Miracle-dz/UniFAR-FTUs huggingface dataset:
Review on A Privacy-preserving and Copy-deterrence Content-based Image Retrieval Scheme in Cloud Computing

: With the increasing importance of people's everyday imagery, Content Based Image Retrieval has been extensively studied. Compared to text documents, images take up more storage space. Therefore, maintenance is a typical example of cloud storage. For privacy purposes, sensitive images, such as medical images and personal images, must be encrypted prior to outsourcing, which prevents CBIR technology in plain text domains. We have studied the process that supports CBIR over encrypted images without deluting sensitive information to the cloud server. Most common approach is the feature vector is separated to display the matching image. Subsequently the process contains, a pre-filter table that is created by a resident combination to optimize the search. In addition, the feature vector is protected by a safe kNN algorithm and the image pixels are encoded by standard stream numbers. We have studied the protocol that uses watermarks to inhibit such illegal distribution. In protocols that use watermarks, unique watermarks are embedded directly into the images encrypted by the cloud server before the images are sent to the user.
Bayesian Semi-supervised learning under nonparanormality

Semi-supervised learning is a classification method which makes use of both labeled data and unlabeled data for training. In this paper, we propose a semi-supervised learning algorithm using a Bayesian semi-supervised model. We make a general assumption that the observations will follow two multivariate normal distributions depending on their true labels after the same unknown transformation. We use B-splines to put a prior on the transformation function for each component. To use unlabeled data in a semi-supervised setting, we assume the labels are missing at random. The posterior distributions can then be described using our assumptions, which we compute by the Gibbs sampling technique. The proposed method is then compared with several other available methods through an extensive simulation study. Finally we apply the proposed method in real data contexts for diagnosing breast cancer and classify radar returns. We conclude that the proposed method has better prediction accuracy in a wide variety of cases.
Analysis of Public Sentiments using Annotation Technique

: Many users share their comments on Twitter that makes it a usable place for analyzing and interpreting public sentiment. This monitoring and analysis will provide important information for higher efficiency processes across multiple domains. In the proposed system, the model tends to take a step towards interpreting the sensory variations of tweets. We tend to discover that the subject has different feelings in a unit time period. The confidence variance is related to the true reason for the variations. To support this observation, LDA algorithm is used to refine topics and highlight long titles. These highlights will provide an interpretation of the potential trust model. We tend to select the most important tweets for the subject, and to develop another mechanical model, called hybrid model using Triple Relation Extraction (HTRE). To improve the readability of the search, most representative tweets were used for the leading subject and rank topics based on their "popularity" for the transition. The results show that our method can find the foreground and logical order efficiently. The proposed format can be used for other tasks, such as finding the difference between different twitter datasets.
Search for Images of Historical Objects Using Wikipedia

We investigate the temporal image retrieval problem by utilizing knowledge from Wikipedia to help retrieve images. Since current search engines do not explicitly consider the time related to the objects displayed in images, we believe that our proposed temporal image retrieval algorithm can more completely satisfy search intentions. A search is done by inputting an entity name (with/without location and time information), and chronologically sorted search results are output to capture the evolution of the queried entity and consider its co-occurrence with other historically important entities. We propose a novel way to map images to Wikipedia articles to utilize Wikipedia’s structure to estimate the historical importance of displayed objects. A combination of criteria is proposed to measure the historical importance of images under entity evolution scenarios and co-occurrence with other historically important objects.
J un 2 00 4 Possible Detection of Cosmological Reionization Sources

We compare the available catalogs of z ≈ 6 galaxies in the Hubble Ultra-Deep Field (UDF) and in the Great Observatories Origins Deep Survey (GOODS) with the expected properties of the sources of cosmological reionization from our previous theoretical study. Our approach is based on the mean surface brightness of the sources required for reionization and depends on relatively few undetermined parameters. We find that the observed mean surface brightness of galaxies at z ≈ 6 is sufficient for reionization, provided that the sources are composed of hot metal-free or metal-poor stars, regardless of whether reionization occurs over a short or long interval of redshift. The broad agreement between the new observations and our predictions suggests that we may have detected the sources responsible for some or even all of the reionization of hydrogen. Subject headings: cosmology: early Universe, observations, theory
Comorbidity of Obsessive-Compulsive Disorder and Post Traumatic Stress Disorder among Patients with Bipolar

Background: Obsessive-compulsive symptoms, and Post-traumatic stress disorder are common among patients with bipolar disorders. This comorbid condition complicates the clinical treatment of the disorders, so identifying these individuals is important. Aim: the study aimed to investigate the comorbidity of Obsessive-compulsive disorder, and Post-traumatic stress disorder among patients with bipolar disorder. Design: A descriptive exploratory designs was used. Sample: A sample of convenience of 150 of patients diagnosed as bipolar patients were selected from In and Out patient El-Abbassia Mental Health Hospital and Psychiatry and Addiction Prevention Hospital, El-Manial University Hospitals. Data collection tools: Sociodemographic and clinical data sheet, Yale Brown obsessive compulsive disorder scale, and the impact of event scale-revised (IES-R) were used to achieve the purpose of the study. A semi structured interview was used to collect the data from the studied sample. Main findings: Finding of the current study reveals that, most of the studied sample (96%) experiencing OCD symptoms, and 75.3% experience severe PTSD symptoms enough to suppress immune system’s function and 14% of them experience symptoms can provide proper diagnosis. Conclusion: The study concludes that, apparent comorbidity between bipolar disorder (BD) and obsessivecompulsive disorder (OCD), and post-traumatic stress disorder is a common condition in psychiatry and it has important therapeutic implications. Recommendations: Assess OCD, and PTSD with bipolar patients on admission and during follow up is important for the treatment plan.
MACROMECHANICAL PROPERTIES OF NANOFIBERS BASED ON POLY(LACTIC-CO- GLYCOLIC ACID) (PLGA) AND POLY(VINYL-ALCOHOL) (PVA)

Nanofibers can be tested on nanoor microscales, but also on a macro-scale, according to their intended application. The procedures of macroscopic testing of nanofiber textiles are similar to the testing of commonly used textile-based materials or foils, where one of the dimensions is significantly smaller (usually by orders of magnitude) than the other two. This paper presents the results of macroscopic tensile testing on nanofiber textiles – in particular tensile strength and stiffness expressed in force per unit width were investigated. The tested nanofibers were based on Poly(lactic-co-glycolic acid) (PLGA), and Poly(vinylalcohol) (PVA), manufactured using electro-spinning on a rotating cylinder electrode of width 500 mm and the tested nanofiber textiles had various weights per unit area. The common equipment for testing of material properties on macroscale could be used only in the case when textiles had the weight per unit area higher than 1 g/m 2 and only if the equipment was calibrated for the specific low-loading measurements. The preparation of tested specimens was also complicated due to their low rigidity. Another complication during the testing of nanofibers was the necessity of the textile ends protection, because they were clamped in the testing machine. The edge reinforcement was ensured by means of a common paper adhesive tape. The measurements confirmed that the mechanical properties of nanofiber textiles are dependent on the textile thickness or the weight per unit area.
An Effective Detection of Mobile Malware Behavior Using Network Traffic: TrafficAV

: Android has become the most popular mobile platform due to its openness and flexibility. Meanwhile, it has also become the main target of massive mobile malware. This phenomenon drives a pressing need for malware detection. In this paper, we propose TrafficAV, which is an effective and explainable detection of mobile malware behavior using network traffic. Network traffic generated by mobile app is mirrored from the wireless access point to the server for data analysis. All data analysis and malware detection are performed on the server side, which consumes minimum resources on mobile devices without affecting the user experience. Due to the difficulty in identifying disparate malicious behaviors of malware from the network traffic, TrafficAV performs a multi-level network traffic analysis, gathering as many features of network traffic as necessary. In an evaluation with 8,312 benign apps and 5,560 malware samples, TCP flow detection model and HTTP detection model all perform well and achieve detection rates of 98.16% and 99.65%, respectively. In addition, for the benefit of user, TrafficAV not only displays the final detection results, but also analyzes the behind-the-curtain reason of malicious results. This allows users to further investigate each feature’s contribution in the final result.
Visual localization system for fire brigade using BIM technology Final Report

​This paper describes a research that has been awarded the 2017 Chief Donald J. Burns Memorial Research Grant by the SFPE Foundation through a partnership with Bentley Systems. Research work in the field of acquiring, verifying, correcting and supplementing data. Performing activities aimed at confirming in a documented manner and in accordance with the assumptions that processes, materials, activities and created devices and systems actually lead to planned results. This report contains description of the proposed research project which focuses on the visual localization system for fire brigade using acceleration measurements and BIM technology.
A Survey on Recent Trends in Question Answering Systems

: Question Answering (QA) Systems is a mechanized way to deal with recuperate cure responses to the questions asked by human in natural language. The principal thinking behind QA framework is to enable man-to machine correspondence. In this paper, we propose scientific categorization for portraying Question Answer (QA) systems, quickly overview major QA systems depicted in literature. At long last, an examination between these approaches based on specific highlights of QA system discovered basic in our investigation has been done, so as to acquire an understanding to explore scope this course. QAS go for fulfilling clients who are hoping to answer a particular question in natural language. In this paper we study different QAS. We give likewise insights and investigation. This can make room and help analysts to pick the suitable answer for their issue. They can see the deficiency, with the goal that they can propose new systems for complex questions. They can likewise adjust or reuse QAS systems for particular research issues.
Working Paper Series 2020 / 003 The Economics of Crowdfunding

An entrepreneur finances her project via crowdfunding. She chooses a funding mechanism (fixed or flexible), a price, and a funding goal. Under fixed funding money is refunded if the goal is not met; under flexible funding there is no refund. Backers observe signals about project value and decide whether to contribute or postpone purchase to the retail stage. Using the linkage principle, we show that the optimal campaign uses fixed funding. Furthermore, we show that an entrepreneur who is not financially-constrained can approximately attract full surplus using fixed funding. Therefore, crowdfunding is attractive to both small and large entrepreneurs. JEL Classification: D42, D83, L11
An Efficient Execution Scheme for Designated Event-based Stream Processing

With the increase of streaming information sources, stream processing has been an important research issue. In this paper, we introduce the designated event-based stream processing scheme in the stream processing engine. Different from the traditional stream processing scheme, the query results are supposed to be generated only when tuples come from designated streams specified by the user. After introducing the proposed scheme, we consider its implementation. We discuss some important implementation internals of the stream processing engine and show an efficient designated event-based execution scheme. We also consider multi-queries which is a common situation in the stream processing engine. The experiment shows the advantages of the proposed execution scheme.
A Review on Recovery of Image with Image Inpainting Technique

—The advancement of multimedia instrument in day to day activities of human being, they are trying to click each and every moment of line. But as the time surpasses the picture get damaged. While clicking the pictures the unwanted person is also came in image, unwanted text in image. These are the some of the examples which causes the problem in image. Image inpainting is method which helps us to recover images. This modification is done so smartly which is unreadable for common user and he is unable to find any problem in image. Image inpainting is used to fill that damaged portion by gathering information related to pixel from nearby region. It searches the pixel information with maximum matching value and closely resembling with original image. The common user is not able to find any difference between damaged image and original image. In this research paper different image inpainting techniques are discussed. The advantages and disadvantages of techniques are discussed by considering time limit and efficiency parameter of image inpainting.
Ecosystem based Adaptation: Building on No Regret Adaptation Measures1

The no-regret approach is an important part of EbA and focuses on maximizing positive and minimizing negative aspects of nature based adaptation strategies and options. No-regret actions include . measures taken by communities [and/or facilitated by organisations] which do not worsen vulnerabilities to climate change or which increase adaptive capacities and measures that will always have a positive impact on livelihoods and ecosystems regardless of how the climate changes.
Impact of Social Media in Coffee Retail Business

Retail coffee business has been growing fast in the Middle East countries particularly during the last decade. High penetration rates of mobile communication devices such as smart phones and high usage of Social Media make the coffee retails in the region with Fee WIFI access, very attractive off-line and on-line social venues. The growth of internet in Arab countries is continuous and offers many e-commerce opportunities for retail businesses to penetrate, grow and achieve loyalty. This article aims to test how coffee retail businesses can optimize social media usage in order to increase their customer base, reach higher level of customer satisfaction and hence increase rate of customer loyalty in the long run. The literature review focuses on social media engagement and use of businesses, small businesses and retailers in the world and in the middle-east, coffee shop industry and coffee shop service expectations of customers. The primary data collection is targeted to test the constructs identified in the secondary data for coffee retail business as well as social media engagement of subjects who frequent coffee shops. Proposed conceptual model suggests that social media engagement of coffee shops customers through retailers’ social media and internet presence will lead to higher satisfaction about the shop and consequently transform them into loyal customers. Therefore, finally the model suggests that coffee shops should continuously seek to optimize their social media enabled marketing activities in order to achieve their business objectives.
Influence of Environmental Parameters on Lipase Production by Serratia Marcesens

Lipase-producing bacteria were isolated from the soil in Ohuhu Community in Umuahia North Local Government Area of Abia State, The crude extra cellular lipases from cell-free culture supernatant were reacted in an olive oil mixture and Rhodamine B dye and their lipolytic activities examined. Among the several bacteria screened, a strain was selected for lipase production as it showed the largest orange fluorescence under UV light, indicating effective production of lipase. Lipase production was carried out using a basal medium containing KH2PO4, Na2SO4, MgSO4.7H2O, Yeast extract, K2HPO4, Peptone, Glucose and Olive oil. Morphological, biochemical and molecular characterization of the isolate identified it as Serratia marcescens. Various physicochemical parameters that were investigated such as pH, temperature ranges, incubation time and rates of agitation were investigated in a shake flask culture and it revealed that pH 6 and Temperature of 40 0 C at 150 rpm for 48 hrs gave optimal lipase activity. It could be inferred that at pH of 6.0 and temperature of 40 °C for 48hrs optimum lipase production by Serratia marcescens can be maximized.
VERTICAL INTEGRATION AND TECHNOLOGICAL PORTFOLIOS IN SUPPLY CHAINS: EXPLORING THE CONNECTIONS WITH THE “DUAL ARCS” FRAMEWORK

Purpose The purpose of this manuscript is to develop a better understanding of how different degrees of vertical integration for the supply chain structure of a focal organisation shape the breadth of its technology portfolio Design/methodology/approach Three case studies were conducted with key players in the Australian retail sector with a distinct supply chain structure. A supply chain network perspective was taken which included manufacturers or suppliers, transport and logistics service providers as well as wholesalers/distributors of these retail organisations. Findings We find several interesting aspects regarding the level, type, complexity and sophistication of information technologies employed by the three case organisations and their extended trading partners. We highlight how the choice of supply chain technologies is affected by their supply chain structure (level of vertical integration). We find that a disintegrated supply chain structures have broader arc of technological breadth whereas integrated supply chains have a narrow arc and is underlined with consistent standards Research limitations/implications (if applicable) This study is confined to three organisations in the Australian retail sector so any extensions should be conducted with caution. Practical implications (if applicable) The framework developed by this study guides organisations in terms of assessing the appropriateness of their supply chain structure with the objectives of their supply chain systems. For standards setting bodies, the findings of this study suggests that technologies need to be tailored to the requirements of the supply chains (with the level of vertical integration being one easy way to segment the supply chain types).
Asset prices and monetary policy in Sweden

Up until 7th August 1997 the Swedish stock market had risen without a major correction since Sweden abandoned the fixed exchange rate system in November 1992. The recent correction has been around 8% as in most European stock markets. Figure 1 shows the Affärsvärlden's General Index (AFGX) for the period January 1985 to July 1997. During this period there have been three major setbacks. The first was in 1987 when the market fell by 32% in just two months. The second major reversal in stock prices came in 1990 when the market dropped by 36% between July and November. The third correction occurred in 1992 with a 30% decrease from May to September.
Internalized stigma experienced by patients with first-episode depression: A study from a tertiary care center

Background: Although there is abundant literature on stigma and its correlates in patients with severe mental illnesses such as schizophrenia and bipolar disorder, data on stigma experienced by patients with first-episode depression (FED) are limited. Aims and Objectives: To estimate internalized stigma perceived by patients with FED and to assess the relationship of stigma with sociodemographic and clinical variables. Methodology: This cross-sectional study included 107 patients with FED with duration of illness of at least 1 month, currently not meeting the criteria of syndromal depression (as assessed on Hamilton depression rating scale score ≤ 7). These patients were assessed on Internalized Stigma of Mental Illness Scale (ISMIS) for internalized stigma and Participation Scale for restriction of activities. Results: About two-fifths of patients (41.1%) reported stigma as per the total ISMIS score. In terms of various domains of stigma, stereotype endorsement (54.2%) was reported by the highest proportion of patients and this was followed by alienation (47.7%) and discrimination experience (38.3%). About half of the study sample (49.5%) reported restriction in participation with one-third of the sample reporting having severe or extreme restriction. Younger age, longer duration of depressive episode, and presence of comorbid physical illness were found to be strongly associated with higher level of stigma. Higher level of participation restriction was associated with higher level of stigma in the domains of alienation (P ≤ 0.001) and social withdrawal (P ≤ 0.004). Conclusions: The present study suggests that internalized stigma/self-stigma is highly prevalent among patients with FED. Accordingly, there is a need to develop stigma mitigation programs addressing these patients at the earliest to improve their treatment outcome.
Extraction and Characterization of Cellulose from Jackfruit Rind (Artocarpus Heterophyllus)

In this study, jackfruit cellulose was extracted by undergoing two steps; bleaching and alkaline treatment. The first step was the production of holocellulose by using bleaching method that removed the lignin from the jackfruit rind (JR). Next step was converting the holocellulose into cellulose by using alkaline treatment at room temperature. The percentage of cellulose extracted from JR in this study was 40% which was higher than the previous research. The characterizations of extracted JR cellulose were investigated by using Fourier Transform Infrared Spectrometer (FTIR) and Scanning Electron Microscopy (SEM). FTIR confirmed that the removal of non-cellulosic components in the jackfruit fibre and the micrograph by SEM displayed a rough surface indicated the presence of the cellulose fibre. Based on this study, JR has the potential to be used as a reinforcement element in composite materials.