Reviewerly/exHarmony huggingface dataset:
Satellite Color Image Enhancement by using Histogram Equalization Techniques

Image enhancement is an important pre processing step in any image analysis process .It helps to catalyze the further image analysis like adjusting the image intensities to enhance contrast levels of image. Here in this paper an approach for satellite color image enhancement on HSV color space is introduced .Satellite images are recorded in digital forms and then processed by the computers to extract information. Here local contrast management is given main focus because noise exist on local regions are found over amplified when enhancement is done through global enhancement technique like histogram equalization . The color arrangement and computations are done in HSV color space .The V channel has been extracted for the enhancement process as this channel represents the intensities and there by represents the luminance of an image .At first the image is normalized to stabilize the pixel distribution .The normalized image channel is analyzed with histogram equalization techniques for local contrast enhancement .The result obtained from the experiments prove the superiority of the proposed approach .
Redefining the Role of the Sound Engineer: Applying the Theories of Cage, Schafer, and Lomax Towards Establishing a Critical Cultural Approach to Sound Engineering

Within mainstream media, more specifically music, sound engineers and producers seek recording environments that are acoustically optimal for recording musical artists and sound.From the minimizing of noise to the isolation of instruments and the multitrack recording process itself, the focus of the session often favors technical and performance precision over concern for more qualitative attributes such as emotion and artist-production environment interaction.As a result, recordings tend to become clinical-a specific studio is chosen for its sound quality (reverberation, delay, and frequency response, to name a few) that changes only when the instrument within the room changes.Ironically, it is often a practice by producers and sound engineers alike to add artificial sonic elements post-tracking as a method to alter the production rather than capitalizing on the natural acoustical and sonic environments.Though resulting productions may fit the commercial needs of the entertainment industry and consumers, it is argued that limiting the role of the sound engineer to such a clinical studio approach eliminates the potential for capturing critical cultural information that aesthetically rich location-based recordings can provide.Such attributes have the potential to transform the musical performance, the production itself, and the consumer listening experience.It is suggested that additional captured acoustic artifacts act as environmental cues and are necessary to documenting and developing an understanding of the culture of musicians and the production process.Through such a critical cultural approach, this paper discusses how selected works, contributions, and perspectives of three influential sound scholars-John Cage, R. Murray Schafer, and Alan Lomax-can be integrated into sound en-gineering pedagogy and more broadly, to the future of sound engineering and the preservation of culturally relevant sonic elements.As a result, a model is presented, followed by a series of examples and recommendations.The role of the sound engineer is redefined to reflect the newly proposed critical cultural approach to sound engineering.By adopting this definition and approach, the performance, recording process, and consumption can be transformed into unique experiences comprised of important cultural information and rich sonic aesthetics as a result of the interaction between person, environment, and sound.
An Advanced Data Management Scheme for Secure De-duplication

Data De-duplication is one of the effective ways now a days employed in the cloud computing.Energy consumption ratio of IT companies is increasing day by day and reason for it is storing redundant copy of data.Data De-duplication is a cutting edge technology that is used to remove redundant copies of data and store only unique copy of data.It reduces network bandwidth and storage space as well.There are many Data De-duplication methods used however in proposed work main focus is on block level Data De-duplication along with security.In Block level Data De-duplication redundancy would be checked based on blocks of data.
Prediksi Jumlah Pendapatan Beasiswa PPA dan BBP Menggunakan Jaringan Syaraf Tiruan Backpropagation

STIKOM Tunas Bangsa is a world education institution located in the area of North Sumatra, where every semester for students who get PPA and BBP scholarships, from the number of students who come from it, not all students get scholarships, and at least get scholarships provided. Each student has the same criteria as the number of scholarships, with a minimum number of scholarship recipients. Therefore, to determine the number of participants who receive PPA scholarships in each country STIKOM Tunas Bangsa. In predicting the number of Kouta scholarship recipients using Backpropagation artificial nerves using data from 2015 to 2019 the data used from previous data has been received by the STIKOM Tunas Bangsa campus. With the existence of this artificial neural network to predict 2020 the number of PPA and BBP scholarship recipients at STIKOM Tunas Bangsa.
Entanglement Generation by Conversion of Position Correlation into Polarization Entanglement

Entangled photon pair sources are of great interest for quantum communication and computation protocols [1]. To date, the brightest sources are based on SPDC in nonlinear materials, with periodically poled crystals leading the field. Their nonnalized detected pair rate has reached a regime of millions of pairs per second per mW of input power in the visible spectral region [2], At these rates, quantum communication protocols are limited not anymore by the source brightness, but by the performance of single-photon detectors. Therefore, the focus of improving entangled photon pair sources lies on their practicality with respect to their size, robustness and ease of use.
Roadmap on Blockchain Transformation for Organizations – Evaluation through Teaching

Even though blockchain technology is currently a widely discussed topic, it is hard to get a straightforward overview or understanding of this topic. For many organizations blockchain causes excitement about the opportunities for innovation but raises also doubt and fear of losing their competitiveness. Most managers have heard of blockchain technology before and feel the pressure to go with the market and implement the technology. However, most organizations do not know how to develop their company towards blockchain. The lack of knowledge includes how to build up knowledge, launch a suitable project, finding a use case that matches the organization, aligning it with their strategy, which kind of blockchain to focus on and how to start a business transformation. As a part of a research project about blockchain teaching and business transformation, a roadmap was developed that aims to support organizations in their transformation towards blockchain technology and in understanding the potentials of this new technology. This artifact was then evaluated through a proof-ofconcept by gathering data on relevance and practical applicability of the roadmap. This was done by using the roadmap in a university class environment and an industry questionnaire. With the evaluation of the artifact in a class environment, a current state-of-the-art topic could be taught to students and, additionally, the learning process of the students enabled research contributions to the project results.
Survey and comparison of different classification techniques for select appropriate classifier of image

In human visual system, visual object classification is easy and effortless but in computer vision systems it is extremely hard Because of the various images of different objects within a specific class may have together with the various viewing conditions had led to have a serious problem.If some images have noisy contents or it contains blurry data, thus it is very hard to classify these types of images.Images processing introduces several techniques which be able to classify the data, but if image is blurry or noisy so they can not able to give the acceptable results.In this survey discuss the main classification methods consider, Supervised learning and unsupervised learning.The major motivation of this survey is to gives a brief comparison among different images classification techniques and methods.Finally, it is determined method that more accurately if an image contains blurry or noisy data.
Feasibility Study of Web-Based Internship’s Information System Based on ISO 1926 Standard

At this globalization era, unlimited accessible information across the overseas, increasing competition for getting a job. This condition affected a university student to enhance their skills to keep competitive. One method to improve is conducting an internship program (PI) at industrial companies. Thus, to implement and monitor the program, Informatics and Computer Engineering for Education Department (PTIK) at Universitas Sebelas Maret was used a web-based information system. This research aims to conduct and analyze a feasibility study of PI information system built for PTIK based on ISO 9126 standard. The research has two phases, the first is developing the system using waterfall method, and the second is feasibility study based on five characteristics of ISO 9126 standard which is:  (1) functionality, (2) reliability, (3) usability, (4) maintainability, and (5) portability. Eighteen PI information system examiners are involved. Those reviewers divided into three categories:  system’s expert, substance’s expert, and the end user of the PI information system. Examining result shows that the average number of all categories is 85.5%. It means that PI information system considered as very-feasible to implement and use.
ANDROID BASED AUGMENTED REALITY FOR DIGITAL VISUAL NAVIGATION

Augmented Reality (AR) used in online business not merely to give new perspective of customer experience to product. AR is also used in operational such as in logistic to deliver product to the customer. The online map service such as Google Map, sometime fails to bring real visualization to user, especially when they are in unfamiliar places.&#x0D; AR may provide visualization of certain location’s coordinate. This digital visual navigation will help the user to choose which direction they should go, especially when Google Maps do not give accurate information related to the user’s surrounding.&#x0D; This papper provide solution to create Android application that can generate Augmented Reality navigation while user is using Google Map to travel. This papper is aimed to support the navigation for logistic management system especially for online business companies.&#x0D; In spite of the result of this reasearch, some findings and issues need to be discussed in the future. There was delay to generate the AR objects especially when user moves the device around fast. A simple 2D AR object is suggested for future work in order to decrease the delay.
Deep Tree Net-Vector of Locally Aggregated Descriptor (VLAD) Model

In this work, we combined both a tree and a NetVLAD (vector of locally aggregated descriptors) in order to design new deep model. In developing this model, we studied the impact of tree hyperparameters and found that branch factors had major effects on the parameter utilization as major indicator and the accuracy of the model. The new architecture presented herein exposes a novel hyperparameter called the tree branch factor, which grants additional control over model complexity and on the maps codependency. Deep Tree Net-Vector provide the flexibility to combine two very famous techniques, namely the tree-based technique and VLAD. The former reduces the number of parameters, whereas the latter provides better feature representation inside the model. This work aimed to demonstrate the integration of the strong image descriptor, VLAD, with the tree module, to gain additional control on model size, rather than obtaining better results than state-of-the-art models, and to enhance image representation inside model layers, which could then be invested towards several tasks such as image classification and retrieval. We performed experiments on the Canadian Institute for Advanced Research-10 dataset and were able to show that the proposed models were superior-in terms of information density and accuracy-to many well-known networks.
The Urgency of Indonesian Literary Text Book in Indonesian Learning at SMP/MTs

There are two purposes of this study, firstly to find out the type of textbook used in indonesian language learning at smp/mts and secondly to find out the design of literary learning in indonesian learning at smp/mts.This research method uses qualitative descriptive methods.Data obtained from interviews and observations.Data processing was done by analyzing the data collected, namely the learning literature observation sheet.The results of this study were that most teachers need a special textbook containing literary material as a complement to the textbooks (compulsory) published by the Ministry of Education and Culture.Literary learning in SMP/MTs is still constrained by the lack of literary material in Indonesian language textbooks.
JENIS FITOPLANKTON DI SUNGAI PANJARATAN SEBAGAI BAHAN AJAR KONSEP PROTISTA SMA KELAS X

Learning is currently using the scientific approach, through direct interaction with lea rning resources. The educator or teacher at the school are expected to use appropriate learning resources. Local potentials that are spread around in the form of learning resources should be of concern to organized, so empowering positive for all students' learning. Not much research to develop teaching materials based on local potential. The amount of biological material that can not be observed directly, such as materials about protists, monera, one-celled animals, make the learners have difficulty to understanding. Research types of phytoplankton can be used as a learning resource to overcome these problems. This research aims to (1) Produce teaching materials of research types of phytoplankton in Panjaratan River (2) Examine the feasibility of teaching materials that are based on research on the type Phytoplankton Panjaratan River. The results showed (1) teaching materials produced are teaching materials enrichment entitled Type Phytoplankton in the River Panjaratan, consisting of 3 BAB, teaching materials prepared in accordance competencies and according to the terms of teaching materials quality that meets aspects of the display, the aspect of the presentation of the material and aspects of language , (2) Eligibility teaching materials in the river Panjaratan Phytoplankton type of expert validation result is quite valid with an average score of 80,43%, readability test students strongly agree with the assessment statement as much as 53,1%, 45,03% agree and 1,87% disagree . Assessment of teachers partners on quite valid with an average score of 76,12%. Results responses of teachers and students each showed a good response. Learning outcomes after using teaching materials in the river Phytoplankton type Panjaratan increase seen from the posttest and normality test Gain (n-gain) with an average value of 83,7 and a gain of 0,81 postest with high improvement category.
Aplikasi Ujian Online Berbasis Intranet Pada Mata Pelajaran Simulasi Digital Di SMK Yadika 4 Ciledug

Yadika 4 Vocational School is a vocational secondary education institution that was established in 1996 and is located on the highway Raden Saleh No. 11 Karang Tengah. Creative school that provides three majors namely Office Administration (AP), Accounting (AK) and Computer Network Engineering (TKJ). In the learning process Yadika 4 Vocational students get subject matter materials according to their competency skills. Another problem that is when the exam is still seen is cheating, such as cheating, this causes the class to become noisy. The thing that makes the writer take this online exam case study is to prepare computer-based examinations held by the education office. Other problems, namely the values that come out of each subject will be entered manually from each class by the subject teacher concerned, sometimes the teacher feels tired to count and match the answers and the scores of each subject tested. Errors when matching cause repetition of entering data into Microsoft Excel tools that are used as learning evaluation reports to the homeroom of each class. The solution to overcome this problem is by making an online test application with questions and answers on online exam applications to be random in order to minimize fraud. In the making, it is expected that online examinations in schools can provide students with an overview of computer-based exams that have been held by the education office with advantages in terms of time correction, resources from teachers (teachers or employees). The results of this study produced an online test application that has been tested, so that users in this application can be helped as the results of observations made by the author in conducting this research.&#x0D; i.
Defense against Adversarial Vision Perturbations via Subspace Diagnosis

Deep neural networks are powerful learning architectures in the field of industrial applications, especially for image analysis. However, recent studies have found that deep learning paradigms are vulnerable to input samples crafted with adversarial perturbations. Adversarial samples are quasi-imperceptible to humans but can easily fool those deep models in the deploying phases, which may raise high risks in safety and security critical conditions. In view of that, this work proposes a novel real-time detection countermeasure called subspace diagnosis. First, principal component analysis has been utilized for feature subspace representations of images. After then, all extracted dimensions are divided into multiple clusters with a predefined scheme for the generation of unified monitoring statistics in various feature subspaces. For deciding the normal boundaries, Gaussian mixture model is considered and the Bayesian inference mechanism has been developed for adversarial example detection. Finally, to evaluate impacts from various attacks quantitatively, a subspace contribution index is further constructed for multi-space perturbation diagnosis. The effectiveness of the entire diagram has been extensively demonstrated on several datasets.
Development of a Semantic Representation Model of Criminal Information to Support the Assessment of Risk Situations

Situational Awareness (SAW) refers to the level of consciousness that an individual or team holds over a situation. In the area of ​​risk management and criminal data analysis, SAW failures can induce human operators to make mistakes in decision making and pose risks to life or property. In this context, risk assessment processes, which commonly involves data mining, fusion and other methods, present opportunities to generate better information and contribute to the improvement of the SAW of crime and risk analysts. However, the characterization of complex scenarios is subject to problems of representation and expressiveness of the information, which may influence its interpretation due to their quality and significance, generating uncertainties. The state-of-the-art in representation of information on risk situations and related areas presents approaches with limited use of information quality. In addition, the solutions are restricted to syntactic mechanisms for the determination of relations between information, negatively restricting the assertiveness of the results. Thus, this paper aims to develop a new approach to semantic representation of information of risk situations, more specifically creating domain ontologies, instantiated with crime data and information quality. In a case study, real information on crimes, represented by the new semantic model and consumed by computational inference processes, was be processed, aiming to characterize robbery and theft situations.
Effect evaluation of countermeasure method for image information leakage by electromagnetic radiation from ITE

Information technical equipment (ITE) usually produces unintentional image information leakage of display by its electromagnetic radiation. In this paper effect evaluation of countermeasure method for the financial ITE was studied, which has been rarely ever reported. The masking countermeasure technique was applied and effectiveness was evaluated. ITU-T K.84 and K.115 were referred to the calculation of protection distance. As a result, it was found that masking technique could reduce the SN efficiency of interception receiver more than 7.2 dB and reduce protection distance more than 163 m at 457.3 MHz in this example.
Sistem informasi geografis berbasis web untuk pembelajaran mitigasi bencana pada sekolah Dalam kawasan rawan bencana Gunung merapi

Klaten Regency is located in Central Java Province, Klaten Regency is included in the high level of disaster category. One of them is from the threat of Merapi volcano, the need for disaster mitigation from an early age or from school. Based on joint observation of Search and Rescue, Klaten Regency, the learning of Merapi volcano mitigation is still limited to simulations and there is no learning media that is easier to use and innovative. This study aims to develop Web-based mitigation learning media. This research method uses the Research And Development (R&D) method and the development method used in this research is the ADDIE (Analysis-Design-Development-Evaluation) model. The subjects of this research were VIII grade students of SMP Negeri 1 Kemalang. Data collection techniques in this study were carried out by observation and questionnaire. Data analysis techniques by calculating the percentage of questionnaire results. The results of the study are as follows: 1) The average rating of the media expert is 93.1% which is included in the very feasible category. 2) The average rating of the material experts is 92.5% which is included in the very feasible category., 3) The average rating of students is 87.30% which is included in the very poor category. The conclusion in this study is the application of Web Gis-based Mount Merapi disaster mitigation learning media is appropriate to use.
The identification of trade secret elements: United States v. Chung

This article examines the legal nature of a trade secret. The term «trade secret» has been being developed by common law and statute law within the legal system of the United States, especially the Uniform Trade Secrets Act of 1979 and the Economic Espionage Act of 1996. The differences between their scopes of appli­cation are considered along with the features of a trade secret being embodied therein. The question of trade secret protection is discussed on the basis of the case «United States v. Chung», which has become the first conviction under EEA. It may be refered to as a vivid example of explaining the circumstances of trade secret infringement. Consid­ering the results of the research one can understand how legal norms related to trade secrets are practically applied and in which way a plaintiff, whose rights were violated, can ground his or her position that the information being the subject of claims contains a trade secret.