Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding Internal Semantics of Deep Learning Models for Electronic Music

Since deep learning showed outstanding performance in the computer vision ﬁeld, Music Information Retrieval (MIR) researchers also started to adopt these successful models in their research area. Unfortunately, a number of publications are still simply applying deep learning algorithms to any new problems or dataset without understanding their models. For sophisticated model design process, interpreting the architecture and the mechanism of hidden layers became more important, and it resulted in multiple publications to propose methods for investigating learnt information in hidden layers: visualization, auralization, and playlist generation. However, due to the fact that proposed methods are very time-consuming processes, hidden layers still remain a black-box. In this paper, I propose two ideas to investigate hidden layers more eﬃciently, which are ranking tags and deriving ﬁlter importances . With conventional approaches and proposed methods, I investigate latent semantics learnt in hidden layers of deep learning models, particularly Convolutional Neural Networks (CNNs). A prototype experiment was processed with Ballroom dataset and the main experiment was done with Beatport dataset which consists of 15k electronic music. The experimental result reports latent semantics of learnt kernels from pre-trained CNNs for the electronic music genre classiﬁcation, which was not mainly explored in a deep learning research.
Zur Struktur der l-Klassengruppe galoisscher Zahlkörper.

In der vorliegenden Arbeit verwenden wir durchweg die folgenden Bezeichnungen: P der Körper der rationalen Zahlen, / eine Primzahl, P der Körper der rational-/-adischen Zahlen, der Ring der ganzen rational-/-adischen Zahlen, eine primitive /-te Einheitswurzel, K ein galoisscher Zahlkörper mit den Eigenschaften ( 0 ) f e K , ( K : P ) ^ O m o d / , g = { , , . } seine Galoisgruppe, bzw. die einfachen bzw. i-adisch-irreduziblen Charaktere von g.
Analysis Monetize Strategy of EZ Marker Technology Product

In this era of Technology, Indonesian education needs advanced technology to support the Human Resource. In addition, According to the data is from Indonesia Cell Phone Association (APSI) Indonesia has around 55.4 milion smartphone users. This fact should be used as a turning point of knowledge transformation process. Moreover, this paper discusses a new product innovation for efficient and effective online method of correcting answer sheets using android computer and website. This application is EZ Marker. Ez Marker has gone through trial processes external validation acquired in SD Negeri 02 (2 nd Elementary School) of Sukapura, Bandung, Indonesia. However, it has not had any Monetize strategy. The purpose of this paper is to find out the users' willingness to buy the product using the EZ Marker analysis theory of Freemium Model. Furthermore, the critical review and descriptive methods are required. The result of this paper will provide references of the startups in Indonesia, since the quantity of ASEAN startups is quite high as well as the users of technology. With user development analysis, we hope to fulfill consumers' needs. In the end, EZ Marker will be more acceptable to Indonesian citizens especially in the education sector.
A Personalization Approach Based on Models Integration for a User Interface for Supervision in a Power Plant

— In the operation of a power plant, the operator has to deal with a number of variables displayed in several windows, presented in different formats such as tabular, one-line diagrams, process diagrams, etc. Under these conditions, the operator needs to locate data relevant to the current status of the plant and efficiently navigate a large number of screens within the user interface. This situation becomes critical for infrequent tasks within the plant such as the start-up, shut-down or for abnormal operational conditions. In order to deal with the above situations, we propose a personalization mechanism based on models for adapting contents in a user interfaces for the operation of power plants. The model takes advantage of the integration of specific sub-models from artificial intelligence, user modeling and human-computer interaction. A personalization approach is applied into an adaptive user interface prototype that is expected to improve the user-system interaction by reducing the time to complete the startup of a power plant. For this purpose, contextual information of the power plant, user interaction logs, user’s preferences and experience are considered. At this first stage, our prototype was evaluated in a simulated scenario with non power plant operators to investigate improvements of task performance for carrying out the procedure of the startup of a power plant process and to identify usability issues. Results from this initial evaluation show consistent time reductions and correct predictions of futures displayed variables for the adaptive user interface version despite the fact that participants in this evaluation had a lack of the domain knowledge. This results needs to be validated with further studies involving power plant operators, in order to compare the impact the domain knowledge plays in the time reductions.
Distribution of Tail Symbols in DST for Markov Sources

Lempel-Ziv’78 is one of the most popular data compression algorithm on words. Over the last decades we uncover its fascinating behavior and understand better many of its beautiful properties. Among others, in 1995 by settling the Ziv conjecture we proved that for memoryless source (i.e., when a sequence is generated by a source without memory) the number of LZ’78 phrases satisﬁes the Central Limit Theorem (CLT). Since then the quest commenced to extend it to Markov sources, however, despite several attempts this problem is still open. In this conference paper, we revisit the issue and focus on a much simpler, but not trivial problem that may lead to the resolution of the LZ’78 dilemma. We consider the associated Digital Search Tree (DST) version of the problem in which the DST is built over a ﬁxed number of Markov generated sequences. In such a model we shall count the number of of the so called ”tail symbol”, that is, the symbol that follows the last inserted symbol. Our goal here is to analyze this new quantity under Markovian assumption since it plays crucial role in the analysis of the original LZ’78 problem. We establish the mean, the variance, and the central limit theorem for the number of tail symbols. We accomplish it by applying techniques of analytic combinatorics on words also known as analytic pattern matching.
THE FORMATION AND PROPERTIES OF POLIOVIRUS- NEUTRALIZING ANTIBODY I. 19S AND 7S ANTIBODY FORMATION: DIFFERENCES IN KIm~TmS AND ANTIGEN DOSE REQUn~E~NT FOR I~'DUCUON*

The use of plaque-forming techniques in animal virology has markedly increased flae sensitivity and precision of measuring neutralizing antibody, and this together with other developments such as the ready availability of large quantities of relatively pure viral antigens and new techniques for characterizing antibody have prompted a reexamination of several aspects of the formation and properties of viral neutralizing antibody. In the work being reported a poliovirus-rabbit antibody system has been extensively studied with particular emphasis on experiments concerned with the length of the induction period, changes in properties of antibody produced at different times after an antigenic stimulus, differences in ! 9S and 7S antibody formation and on the ability of animals to display "immunological memory. " The combination of high sensitivity and high accuracy in measuring antibody to poliovirus (PV) makes an excellent tool permitting for example the study of the very early appearance of circulating antibody. In this work, to be reported in a series of papers, we have sought to (a) analyze 19S and 7S type antibody formation in terms of antigen dose requirement for induction and maintained synthesis, kinetics, duration of immunological memory, and sensitivity to whole body x-irradiation; (b) examine the progressive changes in physicochemical and biological properties of antibody with time after antigenic stimulus; and (c) to investigate the properties of antibody formed in vitro by in ~/vo primed cells. In addition the nature of "normal" antibody and its significance in relation to the immune response has been examined and will be reported. Early in this study it was found (1-3) that the induction period was of the order of several hours or less and that macroglobulin antibody was demonstrable 8 to 12 hours after antigen injection when sufficiently sensitive methods
A Simple Approach Towards Forgery Detection

Forgery detection and investigation has been a relevant topic of interest for human beings since ages. Important messages written and transported by kings in old ages were sealed with signatures and stamps to achieve this purpose. But with the advent of digital technology, forgery detection has become even more important since tools for forgery have become vast as well. In this paper a technique based on pixel clustering has been introduced for detection of modification, alteration or forgery done with a different ink color pen. Hyperspectral images are used for ink mismatch detection in a handwritten note. We propose ink classification based on pixel intensities values present in all the bands of hyperspectral images of the handwritten note. Our proposed technique is quite simple yet effective in detecting ink mismatch with relatively high accuracy.
Post-stroke depression: predictors and prophylaxis

The purpose of the study was to evaluate the effectiveness of prevention of post-stroke depression in patients with acute cerebrovascular accident It was shown that the incidence of PID in patients with ischemic stroke exceeds 30%. In assessing the role of various risk factors among the examined patients with PID, the prevalence of male patients (OR = 1.3 (1.1-1.5)), under the age of 55 (1.7 (1.3-1.9 )), with indications in the history of episodes of depression in the past (1.6 (1.4-1.8)), as well as alcohol abuse (1.2 (1.0-1.3)). In 31 (58.5%) there was a localization of focal ischemia in the frontal lobe of the dominant hemisphere. The use of both SIRS and an antidepressant with multimodal effect - vortioxetine was sufficiently effective in PID, but vortioxetin showing the best results - from 8,8  0,1 points to 6,2  0,1 points. The paper considers the expediency of the use of vorothoxetine in order to prevent PID in patients with
Noncommutative Theories and Gravity

We review the connection between noncommutative field theor ies and gravity. When the noncommutativity is induced by the Moyal product we can use the Seiberg-Witten map in order to deal with ordinary fields. We then show that the effect of the n oncommutativity is the same as a field dependent gravitational background. The gravitation al background is that of a gravitational plane wave and the coupling is charge dependent. Uncharged fi elds couple more strongly than the charged ones. Deviations from the usual dispersion relations are discussed and we show that they are also charge dependent.
The Design of Female Presentation in TV Beer Commercial

TV commercial is one of the most important promotion channels, it can not only stimulate the sales number of products but also insert the cultural meaning into consumer’s mind. However, inappropriate commercial design may lead to audience’s misconception of the product, and it could be harmful to the corporate’s image. Based on the main consumptions of the target audience of beer, mostly male consumers, female are always chosen to be the main character of beer commercial, repetitively appeared as objectified or discri-minated characters in the commercial. Results show that the shot distance and the bending and lifting angles used are correlated with the degree whether female are treated equally. If camera techniques were used properly, avoiding using the objectifying female semiotics, then the improper situation of sexual discrimination would be decreased.
DDDT_A_247259 3251..3262

1Department of Psychiatry and Psychotherapy, Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Munich, Germany; 2Institute for Clinical Chemistry and Pathobiochemistry, Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Munich, Germany; 3Institute for Stroke and Dementia Research (ISD), University of Munich, School of Medicine, Klinikum der Universität München, Munich, Germany
FACTORS AFFECTING THE CAPITAL STRUCTURE OF MICROFINANCE INSTITUTIONS: AN INSIGHT FROM ISLAMIC RURAL BANKS IN INDONESIA

Optimal capital structure is the comparison or balance of using capital in long-term by the company which can be shown from the comparison of long-term debt toward its own capital. Capital structure is extremely important in the company in which affecting funding decision and the company performance. Therefore, capital structure is interesting topic to further study. Then, this study is conducted by sampling 157 Islamic rural banks operating in Indonesia in the period 2010 – 2016 with quarterly data to examine the determinants of Islamic rural banks capital structure. A panel regression technique is applied using fixed effect model to estimate the relationship between growth, profitability, bank size, and asset structure as independent variables toward capital structure as dependent variable. The results show that asset structure is statistically significant affecting the capital structure accordance to the pecking order theory, trade theory, costs bankruptcy theory, and agency theory. However, growth is not significant affecting the bank capital structures. Then, the profitability and bank size have negative and significant effect to capital structure. These results can be used to the bank managers to understand the effect of each independent variable to capital structure in the process of decision-making.
Economic and Environmental Impact of Energy Saving in Healthcare Buildings

The purpose of this article is to estimate the economic and environmental impacts of energy consumption derived from healthcare buildings and proposes several energy-saving options in the sector. An experimental energy consumption study was development between 2005 and 2013 in 12 hospitals and 70 healthcare centres in Spain, built between 1980 and 2005 through audits carried out between 2005 and 2012, performed by the Extremadura Energy Agency. The study focused on electric energy, HVAC, DWH, lighting systems, renewable energies, maintenance strategy, thermal insulation, and optimal building size. Specifically, the following parameters were evaluated: energy savings, investment emission of CO2, NO2, and SO2 gases, and payback. The results revealed that through an appropriate energy management of healthcare buildings it is possible to save up to 8.60 kWh/m2 per year, for buildings of less than 5000 m2 (with no beds), which represents an expense of 1.55 €/m2. In healthcare buildings larger than 5000 m2 (with beds), it was possible to save up to 6.88 kWh/m2 per year, which represents an expense of 1.25 €/m2.
An intermediate point obstacle avoidance algorithm for serial robot

The trajectory planning and obstacle avoidance of serial robot is an important area of research and efficient optimization algorithms are needed. This article proposes an intermediate point obstacle avoidance algorithm to ensure smooth trajectory and efficient movement during the obstacle avoidance process. Using the intermediate point obstacle avoidance algorithm, the robotic arm can steer obstacle around with the minimum joint space variations and the shortest end motion trajectory. We also design a novel collision detection strategy and fitness evaluation function based on genetic algorithm to optimize the intermediate point parameters. In order to evaluate the performance of the intermediate point obstacle avoidance algorithm, we have conducted three typical experiments: single obstacle, multiple obstacles, and no obstacle. The experimental results demonstrate that the proposed method can not only effectively realize the obstacle avoidance, but also efficiently improve the movement performance of the robotic arm.
Energy-Aware Production Scheduling in Flow Shop and Job Shop Environments Using a Multi-Objective Genetic Algorithm

Abstract The energy-aware scheduling problem is a multi-objective optimization problem where the main goal is to achieve energy savings without affecting productivity in a manufacturing system. In this work, we present an approach for energy-aware flow shop scheduling problem and energy-aware job shop scheduling problem considering the process speed as the main energy-related decision variable. This approach allows one to set the appropriate process speed for every considered operation in the corresponding machine. When the speed is high, the processing time is short but the energy demand increases, and vice versa. Therefore, two objectives are worked together: a production objective, paired with an energy efficiency objective. A generic elitist multi-objective genetic algorithm was implemented to solve both problems. Results from a simple comparative design of experiments and a nonparametric test show that it is possible to smooth the energy demand profile and obtain reductions that average 19.8% in energy consumption. This helps to reduce peak loads and drops on applied energy sources demand, stabilizing the conversion units operational efficiency across the entire operational time with a minimum effect on the production maximum completion time (makespan).
Performance Isolation of Co-located Workload in a Container-based Vehicle Software Architecture

—As the development in the automotive sector is facing upcoming challenges, the demand for in-vehicle computing power capacity increases and the need for ﬂexible hardware and software structures arises, allowing dynamic managament of resources. In this new scenario, software components are to be added, removed, updated and migrated between computing units. To isolate the software components from each other and allow its orchestration, a container-based virtualization approach is being tested throughout this research. The analysis focuses on the question if this virtualization technology could be an option to ensure an interference-free operation. Four different sample applications from the automotive environment are tested for their susceptibility to resource contention. The research on the one hand shows that CPU and memory used by an application can be largely isolated with this technology, but on the other hand, it becomes apparent that support for I/O-heavy usage is currently not implemented sufﬁciently for container engines.
Optimizacija ruta vozila za potrebe istraživanja kvalitete mobilne mreže primjenom algoritama za rješavanje problema trgovačkog putnika

The aim of this Master's Thesis is to find a way how to minimize the total distance traveled by P3 Communications company, a company that conducts mobile network quality research. In order to give a general picture of the quality of a mobile network for some geographic area, it is necessary to perform measurements of different parameters at different places but also on the roads linking these places. It is often a great number of places that needs to be visited. To visit all places in the shortest amount of time, company P3 Communications uses more than one vehicle. For the purpose of minimizing the total traveled distance, a software solution has been developed using algorithms based on solving traveling salesman problem. The solution uses a total number of three algorithms, two which are used for solving traveling salesman problem and one algorithm used for clustering. Algorithm used for clustering is called K-means algorithm, which is one of the partitions algorithms. The other two algorithms are nearest neighbour algorithm, a heuristics algorithm, and 2-Opt algorithm, which improves the initial solution obtained by the nearest neighbour algorithm. The solutions provided by the software are shown on a graphical user interface on which different routes are drawn, for each vehicle separately.
Inducing Its Receptor Aggregation Binding May Initiate Mast Cell Response by Enforcing the Artificial: Monomeric IgE Cutting Edge: Death of a Dogma or

Several recent reports have suggested that binding monomeric IgE (mIgE) to its type 1 receptor, Fc (cid:1) RI, on mast cells induces important responses. These observations con-tradict the notion that it is the aggregation of this receptor that is essential for initiating mast cell response. In the present study, we suggest that the most probable causes for the reported observations are the experimental pro-tocol used combined with the high expression levels of the Fc (cid:1) RI by mast cells. Specifically, we suggest using the published data and physicochemical calculations that the exceptionally high number of cell surface Fc (cid:1) RI-bound monoclonal IgE yields, in the two-dimen-sions of the cells’ membranes, a situation where even a low affinity of these mIgE for epitopes on their own structure or on another cell surface component may lead to their aggregation. Hence, we hypothesize that the reported response to mIgE binding is a result of such an Fc (cid:1) RI-IgE induced aggregation. The Journal of Immunology, 2005, 174: 4461– 4464. only upon Fc (cid:1) RI clustering is the cascade coupling it to mast cells’ response triggered (1, 2). IgE generally to just endow the Fc (cid:1) RI with specific Ag recognition capacity or affect its cell surface expression levels. However, of (mIgE) 2 the Fc (cid:1) RI its stimulus-response The conditions.
Determinants of land-use change: A case study from the lower Mekong delta of southern Vietnam

The paper examines forestland conversion in the period from 2001 to 2005, and its socioeconomic determinants affecting changes in the Kien Luong district of southern Vietnam using Geographic Information Systems (GIS), Remote Sensing (RS), and multiple regression techniques. The land use/ land cover (LULC) classes from 2001 and 2005 were classified from Landsat ETM Plus 2001 and digitized from the 2005 district land-use map. Socioeconomic data corresponding to the derived LULC classes were aggregated for the multiple regression analysis of determinants of the forestland conversion. The findings indicated that the loss of forestlands was driven by the quick growth of the rural economy, and the two largest contributors were the prompt expansion of agricultural and aquaculture. Such a land-use change hampered agricultural development and ecological services. Addressing land-use suitability for production systems and the socio-environmental costs of the changes is necessary for informing more effective policies of utilization and management of land resources.
THE PRIMITIVE IN-VITRO PHARMACOLOGICAL STUDIES OF THE EXTRACTS FROM WITHANIA SOMNIFERA

From ancient times, Medicinal plants were used for the treatment of various deadly diseases. Especially Asian countries like India, china etc., were used medicinal plants as a potential curing agent for various diseases and used in their different medicinal system named ayurvedic, siddha etc.,. Withania somnifera is an indigenous herb belonging to family Solanacae, commercially known as Ashwagandha. It is extensively used in most of the Indian herbal pharmaceuticals and nutraceuticals, It was spread all over the India and in some other Asian countries. It has phytochemicals named alkaloid, steroidal lactones, flavonoids, saponins and tannins; it has various pharmacological activities whereas in the present study we clearly investigate their antibacterial, antifungal and antioxidant activities in their leaves and root extracts. Among the various solvent used our research reveals that the Aqueous, chloroform and methanol extracts shows maximum inhibitory effect against the tested bacteria and fungi. In addition to that we proved that these extracts also have antioxidant activity. Furthermore we concluded that the aqueous leaf extract and methanolic root extract has virulent activities when compared to other.