the health information system for pregnant women and children faster, there are now many mobile applications that are able to meet the health information needs of pregnant women and children Method : Observation method and literature review. Results : The results of this study are the creation of an application, this Android-based mother and child application that is useful for obtaining information for pregnant women and children based on the parameters needed for each menu Conclusion : The conclusion of this research is an Android-based information system created to help monitor health for pregnant women and children in the womb. Keywords: Android, Experts , Health, Pregnancy
Sistem Pakar dalam Mendeteksi Kerusakan Laptop dengan Metode Case Based Reasoning

Laptop is an electronic device that is very widely used today, so the damage to this tool is the most frequently found case. Very many laptop users do not understand the type and level of damage. So researchers conducted this research in making it easier for users to detect laptop damage earlier. This study uses an Expert System that functions as a substitute for experts as a media consultation. The method used is Case Based Reasoning of laptop damage data on Lutfi Computer. The results of this study can detect damage more quickly and precisely in helping users to find the right solution to overcome the damage. So this research is very helpful for laptop users in general in overcoming early on accurately, so users can determine an accurate solution in dealing with damage to their laptops.
The General Higher-Order Neural Network Model and Its Application to the Archive Retrieval in Modern Guangdong Customs Archives

Because of the unique attributes of archive information, it is challenging to manage and effectively retrieve archive information in the archive information management practice. This paper designs and develops the first general higher-order Neural Network Model for archives. Based on the analysis of the correlation, the relevance of the weight model, the study of technical methods about the core weight, the direction weight retrieval, and the statistical ranking of the results, this paper designs a corresponding archive information analysis system. Finally, this paper adopts the B/S development model by applying the relevance ranking weight algorithm into the comprehensive archive retrieval activities, which not only enhances the intelligence and efficiency of the archive retrieval, but also can act as a standard example to demonstrate informatization construction for archive management. This paper compares this algorithm with two other existing retrieval algorithms and verifies the practicability of the relevance algorithm by evaluating the algorithm and the default retrieval algorithm using the NDCG evaluation method.
The Crisis of Collegiality in Scientific Organization, and the Scientific Policy

The article substantiates that science, thanks to the latest media in the dissemination of scientific communication (especially computer word processing, big data accumulation, mega-science installations, the latest international networking platforms and collaborations), has gone beyond all institutional, organizational, regional, national and partly disciplinary borders. Science as a supranational communication system has reached a complexity that is incompatible with the standards for evaluating scientific work and scientific achievements, which are traditionally carried out in the form of scientific committees, individual examinations and other collegial forms of scientific communication. The collegiality of making the most important decisions regarding the examination of the scientific product itself, the thematic agenda, professional competencies and the resulting distribution of remuneration, reputation, ranks, degrees, grants has exhausted its capabilities to a certain extent. As a result, science turns out to be opaque both for the regulator, who is trying to exercise control over scientific institutions, and for science itself, which in the form of scientific self-government and philosophical reflection of science carries out the function of self-observation and self-description. A working hypothesis is proposed, which states that in response to this crisis of collegiality, reflection and control, new media of communicative success and new organizational forms of scientific communication crystallize in science, which can restore the ability of a scientific system to process its internal and external complexity. These media are represented by a new, social-networked form of scientific expertise and partly scientific work, which will be able to compensate for the lack of self-reflection, both at the organizational level of research institutes and at the level of global control over science as a whole.
LdsConv: Learned Depthwise Separable Convolutions by Group Pruning

Standard convolutional filters usually capture unnecessary overlap of features resulting in a waste of computational cost. In this paper, we aim to solve this problem by proposing a novel Learned Depthwise Separable Convolution (LdsConv) operation that is smart but has a strong capacity for learning. It integrates the pruning technique into the design of convolutional filters, formulated as a generic convolutional unit that can be used as a direct replacement of convolutions without any adjustments of the architecture. To show the effectiveness of the proposed method, experiments are carried out using the state-of-the-art convolutional neural networks (CNNs), including ResNet, DenseNet, SE-ResNet and MobileNet, respectively. The results show that by simply replacing the original convolution with LdsConv in these CNNs, it can achieve a significantly improved accuracy while reducing computational cost. For the case of ResNet50, the FLOPs can be reduced by 40.9%, meanwhile the accuracy on the associated ImageNet increases.
Correlation Between Bone Density and Fractal Dimension: A Pilot Study

Fractal analysis is a mathematical method used to describe the internal architecture of complex structures, such as the bone tissue. The aim of this study was to determine whether fractal dimension (FD) is able to distinguish between different bone densities (BD), assessed histomorphometrically, and whether there is a linear dependence between the FD and BD in order to support the use of FD as a supplementary non-invasive method for BD measurement. Microscopic photographs of bone specimens stained with acid fuchsin and toluidine blue obtained during block biopsies from nine segments of bovine ribs were used. A total of 42 regions of interest (ROI) were cut off from the original photo, converted into a bitmap and binarized. The evaluation of FD was carried out using the box counting method. Comparison of FD values in the four different densities bone sites (D1-D4) was made by means of Kruskal-Wallis test followed by Dunn's multiple comparison test. The linear dependence between the two variables (FD and BD) was investigated calculating the Pearson's r test correlation coefficient, which was considered significant when P &lt; .05. The more the bone was compact, the higher were FD values. A strong positive correlation between BD evaluated by histomorphometry and FD (R : 0:9651), p-value &lt; .00001 was found. The increase in the values of the FD strongly correlated with the increase of the percentage of the bone trabeculae observed in the histological slides. This pilot study demonstrates that FD might be able to distinguish different densities in bone sites and that there is a linear correlation between BD and FD on histological samples. Future studies will be addressed at evaluating whether this data can be confirmed on a larger samples size and on radiographic images. This will be useful for the early and non-invasive detection of structural changes in the trabecular bone pattern during healing, inflammatory processes and pathologies associated to bone breakdown.
As We Could Have Thought: Deploying Historical Narratives of the Memex in Support of Innovation

The memex has been hailed as an inspiration by many innovators since it was first described in 1945. Allowing users to combine and annotate information from diverse sources stored in microfilm and to create links between related items, the memex is said to predict today's information devices. In this way, the memex is presented as a cultural imperative, yet few of the innovators who invoke the memex account for the introspective thinking that the memex was supposed to provide. Even those who did respect the memex's disruptive potential were unable to divert the direction of innovation because their ideal users conflicted with existing paradigms. The repeated misunderstanding of the memex-which this article observes in early information science, commercial versions of hypertext, and the Web-is an important warning about the use of simplistic historical arguments to undergird innovation.
Design and Implementation of a Smart &amp; Portable Wireless FM Transmitter for Wide Range Communication

The evolution of smart technologies makes end users to choose portable, cost-effective and reliable devices for their daily life usage. The optimum service and superior quality of any such devices are always remain the centers of attraction for any customer. The advent of new technologies gives the smart FM transmitters also a unique shape. Depending on the dynamic requirements, the customer needs always changes with time. Keeping this fundamental issue in mind, in this work, we have designed and implemented a smart FM transmitter model keeping the key features in mind. Its small size, long battery life, and easy portability make it very useful to be used in day to day life. It has the potential of real-time noise cancellation features to get the optimum sound quality at the receiver end. The Digital Frequency Modulation Scheme has been used here to boost the signal strength for long-range communication. The used components are very cost-effective and reliable for prolonged use. The test case has given high-quality sound reception at the receiving end from the source end using our model. This smart transmitter section model has been found to be very effective for the future digital communication system. The specific station catching ability and low tone scanning capability make it superior to other existing similar kinds of devices. It can be used at home, or institutional premises, or any other distant trials for effective information exchange.
SEGMENTASI CITRA THORAX PARU-PARU MANUSIA DARI SINAR-X MENGGUNAKAN METODE KONTUR AKTIF

Research on medical image objects in the form of lung images of thoracic X-Rayis increasingly being developed because the information contained in medical images is used to analyze and determine the shape of the lungs. The process of normalization and image improvement is needed and continued with the segmentation process using the right method. The active snake contour method is used because it is resistant to the noise around the object. The research has been usedthe Matlab software GUI program version R2015a. The image through the initial preprocessing stage is converted into a grayscale image. The segmentation process used after the initialization process in the form of a small circle curve placed of the object to be segmented and the determination position of the active contour or detemination of the active parameters of the contour. Determination of the value active contour parameters greatly influences the results of segmentation and influences the direction of active contour movement. If the active coordinate position of the contour is outside the area to be segmented it will cause active contours to move away from the object. Validation the level of accuracy of segmentation results is done by comparing the results of the snake active contour segmentation to the results of manual segmentationused MSE method
Image Encryption Based on High-Dimensional Manifold Computing and Block Dividing Algorithm

The image encryption schemes developing more sensitive and more chaotic maps are used as a key sequence generator, such as cascade chaotic maps and high-dimension maps. High-dimension chaotic maps can generate sequences with little correlation after hundred times of iteration. In fact, the sequence is just a flow of the manifold of the chaotic system. A fast way to select sensitive flows of the dynamic systems is introduced in the paper. Combining with the divided blocks diffusion algorithm, the novel scheme yields the cipher image more randomly. Experimental results show that the sensitive flows of the high-dimension system can generate a series with better ergodicity and less correlation compared with the common flows of the same system. The encryption efficiency is enhanced by choosing the sensitive flows of the high-dimension system. The analysis proved that the novel image encryption scheme can resist all common kinds of attacks.
ADVANCEMENT OF ATTACK AND DEFENSE TECHNIQUES IN ADVERSARIAL MACHINELEARNING

Machine Learning, these days, is helping make decisions about real-world problems and its use in almost everyfield signifies that it is quite effective. But, it is prone to some serious threats which are known as adversarialexamples and, using these adversarial examples to attack machine learning is called adversarial machinelearning. Adversaries have started to develop various methods to infiltrate machine learning models and modifythem such that the models start working for their benefit or start behaving absurdly. Adversarial machinelearning poses a grave threat to all the sectors in which machine learning is being used. Here, the vulnerabilitiesin machine learning models, major types of attacks that avail these vulnerabilities to weaken the models usingadversarial examples and,defenses against these adversarial attacks are discussed.