Reviewerly/exHarmony huggingface dataset:
The Accuracy Comparison of Social Media Sentiment Analysis Using Lexicon Based and Support Vector Machine on Souvenir Recommendations

Social media is one source of information that can be obtained by organizations / vendors or consumers. One of the information obtained from social media is the opinion of social media users on a matter. These opinions can be positive, negative or neutral. Sentiment analysis can be used to assess the sentiments of the opinions expressed by social media users. Sentiment analysis method used is a machine learning algorithm that can help the classification process. In this study the comparison of the accuracy of opinion sentiment analysis on the recommendation of favorite souvenirs in the Yogyakarta area using the Lexicon Based method and Support Vector Machine. The processed data is Twitter and Instagram social media sentiment data. The training data used were 1000 sentiment data, while the test data for the testing process were 50 sentiment data. The test results obtained the greatest accuracy is using a Lexicon Based 87.78%, then the greatest precision results are using a Lexicon Based of 94.23%, while for the greatest recall results are using a Support Vector Machine of 100%.
Knowledge Enhanced Latent Relevance Mining for Question Answering

Answer selection which aims to select the most appropriate answer from a pre-selected candidate pool has become increasingly important in a variety of practical applications. Previous work tends to use complex attention mechanisms to capture contextual relevance between question-answer (QA) pairs while ignoring large scale commonsense knowledge. However, this commonsense knowledge provides real-world background information beyond the context, which can help to discover the latent relevance between two sentences. In this paper, we propose to integrate commonsense from the external knowledge graphs (KGs) into the answer selector through a knowledge-aware context-based attention mechanism. To explore the interrelations among knowledge and context, we leverage a compare-aggregate framework to capture more interactive features between questions and answers. Our model is evaluated on two widely-used benchmark QA datasets: WikiQA and TrecQA. The experiments show that our proposed model outperforms the state-of-the-art method.
ANALYSIS TECHNOLOGY OF ENVIRONMENTAL MONITORING DATA BASED ON INTERNET OF THINGS ENVIRONMENT AND IMPROVED NEURAL NETWORK ALGORITHM

With the development of industrialization, the problem of environmental pollution has become increasingly serious.Environmental monitoring data, as a measurement index of environmental quality, is increasingly valued by governments and citizens.However, the environmental data accumulated through real-time monitoring at the current stage is mostly used to write basic reports, while the hidden laws or values still need to be further explored.This paper proposes two original environmental prediction models and improves upon these two methods separately to predict the quality of the atmospheric environment.The following research results are obtained: the multivariate linear equation is optimized through stepwise linear regression, which can accurately predict the short-term atmospheric environmental quality; the improved BP neural network can predict the mid-term and long-term atmospheric environmental quality through short-term training.
Convolution Neural Network Development Support System using Approximation Methods to Evaluate Inference Accuracy and Memory Usage in an Embedded System

Convolution neural networks have become widely used in embedded systems such as automatic driving systems. In these cases, inference functions in convolution neural networks are implemented due to resource limitation in embedded systems. Field-programmable gate array implementation is preferable because of low power consumption and real-time response time in embedded systems. Parameters in a convolution neural network are floating-point numbers, and enormous floating-point calculation is required. This is a challenge because the field-programmable gate array has a limited floating processing unit and in-memory processing. One way to solve the problem is to approximate an enormous number of parameters and to perform efficient computation. In the approximation, floating-point numbers of parameters are implemented using smaller-size integers or numbers having fewer bits. However, the inference accuracy decreases in the approximation, leading to a tradeoff situation. In addition, which layer should be approximated in order to be effective is not clear. In order to solve these problems, we developed an approximation support system. The developed system approximates the parameters and calculates the accuracy of the parameters and the required memory size. Furthermore, using this system, we carry out experiments to evaluate the effectiveness of several approximation methods for a large-scale network and dataset.
Screen-Camera Communication System Based on Dynamic QR Code

Screen-camera communication is a new information communication method based on visible light. However, such communication mechanism relies on barcodes to transmit information which suffers a limited capacity and a low communication rate. Hence, we proposed a color multiplexed dynamic QR Code communication system based on mobile devices. Use this method can further improve the communication rates over the system. In our system, a self-defined frame structure has been designed for a better reliability and diversity in the transmission. The experiment results indicated that in the traditional dynamic QR Code transmission mechanism, the real-time communication rate is 150 Kbit/s and the non-real-time communication rate is 300 Kbit/s. While, under the proposed color multiplexed dynamic QR Code communication system, the real-time communication rate can reach 320 Kbit/s and the non-real-time communication rate can reach 900 Kbit/s. After multiple experimental tests, it can transfer text, picture and audio files with no error.
Black Box Explanation Guided Decision-Based Adversarial Attacks

Adversarial attacks have been the hot research field in artificial intelligence security. Decision-based black-box adversarial attacks are much more appropriate in the real-world scenarios, where only the final decisions of the targeted deep neural networks are accessible. However, since there is no available guidance for searching the imperceptive adversarial perturbation, boundary attack, one of the best performing decision-based black-box attacks, carries out computationally expensive search. For improving attack efficiency, we propose a novel black box explanation guided decision-based black-box adversarial attack. Firstly, the problem of decision-based adversarial attacks is modeled as a derivative-free and constraint optimization problem. To solve this optimization problem, the black box explanation guided constrained random search method is proposed to more quickly find the imperceptible adversarial example. The insights into the targeted deep neural networks explored by the black box explanation are fully used to accelerate the computationally expensive random search. Experimental results demonstrate that our proposed attack improves the attack efficiency by 64% compared with boundary attack.
Towards Accurate and Robust Fall Detection for the Elderly in a Hybrid Cloud-Edge Architecture

Falls are a very important phenomenon for elderly citizens because these can create fatal and non-fatal injuries and an effective fall detection technique is needed to prevent this hazard. In this paper, we are going to introduce a hybrid cloud-edge based architecture for elderly fall detection. This architecture consists of four tiers which are body area network (BAN), intelligent mobile edge, secure network and medical cloud. The BAN is composed of a number of sensors like accelerometer, gyroscope, camera etc. which can send valuable information about human activities. Data fusion of these sensors can be very useful in case of elderly fall detection in terms of achieving higher accuracy and lower false alarm rates (FAR)s. So here, we are going to introduce an algorithm, named, ActDec-SysOpt (Activity Detection System Optimization) which is based on long short term memory (LSTM) type machine learning technique focusing on fusion of accelerometer and gyroscope data to determine human activities particularly. The result shows that maximum 91 % accuracy with minimum 1.89 % FAR in detecting human activities can be achievable using these proposed algorithms.
SECURITY’S LEAKS IN SEO SPAMMING

The full lack of security provides a huge omission in the application or software development life cycle. An example of security flaw is an ineffective search engine optimization (SEO). That can lead to various troubles in an already well developed or during development Internet sites. There has been a rise in SEO spam and malware which purpose is to destroy the application search indexes by adding content, which does not correspond to the idea of the application. Unusual links, pages or comments can confuse the website's visitors and drive the traffic to malicious websites.A badly secure websites are juicy target for each hacker. In some cases, the obstacle of implementing each type of security protection is just time, but the worst reason is either uninformed or unqualified developers without experience in SEO. The amount of guides and tools to help them is huge which interferes with developers’ work by adding more time in investigating it!The purpose of the current research is to review SEO spams, malware, and the damages they can cause to the Internet applications! Firstly, we describe the concept and definition of SEO spams and malware. Then we are going to review different mechanisms for protecting the Internet applications of those SEO spams and malware. We provide basic information for each protection method as well as some real examples on the SEO spamming threat.In conclusion, we analyze different damages they can cause as well as different ways of finding those types of attacks by scanning some of the most common sites in Bulgaria. In the analysis, we have used the ALEXA Top 1 Million sites Insight tool. In addition to our new knowledge and skills gained during the research, we have added several more sites developed in our work and on which we have applied those skills.The concept of our entire study is to show the use of free tools in supporting developers’ work progress. Therefore, we are showing some free scanners in order to confirm what we propose in this research!The need of security integration in the web applications becomes more and more necessary with the evolution of technology. Along with other security’s implementations on a programming and on a server’s level the ones described in the article bring another layer of security management that mitigates certain types of cyberattacks and vulnerabilities. It does not fully protect our applications but it gives an extra level of security by restricting the attackers’ actions.Those attacks as well as other types of attacks prove that the security of an application must be taken apart and integrated at the beginning of the application development life cycle.
The Pronunciation of the Hijaiyah Letters for Autistic Children at Extraordinary Islamic School Qothrunnada Yogyakarta

This research aims to describe the pronunciation of the hijaiyah letters for autistic children at Extraordinary Islamic School Qothrunnada, as well as explaining factors cause errors of pronunciation of the letters hijaiyah and changing meanings. Formal object in this research is the pronunciation of the hijaiyah letters. The object of the material in this study is an autistic children at Extraordinary Islamic School Qothrunnada. The methods used in the analysis of data is a method in accordance and its preliminary technique is the technique hear and technique chat. Through this study, the researchers found the hijiayah letters which undergoes changes, with the following details 1) change letter Ø« become Ø³, 2) change letter Ø° become ,Ø¯ 3) change letter Ø² become ,Ø¬ 4) change letter Ø´ become Ø³, 5) change letter Øµ become Ø³, 6) change letter Ø· become Øª, 7) change letter Ø¸ become Ø¶, 8) change letter Ø¹ becomeØ£ , 9) change letter Ù‚ become Ùƒ, 10) change letter ï»« become Ø­, 11) change letter Ø¹ become nga. Factors cause changes in the sound is 1) Central System talk, 2) sound production system 3) the influence of first language, 4) articulation (makharijul huruf).
Web Application for Online MCQ Test

An Online Examinations system content provider is to focus on creating the effective assessment for questions and focusing on exam’s feedback delivered to the students. In the paper we present techniques that are patients to the elements of assessment process for question and answers submission, computerized grading, and feedback after submission. The examination system for computer is working on the instructions; it to becomes easier for the coordination of human beings, commodity and computers in a modern organization. The administration and student who attend the Online Examination system so we can communicate with the system through the instruction, thus facilitating effective implementation and monitoring of various activities of Online Examinations are conducting the exams are scheduled on the basis and delivering result to that particular student. The details of students who attempt the Online Examination are maintained to the administrator.
Enhance Part-Based Model for Person Re-Identification with Fused Multi-Scale Features

In recent years, part-based models have been verified their effectiveness for person Re-identification (Re-ID). Since they learn an embedding only by partitioning single-scale features of the highest layer in the backbone network, their performances highly depend on the well-aligned parts of the extracted feature maps. However, misalignments occur very commonly in person Re-ID tasks due to the variations of viewpoints and poses. To address the part-misalignment problem and learn a more discriminative embedding for person Re-ID, we propose a novel Part-based model with fused Multi-Scale features (PMS), which innovatively upscales the low-layer features by using UpShuffle Modules and smoothly integrates the high-layer features. The fused multi-scale features are very robust to the variations of pedestrian scale and beneficial to resolve the part-misalignment problem. Experimental results on three commonly used datasets, including Market-1501, DukeMTMC-reID and CUHK03, have validated our model by outperforming the state-of-the-art methods with no need of re-ranking.
COMPARISON THE BED SEDIMENT CONTAMINATION OF THE SOUTHERN PART OF EUPHRATES RIVER WITH SHATT AL-ARAB, IRAQ

&nbsp;This study aims to investigate the contamination of Euphrates and Shatt al-Arab with heavy metals. Identifying the pollution degrees and the sources of contamination are among the aims of this study. The fieldwork was carried out in January 2018 by using Stream Sediments Core Sampler Device at depths ranges 20–58 cm from eight river bed sediment sites (from S1 to S12) along the course of Euphrates to Shatt Al-Arab (from north Hilla to Basrah). About twenty-five core samples were chosen for this purpose. Twenty-one of heavy elements were determined by XRF technique. These trace elements are; Ta, W, Ni, Mo, Cr, As, Br, Pb, Co, Ga, Zn, Sr, V, Zr, Mn, Ba, Th, Cu, Rb, Y and Nb. Four indices are selected to evaluate the contamination levels. These are; enrichment factor (EF), the geo-accumulation index (I-geo), contamination factor (CF), and pollution load index (PLI). According to EF mean values, the heavy metals W and Ta recorded a very high enrichment category denoting very high pollution, whilst Ni and Mo referred to a significant category. Nevertheless, the other metals reflected moderate to minimal category. I-geo mean values showed high polluted grade for Ta metal, and moderate polluted grade for Ni, Mo and W metals. However, the other metals were either unpolluted or moderate to unpolluted. Due to CF average values, the heavy elements Ni, Mo, Ta, and W reported very high contamination, but the other elements generally had moderate to low contaminated grade. It was clear that the very polluted heavy elements in the current study were Ta, W, Ni, and Mo. Moreover, the contaminated grade can be ordered as following; Diwania&gt;Simawa&gt;Nasiria&gt;Hilla&gt; Basrah. The high degree of contamination may be mainly attributed to different anthropogenic sources. The other reason maybe originated from the crustal materials of natural origin (lithogenic source). &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp
Mapping of Pyroclastic Density Currents Hazards and Assessment of Related Risks by AMS Technique in the West-Cameroon Highlands: Case of Bambouto and Bamenda Volcanoes

Ignimbritic flow deposits which derived from pyroclastic density currents (PDCs) are mostly observed in West-Cameroon Highlands located in the central portion of the Cameroon Volcanic Line (CVL), especially in Bambouto (21.12 - 0.50 Ma) and Bamenda (27.40 - 0 Ma) volcanoes. These deposits covering approximately 27% (≈195 km2) of the volcanoes surface with thickness ranging from 30 to 200 m representing a total volume estimated at 20 km3. Because of the intense weathering of the ignimbritic formations after their setting up and being buried by basaltic and trachtytic flows, the initial volume of these pyroclastic deposits is really much larger. Soil fertility has fostered an important population growth (more than 1,200,000 people) in these volcanoes. The economic and agropastoral activities on the flanks and inside the caldera of the volcanoes are estimated at about $US7.5 billion. In this paper, we evaluate and realize cartography of the hazards associated to ignimbritic eruptions which are most disastrous in term of volcanic process in this region. Magnetic studies, specifically, Anisotropy of Magnetic Susceptibility (AMS) method has been utilized for the determination of flow directions in visually nearly isotropic ignimbritic deposits outcrops. The AMS data reported from the Bamenda and Bambouto volcanoes ignimbrites produced significant informations about the depositional scheme of the PDCs. In most sites, magnetic lineations and principally magnetic foliation are reliably parallel to downhill directions, frequently with an upslope imbrication. Inferred palaeoflow directions based on the field indicators, orientation of minerals and other objects in oriented thin sections and the directional AMS data show that Bambouto caldera, Oku crater and Santa-Mbu caldera are the sources of main PDCs of Bambouto and Bamenda volcanoes. These AMS results have aided us to produce a hazard and risks maps related to potential future pyroclastic flows on these volcanoes. The assessment of risks in these volcanoes was based on populations in the study area, infrastructures (houses and roads) and average income of breeding activity.
Defocus spot detection of astronomical optical system

Abstract Defocusing spot size detection is especially essential for aberration analysis and correction of optical systems. In the case of far defocusing, the celestial forms a pupil image on the detector, and the size of the image is linearly changed with the defocusing distance, and can be used to correct the optical system and analyze the image quality. Based on the focal plane attitude detection of Large Sky Area Multi- Object Fiber Spectroscopy Telescope (LAMOST), this paper uses a variety of methods to detect the size of the defocusing spot of LAMOST telescope. For the particularity of the spot, the average value spacing algorithm, the peak value spacing algorithm, the ellipse fitting algorithm, and the multi-peak Gaussian fitting algorithm are used to detect the spot size. This paper will introduce these four methods, in which the average value spacing algorithm is proposed by the author of this paper. The advantages and disadvantages of the four methods are compared. The experimental results show that the average value spacing algorithm can achieve better accuracy of spot size detection in the four algorithms.
Applications of Assistive Tools and Technologies in Enhancing the Learning Abilities of Dyslexic Children

Procuring proper education is the birth right of every individual.It is the terminal way to walkover all the personal and social problems and is significant to all as it plays very prime roles in every individual's life.So, all students regardless of any challenges they have, has to be placed in age-appropriate general education classes that are in their own neighbourhood schools in order to receive high-quality instruction, interventions, and supports that will enable them to achieve success in their life.In today's era technology is everywhere due to its wider applications.But there are specific tech tools that can help people who learn and ponder adversely and these are called assistive technology or AT which are often inexpensive easy to use and may range from low to high tech.Assistive tools and technologies are any devices, software's, or equipments that aid people to work around their challenges.It has a significant effect in helping students with disabilities progress towards the goals outlined on their Education Plans.It helps dyslexic students to save time and overcome from the challenges such as note taking and poor handwriting which allow them to demonstrate their abilities which are incredible.Also, to learn how to complete their task and bypass an area of difficulty.In this paper the author enumerates the various types of assistive tools and technologies which are helpful for dyslexic students who are having learning disabilities and these technologies includes computer program, tablet applications that provide text-to-speech speech-to-text word prediction capabilities graphic organizers and many more.