Reviewerly/exHarmony huggingface dataset:
Research on One-Dimensional Barcode Recognition of Express Delivery Based on Machine Vision

To improve the efficiency and accuracy of barcode recognition in express delivery on the production line, a one-dimensional barcode recognition algorithm based on machine vision technology was studied. This studies first express image acquisition platform is designed, and then the express mail address information, by using a method of image processing of automatic identification according to the barcode coding principle, adopts the method of article to calculate the width of the empty realization decoding, getting barcode digital information, which interacts with the express query web site, for express mail address information.
LibGuides: Requesting Materials from Skyline Library: Important Safety Information

This guide is for students who need technology, books and other items from Skyline Library. It explains how to request, pick up and return materials.
DYNAMIC VIRTUAL MACHINE MANAGEMENT IN CLOUD DATA CENTERS

Hidden text: The abstract may be included at the discretion of the supervisor.The cloud computing paradigm engages a growing number of complex applications to run in remote data centers that have thousands of servers around the world. However, cloud data centers consume massive amounts of electrical energy. The increase in energy consumption causes an increase in cloud users cost. Currently, one of the widely used techniques for decreasing the energy consumption is dynamic Virtual Machine (VM) consolidation. Within a consolidation, the cloud service provider can run numerous VMs on each server (host), live VM migration from an underloaded server to another, and switching the idle servers to the low-power sleep or hibernation mode. Nevertheless, consolidation has a negative impact on performance leading to the Service Level Agreement (SLA) violations and affects the Quality of Service (QoS) requirements of cloud users. Hence, cloud-service providers face the energy-performance trade-off problem. Numerous VM consolidation mechanisms have been proposed in the literature to deal with this problem. Nevertheless, they either give preference to minimizing energy consumption or SLA violations. Indeed, selecting which VM to migrate from one host to another and deciding the preferable host for placing the migrated VM is a challenging task since it can affect performance. Researchers came up with several solutions and policies for efficient VM selection and VM placement. This thesis exploits the fact that many tasks and users may tolerate some performance degradation. In other words, tasks running on the VMs can be of different priorities. Accordingly, this thesis proposes novel priority-aware management for dynamic VM consolidation where low priority tasks are always selected first for migration. The efﬁciency of the proposed management is confirmed through simulations using CloudSim toolkit and a real workload. The results show that priority awareness is a promising scheme, which has a positive impact on decreasing energy consumption as well as maximizing the obligation of SLA.
How Reverse Image Search Technology & Algorithms Work

Browsing for reverse photos using automated tools is handy. It provides you similar images and finds duplicate ones in return for your query. It is the ...
Deep Learning Platforms

There are many deep learning platforms available such as Caffe, TensorFlow, MXNet, Torch, and Theano. Caffe (Convolutional Architecture for Fast Feature Embedding) is a deep learning framework, which originally was developed at the University of California, Berkeley. Caffe supports visual object detection and classification as well as image segmentation using CNN, R-CNN, LSTM, and fully connected neural networks. Caffe supports GPU-based and CPU-based acceleration. Caffe2 includes new features such as Recurrent Neural Networks. At the end of March 2018, Caffe2 was merged into PyTorch.
LibGuides: Educational Apps : Welcome!

Check out these free to low cost apps that can help supplement your classes! Just a few minutes a day can make a difference!
The effect of political connection on tax evasion: Post-revolutionary evidence from Tunisian firms

In this study, we examine the effect of political connection on tax evasion in the Tunisian context. We use a sample of 72 Tunisian firms observed from 2012 to 2015. To measure firms’ political connections through their board of directors, we manually collected a wide-ranging data set from various sources. To measure tax evasion we relied on a fundamental proxy: the effective tax rate (ETR). The findings show that politically connected firms are more likely to avoid taxes via the practices of tax evasion than non-connected firms. Thus, directors who have former political position tend to favor the tax evasion. The results may be useful for investors in their process of evaluation of benefits and risks associated with their investment and also for tax authorities in the establishment of their plans of enforcement activities. To the best of our knowledge, until now this is the first study to investigate the effect of political connection on tax evasion for Tunisian firms.
Prototype of Blind Aid Tool With The Haar Like Feature

Every human being is born perfectly but not all humans are born perfect, some of us are born have a deficiency in blindness. Blind people are someone whose vision is impaired from birth or because of an illness that causes their vision to be disrupted. Blind people need tools for their daily activities usually in carrying out blind activities using tools as a tool. Tools that are now widely circulating only as a detector can not yet identify objects, for that blind people neeed a tool that can identify the object. To make this happen, a prototype design research is done. Blind assitive devices use the haar like feature and extreme contour methods. Prototyping method is chosen so that users can play an active role during the process of designing, testing and implementing tolls. Contour is a curve or image that has similarities with objects or objects with functions using OpenCv. The conclusion of the detection results using the haar like feature method is the form of a string then processed using pygame so that the blind are able to know the object in fron of it.
Linear Collaborative Discriminant Regression and Cepstra Features for Hindi Speech Recognition

Speech recognition system is one of the significant, but challenging systems in computer-human interaction. Recognizing Indian languages, especially Hindi, find many practical difficulties due to its wide grammatical and phonetic features from English.  This paper focuses on Hindi speech recognition system for which Cepstra features and linear collaborative discriminant regression (LCDR) model are proposed for feature analysis and recognition. For a definite of audio signals, two models of test speech signals are synthesized and experimental investigations are carried out. The performance of the LCDR methods are analysed using Type I and II error functions and compared with the existing methods such as NN2-cepstra and SVM2-cepstra. Moreover, the best, worst, mean, median and standard deviation are used for the statistical prediction and the proposed LCDR method is proved as the superior method for recognising Hindi speech.
On the use of technique and technology in education

This text reflects upon the impact of Information and Communication Technologies (ICT) on education from a philosophical, historical and hermeneutical point of view. The results show that, currently, there is a problem of comprehension of the concepts of educational technique and technology, evidenced in the different ways of interpreting and evaluating the appearance of ICT in education. In the end, it is proposed to continue the debate on technique and technology in the various teaching andlearning processes.
On the Use of Elliptic Curves in Public-Key Cryptography

In this thesis, an introduction to public key cryptography over finite fields and elliptic curves is given. Elliptic curves are introduced using affine and projective spaces. The thesis also gives an introduction to algorithms that are able to break the discrete logarithm problem over finite fields and elliptic curves faster than an exhaustive search.
An attempt to enhance the time of reply for web service composition with QoS

The web services are the commonly prevailing service clusters of the service-oriented framework (SOA) and service related assessments. The disputes are related to the quality of service (QoS) for choosing web services freely and creating a collection of web services for carrying out trades. The ultimate aim is to choose web services based on the non-functional features and quality of service (QoS) ranks. In order to choose a web service for every process a social aspect web (SAW) scheme is employed which does not comprehensively make use of all sorts of web services. It employs the requirements of the user for ranking web service set of the applications and finally provides SAW schemes over a set of web service applicants. The mechanism helps in selecting the web services in terms of quality of services (QoS) scores and user needs. The choice of web services over varied web services based on scheme can be utilised for aggregation and organising web services resulting in optimised time of reply to the web service actions.
PENGEMBANGAN BAHAN AJAR E-BOOK BERBASIS FLASH FLIP BOOK PADA KOMPETENSI DASAR MEMAHAMI PENYIMPANAN DAN PENGGUDANGAN DI KELAS XI SMK PPN LEMBANG

Pengembangan bahan ajar e-book berbasis flash flip book ini dilakukan berdasarkan hasil wawancara kepada guru mata pelajaran keamanan pangan, penyimpanan dan penggudangan dimana mata pelajaran tersebut adalah mata pelajaran dengan kompetensi dasar yang cukup banyak dan materi yang cukup sulit, sehingga dalam proses pembelajarannya untuk menghindari kejenuhan diperlukan bahan ajar yang inovatif dan variatif, bukan hanya menyajikan teori dan gambar tetapi perlu juga menampilkan audio dan video. Penelitian ini bertujuan untuk mengembangkan dan mengetahui kelayakan bahan ajar e-book berbasis flash flip book yang dapat digunakan dalam pembelajaran kompetensi dasar memahami penyimpanan dan penggudangan. Metode yang digunakan dalam penelitian ini adalah Research and Development (RDThe development of e-book learning materials based on flash flip book is based on the results of interviews with teachers of food safety, storage and warehousing where these subjects are subjects with considerable basic competence and material that is quite difficult, so in the learning process to avoid saturation requires innovative and varied teaching materials, not only presenting theories and images but also displaying audio and video. This study aims to develop and determine the feasibility of flash flip book based e-book teaching materials that can be used in learning basic competencies in understanding storage and storage. The method used in this research is Research and Development (R&D) which consists of ten stages, namely identification and potential problems, data collection, product design, design validation, product revision, small-scale product trial, product revision I, product trial large scale, revised product II, and final product. The assessment of the feasibility of flash flip book-based e-book teaching materials is reviewed from several assessments, including the assessment of media experts, the evaluation of linguists, the assessment of material experts, and the assessment of students as respondents. Flash flip book based e-book teaching materials are considered very feasible by media experts, material experts, and linguists. The results of small-scale trials on students showed that the average value in the aspect of presentation of the material, aspects of interest in teaching materials, and in aspects of the display of teaching materials included in the agreed category. The results of large-scale product trials of students stated strongly agree on the aspects of the presentation of material, interest in teaching materials, and display of teaching materials.
An Analysis on Prospective Teachers’ HCK: Focused on Understandings of Inverse Function Symbol

This study analyzed characteristics of prospective teachers' HCK related to understandings of inverse function symbol. The aim of this study based on the analysis was to deduce implications of developing HCK in terms of the means which would enhance mathematics teachers' professional development. In order to achieve the aim, this study identified features of HCK by examining the previous literature on HCK which has conformed Ball &amp; Bass(2009) and exploring the research in AMT including Zazkis &amp; Leikin(2010) which has emphasized cultivating AMT through university mathematics education. In addition, a questionnaire was developed with reference to the features of HCK and taken by 57 prospective teachers. By analyzing the data obtained from the written responses the participants presented, this study delineated the specific characteristics of the teachers’ HCK with regard to inverse function symbol. Additionally, several issues in the teacher education for improving HCK were discussed and the results of this research could provide inspiration for designing and implementing a teacher education program relevant to HCK.
LibGuides: Resources for Non-binary Students: References

Finding books, movies, and more featuring non-binary characters can be difficult. This is a list of resources, fiction and non-fiction, written about and often by non-binary people.
Relation Classification: How Well Do Neural Network Approaches Work?

Relation classification is a well known task in NLP. It classifies relations that occur between two entities in sentences by assigning a label from a pre-defined set of abstract relation labels. A benchmark data set for this task is the SemEval-2010 Task 8 data set. Neural network approaches are currently the methods that give state-of-art results on a wide range of NLP problems. There is also the claim that the models trained on one task carry over to other tasks with only a small amount of fine tuning. Our experience suggests that for the relation classification problem while a wide variety of neural network methods work reasonably well it is very hard to improve performance significantly by including different kinds of syntactic and semantic information that intuitively should be important in signalling the relation label. We think that improved performance will be hard to achieve without injecting controlled class specific semantic information into the classification process. In our experimentation we have given many different kinds of syntactic and semantic information by tagging suitable words with relevant semantic/syntactic tags. We have also tried various embedding methods like Google embeddings, FastText, Word-to-vec and BERT. None of these make a substantial difference in the performance which hovers between 82% to 85%. Surprisingly, when we looked at the top three classification performance it was above 96% that is 11 to 14% above the top one performance. This implies that it should be possible to boost the correct label from the second or third position to the first position by suitable semantic inputs and architectural innovations. We have experimented with an architecture that gives supplementary information about words in the sentence as well as the sentence itself in parallel with the main stream of information, namely the sentence itself. In one such case we are able to boost performance to state-of-art levels. A systematic investigation is ongoing.
The geometry of belief functions

Belief measures are complex objects, even when classically defined on finite sample spaces. Because of this greater complexity, manipulating them, as we saw in Chapter 4, opens up a wide spectrum of options, whether we consider the issues of conditioning and combination, we seek to map belief measures onto different types of measures, or we are concerned with decision making, and so on.
Eyes Wide Shut: Gaze dynamics without vision,

Video stream: https://vimeo.com/365522806&#x0D; The human ability for visualization extends far beyond the physical items that surround us. We are able to dismiss the constant influx of photons hitting our retinas, and instead picture the layout of our kindergarten classroom, envision the gently swaying palm trees of our dream vacation, or foresee the face of a yet-to-be-born child. As we inspect imaginary objects and people with our mind’s eye, our corporeal eyeballs latch onto the fantasy. Research has found that our eyes can move as if seeing, even when there is nothing to look at. Thus, gaze explorations in the absence of actual vision have been reported in many contexts, including in visualization and memory tasks, and perhaps even during REM sleep. This symposium will present the manifold aspects of gaze dynamics in conditions when the visual input is impoverished or altogether absent. Presentations will address the characteristics of large and small eye movements during imagined and remembered scenes, the impact of visual field deficits on oculomotor control, and the role of eye movements in the future development of neural prosthetics for the blind.
Research Guides: Computer Information Technologies (CIT): Home

Discover LCC Library resources and more for the Technical Careers Division's CIT programs: Computer Information Technologies; Geospatial Science; CIT Advisors; IT Student Alliance (ITSA); CIT Employment Resources; CIT Apprenticeship
Perception Through Image Processing Applications for Situation Awareness

This paper introduces a concept for the perception level of situation awareness through image processing applications. The perception of the information from the environment is lacking to achieve highly autonomous vehicles. This approach mainly focuses on collecting information from the environment using camera sensors. The frames from the camera are processed using multiple image processing algorithms, outputs converted into CAN message, and sent to the expert system. CE-Box custom hardware that consists of a Raspberry Pi 3b model counted with PiCAN 2 used to implement and evaluate this approach. The goal of this paper is to provide a conceptual method to make decisions based on the extracted information from the environment using image processing algorithms.
English Teachers' Interaction In The Time Of Covid-19 Pandemic On Online Learning At Public Islamic High Schools (MAN) In Pandeglang Regency

The education sector has been impacted by COVID-19. The school forced to shift the teaching to online learning modes. Teachers and students have had to adapt to this change, the way teaching and learning, and the assessment process. Hence, the writer focuses on the interaction in the time of Covid-19 pandemic on online learning at public islamic high schools, the research questions are 1) How is learning in the time of Covid-19 pandemic? 2) How is the interaction between students and teachers in online learning? The aims of the research are 1) to find out how the learning process when physical distancing 2) to find out what applications are used for learning from home 3) to find out the English teachers’ interaction in online learning, and to find out the opportunities and challenges of online learning through Whatsapp group based on students’ perspective. This research uses the qualitative method. The population of this research is the students in grade X, XI, and XII at public islamic high schools (MAN) in Pandeglang regency. The data collection technique is a survey by distributing questionnaires (N=203, 148 females, and 55 males), the research conducted during the Covid-19 pandemic in May 2020. The results of the research concluded that online learning use technology, although without preparation/ planing because the Covid-19 pandemic showed a pretty good interaction and its progress. So, it is liked by 136 students (67%), 54 students (26.6%) did not like and 13 students (6.4%) be neutral.
PERAN LINGKUNGAN TEMAN SEBAYA DALAM MEMODERASI PENGARUH STUDENT ENGAGEMENT TERHADAP HASIL BELAJAR SISWA MATA PELAJARAN EKONOMI(Survei pada Siswa Kelas XI IIS SMAN di Kabupaten Bandung Wilayah 4)

The background of this study was learning outcomes low on economic subjects, evidenced by the results of the Mid Semester Assessment (PTS) of the 2019/2020 school year which is still below the Minimum Mastery Criteria (KKM). This study aims to determine the effect of student engagement on learning outcomes with peer environment as moderating variables. The population of this research is 6th grade students of IIS SMAN in Bandung Region 4 as many as 6 schools, then using a random sample technique obtained as many as 268 student samples. The research method used is an explanatory survey with hierarchical regression data analysis techniques and multiplier regression analysis (ARM). The results showed that: (i) student engagement in the high category, peer environment in the high category, and low learning outcomes; (ii) student engagement has a positive effect on learning outcomes; (iii) peer environment negatively moderates the effect of student engagement on learning outcomes
Assessing the Mobility of Elderly People in Domestic Smart Home Environments

A continuous monitoring of the physical strength and mobility of elderly people is important for maintaining their health and treating diseases at an early stage. However, frequent screenings by physicians are exceeding the logistic capacities. An alternate approach is the automatic and unobtrusive collection of functional measures by ambient sensors. In the current publication, we show the correlation among data of ambient motion sensors and the wellestablished mobility assessment Short-Physical-Performance-Battery and Tinetti. We use the average number of motion sensor events for correlation with the assessment scores. The evaluation on a real-world dataset shows a moderate to strong correlation with the scores of standardised geriatrics physical assessments.