Reviewerly/exHarmony huggingface dataset:
Analysis of Cloud Computing Load Balancing Algorithms

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
The Historical Aspect of the Development of Quantum Consciousness at the Beginning of the XXI Century

The biochemical model explains the complex mechanisms of mental life seems to be correct. The transmission from inanimate matter to living matter cannot be explained. He still cannot explain the nature of consciousness and the transition from inanimate matter to living one. Where is the threshold and what is the role of biochemical processes in consistency of soma and consciousness as well as in building a mental structure. The author supports the thesis that the nature of mental processes is inexplicable as far as interactions of biochemical processes are concerned and it is much easier to describe it in the light of quantum processes.
Living in Denial: The Relationship between Access Denied Turnaways and ILL Requests

Access denied turnaway statistics are provided to libraries to help with serials collection development, but very little research about turnaways is available. This article examines the relationship between access denied turnaways and interlibrary loan (ILL) requests at one institution in an attempt to deepen our understanding of turnaways. The study showed that there is a moderate correlation with an overall ILL requests to turnaways ratio of 11.4%. The strength of the relationship and the ILL requests to turnaways ratio do vary depending on the publisher/provider. The article also discusses potential explanations and implications as related to the relationship.
Blockchain, consensus, and cryptography in electronic voting

Motivated by the recent trends to conduct electronic elections using blockchain technologies, we review the vast literature on cryptographic voting and assess the status of the field. We analyze the security requirements for voting systems and describe the major ideas behind the most influential cryptographic protocols for electronic voting. We focus on the great importance of consensus in the elimination of trusted third parties. Finally, we examine whether recent blockchain innovations can satisfy the strict requirements set for the security of electronic voting.
Human Activity Recognition Systems: State of Art

The present paper surveys the current research directions of the human activity recognition (HAR). Firstly, it is presented the problem of the occupational diseases and the importance of the HAR systems in the prevention of these illnesses. Then, the main steps and the most used techniques of the activity recognition process are described. Therefore, are referred some issues related to the HAR systems, that could affect both the system usability and recognition performance. By the end, the capital limitations related to these systems are discussed, as well as, some considerations to take into account in a future work.
Online Single Person Tracking for Unmanned Aerial Vehicles: Benchmark and New Baseline

Online tracking a specific person from a low-altitude unmanned aerial vehicle (UAV) is a very interesting and challenging problem to be solved. However, there exists no large-scale aerial video dataset regarding this online single person tracking (OSPT) task. To promote the study of the OSPT problem in UAV, we first construct a new benchmark dataset including 100 fully annotated aerial videos with nearly 130K frames and 11 challenging factors. Second, we evaluate several state-of-the-art online trackers with real-time performance using our dataset, considering the potential applications in the UAV platform. In addition, with respect to the OSPT problem, we attempt to design a new baseline method with the combination of tracking, detection and re-identification and conduct detailed analysis of different components. This method achieves much better performance than the existing online trackers, which will serve as a new baseline for our benchmark.
Assessment of the Geochemical Potential in a Complex Tectonic Environment of South-East Sicily: New Insights From Hydrochemical Data

We analyzed a large dataset (143 water sampling sites, 22 variables) of chemical parameters in local groundwaters from the south-east sector of Sicily, namely the Hyblean plateau, in order to set an original evaluation of its geothermal potential using applied geochemistry. The area was affected by volcanism until about 1.4 Ma. Today, though no active volcanism occurs, it is site of surface gas manifestations of focused degassing to which a mantle source has been attributed. We identified and thence selected the most promising sites (water springs and wells) based both on their main geochemical characteristics and on their calculated equilibrium temperature (resulting in the range between 50 and 140 °C). We then applied Principal Component Analysis (PCA) to this restricted dataset and we were able to discriminate between different sources of solutes, both natural and anthropogenic. Finally, we mapped the factor scores obtained from PCA and we focused on those likely related with geothermal conditions in order to highlight the areas with the highest geothermal potential.
Stop to Unlock - Improving the Security of Android Unlock Patterns

Android unlock patterns are among the most common authentication mechanisms on mobile devices.They are fast and easy to use but also lack security as user-chosen gestures are easy to guess and easy to observe.To improve the traditional pattern approach, we propose Stop2Unlock, a usable but more secure modification of the traditional pattern lock.Stop2Unlock allows users to define nodes where they stop for a limited amount of time before swiping to the next node.We performed a lab study (n=40) and a field study (n=14) to show that this small change in user interaction can have a significant impact on security with a minimal impact on usability.That is, user-selected Stop2Unlock patterns are significantly harder to guess while being comparable in terms of usability.Additional analysis showed that users perceived the stop component as a rhythmic and memorable cue which supported the selection of higher entropy patterns.
Reversible Data Hiding in Audio Based on Discrete Cosine Transform and Location Maps

Transmitting information via public networks is prone to illegal attacks.Thus, data hiding is a suitable aspect that is useful to assure information security.Nowadays, multimedia tempering becomes the most variety problem that occurs on public networks.Audio steganography methods aim to hide secret data in an audio file called cover.Many methods in the time domain can hide large data (payload) with relatively low robustness.On the other hand, transformed based frequency algorithms can be more robust but the recovery of the cover audio is not guaranteed.In this paper, we investigate the time and frequency domains and tend to bridge gaps in the area of data hiding with the frequency transformation methods.In addition, we propose a new reversible audio data hiding based on Discrete Cosine Transform (DCT) and location maps.This kind of map helps to fully recover both the secret message and the cover file from the stego where the frequency sample values are increased or decreased by 10 in correspondence with the intended bit to be embedded.The experimental results prove that this method is able to hide high payload, and it is also robust since it guarantees 100% the reversibility of both the secret message and the cover audio file.The quality measured by Signal-to-noise ratio (SNR) is approximately 75 dB, Normalized Correlation (NC) value is 1.000, and Bit Error Rate (BER) is around 0.006.Additionally, this method is able to maintain the quality and invisibility, which may not be achieved by some previous research.
Color Image Steganography using Dual Wavelet Transforms

Steganography is the art and science of covert communication.The secret information can be concealed in content such as image, audio, or video.This paper provides a novel image steganography technique which hides both image and key in color cover image using Discrete Wavelet Transform (DWT) and Integer Wavelet Transform (IWT).The cover image and secret image coefficient values are embedded by using a fusion technique.The cover image is a color image and the secret image is a grayscale image.This algorithm first separates RGB color planes of the cover image.Next, the algorithm extracts either DWT or IWT coefficients of both R-plane of the cover image and secret image.These two extracted coefficient values are fused into a single image by using a wavelet-based fusion technique.By taking IDWT/IIWT transform of the fused image the stego image is obtained.Different combinations of DWT/IWT transforms were performed on the scrambled secret image and cover image.Experimental results shows that the proposed method can produce stego images with high level of perceptual invisibility and security.
Improved optimization of numerical association rule mining using hybrid particle swarm optimization and cauchy distribution

&lt;div class="page" title="Page 1"&gt;&lt;div class="layoutArea"&gt;&lt;div class="column"&gt;&lt;p&gt;Particle Swarm Optimization (PSO) has been applied to solve optimization problems in various fields, such as Association Rule Mining (ARM) of numerical problems. However, PSO often becomes trapped in local optima. Consequently, the results do not represent the overall optimum solutions. To address this limitation, this study aims to combine PSO with the Cauchy distribution (PARCD), which is expected to increase the global optimal value of the expanded search space. Furthermore, this study uses multiple objective functions, i.e., support, confidence, comprehensibility, interestingness and amplitude. In addition, the proposed method was evaluated using benchmark datasets, such as the Quake, Basket ball, Body fat, Pollution, and Bolt datasets. Evaluation results were compared to the results obtained by previous studies. The results indicate that the overall values of the objective functions obtained using the proposed PARCD approach are satisfactory.&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;
Criteria-based Assessment of Spatial Representations in Primary School Students

The formation of spatial representations in schoolchildren is one of the most important tasks of the teaching methods of mathematics in the primary school. The images of phenomena, actions, objects that reflect spatial relationships of size, shape, location, and movement of objects are mentally created with spatial representation. The problem of performance assessment is one of the most urgent problems in pedagogical practice. In addition, subjectivity of the school marks, which is already observed at the initial stage of teaching, is the main problem in the assessment. To solution to this problem contributes an introduction into the practice of criteria-based assessment, i.e the assessment process based on the comparison of students’ learning achievements with clearly defined, collectively developed criteria known to all participants of the educational process that are consistent with goals and content of education, promoting the development of students’ ability to study.
Implementasi Metode Promethee Dalam Sistem Pendukung Keputusan Penilaian Raport Dosen

Assessment of lecturer report cards is a decision-making process using information obtained through measuring the results of lecturer performance by students and administrative completeness of each lecturer. The object used in this study is the Informatics Engineering IV Study Program using the promethee method. The Promethee method is used to obtain a ranking of grades from lecturers. Promethee's method of calculating requires several alternatives and criteria. The alternative used for assessment is the lecturer who teaches in the D IV Informatics Engineering Study Program. The criteria used to assess each alternative are lecturer assessment data by students which includes student assessment input taken from the final score or the average resulting from the questionnaire assessment filled in by students. Administrative appraisal data which includes: syllabus collection, collection of college contracts, modules, number of attendance, timeliness of UTS and UAS collection questions as well as the timeliness of collecting UTS and UAS scores. From this study, the assessment of lecturer report cards was obtained, which also included lecturer rankings based on the scores produced. System testing is done by comparing the results of manual assessment with the results of the assessment produced by the system. Based on the testing that has been done it can be concluded that the results of testing both manually and using the system are the same.
A Large-Scale Analysis of Regional Tendency of Twitter Photos Using Only Image Features

It is common activities for many people to post photos on open SNSs such as Twitter and Instagram where anyone can see all the posted photos. The difference on idea of the privacy issue at SNSs depends on culture and history. In fact, the people in Eastern Asian such Japan and Korea do not like to post human face photos to SNSs, while Western and South-Eastern-Asian people posts many human face photos. To make this fact clear and explore it deeper, we analyzed geotagged photos collected from the Twitter streams by classifying them into five kinds of rough categories, "people", "building", "document", "scene" and "food". As results, we found there are quite large differences on regional tendency of posted Twitter photos regarding the photo genre distributions.
An ensemble of neural networks for nonlinear segmentation of overlapped cursive script

Precise character segmentation is the only solution towards higher optical character recognition (OCR) accuracy. In cursive script, overlapped characters are serious issue in the process of character segmentations as characters are deprived from their discriminative parts using conventional linear segmentation strategy. Hence, nonlinear segmentation is an utmost need to avoid loss of characters parts and to enhance character/script recognition accuracy. This paper presents an improved approach for nonlinear segmentation of the overlapped characters in handwritten roman script. The proposed approach presents a set of rules that are derived heuristically to search character boundaries of the cursive script that is validated by using ensemble of neural confidence. Accordingly, correct boundaries are retained and incorrect are removed based on ensemble neural networks vote. Finally, based on verified valid segmentation points, characters are segmented nonlinearly. For fair comparison CEDAR benchmark database is experimented. The experimental results are much better than conventional linear character segmentation techniques reported in the state of art. Ensemble neural network play vital role to enhance character segmentation accuracy as compared to individual neural networks.
An Ontology Approach for Knowledge Representation of ECG Data.

The number of features that can be extracted from ECG signals has increased with the advancement in signal processing techniques. At the same time, there is an increase in research efforts to support efficient and effective analysis and interpretation of these signals. In this paper, we propose the use of ontology for knowledge representation and discovery of ECG data. Given the lack of a widely acceptable standards, the use of ontology can support the establishment of common understanding of the kind of knowledge that can be extracted from the ECG data and shared among various heterogeneous systems. The proposed ontology is both platform and application independent. Furthermore, it is possible to enrich the proposed ontology with new knowledge that may not explicitly be expressed in the data.
3D Res-Inception Network Transfer Learning for Multiple Label Crowd Behavior Recognition

The problem towards crowd behavior recognition in a serious clustered scene is extremely challenged on account of variable scales with non-uniformity.This paper aims to propose a crowed behavior classification framework based on a transferring hybrid network blending 3D res-net with inception-v3.First, the 3D res-inception network is presented so as to learn the augmented visual feature of UCF 101.Then the target dataset is applied to fine-tune the network parameters in an attempt to classify the behavior of densely crowded scenes.Finally, a transferred entropy function is used to calculate the probability of multiple labels in accordance with these features.Experimental results show that the proposed method could greatly improve the accuracy of crowd behavior recognition and enhance the accuracy of multiple label classification.
Vaguelette-Wavelet Deconvolution via Compressive Sampling

Vaguelette-wavelet deconvolution (VWD) is known as a transform-based image restoration technique that involves applying wavelet-domain denoising to an observed image, followed by the Fourier-domain blur inversion, which can prevent noise amplification in conventional Fourier-domain deconvolution techniques. However, the direct application of VWD often results in poorly restored images because of the artifacts that result from the denoising and inversion stages. In this paper, we thus propose a new image deconvolution technique based on VWD that applies a cycle-spinning and averaging technique and a compressive-sampling-based recovery technique to suppress these artifacts. The experimental results revealed that the proposed technique outperforms the existing deconvolution techniques in terms of both restored image quality and computational cost.
TEACHING DERIVATIONAL PROCESS TO COMPOSE PROPER SENTENCE

The title of this research is Teaching Derivational Process to Compose Proper Sentence. The objective of this study was to prove whether or not that Teaching Derivational Process influences students’ ability in using the proper words in constructing proper sentence. The group pre-test post-test design and quantitative method were used in this research. There were 26 students in this research to be entire population and they are from SMK Mohammad Toha Cimahi. This research used pre-test and post-test as the instruments. The data were collected by giving the instruments to the students, both pre-test (before giving the students treatment) and post-test (after giving the students treatment) and to analyze the data, the writer used t-test formula. The result of this study showed that the mean score of pre-test was 50,38, the mean score of post-test was 82,30, the t-obs was 10, 96, the t-table with degrees of freedom (df) was 25 and level significance at 5 % (0,05) was 1,71. From the data analysis, the writer concluded that the students’ understanding about derivational process influenced their ability in using the proper word in constructing proper sentence and it also meant that the t-observe was higher than t-table (10,96 &gt; 1,71), so the alternative hypothesis was accepted.
INVENTORY INFORMATION SYSTEM OF GOODS USING CODEIGNITER FRAMEWORK

This type of research is experimental, namely by designing, manufacturing and testing the system model. This inventory information system aims to manage inventory data, incoming goods data and item data out at the real store. The testing method on this system uses black box testing which aims to find out functions that do not work well or errors from a system. From the results of testing on the modules in this system, namely logins, units, goods, incoming goods, outgoing goods, incoming goods and reports of outgoing goods can function properly. The inventory system that has been built can help a true store in terms of managing goods data, incoming goods data and outgoing item data
Protection of Systems Against Fuzzing Attacks

A fuzzing attack enables an attacker to gain access to restricted resources by exploiting a wrong specification implementation. Fuzzing attack consists in sending commands with parameters out of their specification range. This study aims at protecting Java Card applets against such attacks. To do this, we detect prior to deployment an unexpected behavior of the application without any knowledge of its specification. Our approach is not based on a fuzzing technique. It relies on a static analysis method and uses an unsupervised machine-learning algorithm on source codes. For this purpose, we have designed a front end tool fetchVuln that helps the developer to detect wrong implementations. It relies on a back end tool Chucky-ng which we have adapted for Java. In order to validate the approach, we have designed a mutant applet generator based on LittleDarwin. The tool chain has successfully detected the expected missing checks in the mutant applets. We evaluate then the tool chain by analyzing five applets which implement the OpenPGP specification. Our tool has discovered both vulnerabilities and optimization problems. These points are then explained and corrected.
Development of Learning Media Based on Mobil Learning Application

Development of mobile learning application-based media. Objectives: The purpose of this study is to develop a more dynamic learning media by utilizing technology in the form of applications on smartphone devices to improve student learning outcomes. Methods: This study uses research and development methods with data collection techniques in the form of questionnaires, feasibility tests and effectiveness of mobile learning applications developed as learning media through stages designed according to the ADDHIE model. Findings: Product development in the form of mobile learning applications is feasible as a learning medium and effective for improving student learning outcomes with an increase in the average value of 28 students from 57.32 to 81.43. Conclusion: Mobile learning application is a good choice as a learning media. Keywords: Learning media, mobile learning application, research and development Abstrak: Pengembangan media pembelajaran berbasis aplikasi mobile learning. Tujuan: Penelitian ini bertujuan untuk mengembangkan media pembelajaran yang lebih dinamis dengan memanfaatkan teknologi dalam bentuk aplikasi pada perangkat smartphone untuk meningkatkan hasil belajar siswa. Metode: penelitian ini menggunakan metode penelitian dan pengembangan dengan teknik pengumpulan data dalam bentuk kuesioner, tes kelayakan dan efektivitasi aplikasi pembelajaran mobile yang dikembangkan sebagai media pembelajaran melalui tahapan yang dirancang sesuai dengan model ADDHIE. Temuan: Pengembangan produk dalam bentuk aplikasi pembelajaran mobile layak sebagai media pembelajaran dan efektif untuk meningkatkan hasil belajar siswa dengan peningkatan nilai rata-rata 28 siswa dari 57,32 menjadi 81,43. Kesimpulan: Aplikasi pembelajar mobile merupakan pilihan yang baik sebagai media pembelajaran. Kata kunci: Media pembelajaran, aplikasi pembelajaran mobile, penelitian pengembangan DOI: http://dx.doi.org/10.23960/jpp.v9.i1.201907