Miracle-dz/UniFAR-FTUs huggingface dataset:
Hiding Encrypted Data into Audio File

Summary Communication is one of the most important issues that affect different aspects of our lives. To communicate, it is important to ensure that the channel of such communication is secure. Secure channels are very limited because of their high cost. Encrypting data before transferring it could provide some security. Steganography is also introduced as an alternative way to secure communication by hiding the required data to be transferred into a media file and transferring the cover file itself. This ensures that data will be transmitted under a cover of an innocent media file. This paper introduces an idea of combining both cryptography and steganography to increase the level of security that is required to transfer data. To achieve this, two encryption algorithms, Pohlig-Hellman and One-Time-Pad, are used to encrypt data before hiding it. To hide encrypted data, Least Significant Bit (LSB) technique is used whereby audio wave file (.wav) is used as a cover file to hide data into it. This paper described the development of a software that uses above algorithms and technique to encrypt and hide data into audio wave files. The developed software allows the user to hide data into two different forms, file format and text format. In file format, the software allows the user to hide a file of any type into an audio wave file while, to hide the text format, it allows the user to write a text message before asking the software to encrypt and hide it. To be able to hide a larger data size, a compression algorithm, LZ77, is used to compress the text before encrypting and hiding it.
A Survey on Video Surveillance Using Hadoop

-Object detection and tracking are two fundamental tasks in multicamera surveillance. The most important technique of this multicamera related technique is to track and analyze objects within the images. The core technology of multicamera analysis is used in detecting, analyzing, and tracking the object’s motion. In addition, when the light’s color or direction changes, it is difficult to trace the object. Firstly use the block based algorithm for detecting the change scene in video if the scene is change is detected then video is stored on the server for further analysis. Once the video was stored on the server. Stored videos are dived in to chunks and send to different nodes for analysis using map reduce technology of Hadoop. for detecting object we apply the object tracking algorithm using a novel Bayesian Kalman filter with simplified Gaussian mixture (BKF-SGM). Using Hadoop we minimize the analysis time Finally draw the graphs in which show the no of objects to be detected and time to be required for analysis and stored analysis result into database for security purpose.
Identity Deception Detection and Security in Social Medium

— There has been a large increase in the usage of the Internet in the past few years. Identity deception has become an increasingly important issue in the social media environment. The case of blocked users initiating new accounts, often called sockpuppetry, is widely known. The past efforts to detect such users have been primarily based on verbal behaviour. Although these methods yield a high detection accuracy rate, they are computationally not very efficient for the social media environment. We present a detection method based on non-verbal behaviour and verbal behaviour for identity deception, which can be applied to many types of social media. We demonstrate that our proposed method results in high detection accuracy over previous methods proposed while being computationally efficient for the social media environment. We also demonstrate the potential of nonverbal behaviour data that exists in social media and how designers and developers can leverage such non-verbal information in detecting deception to safeguard their online communities. We create a social medium to demonstrate this.
An international overview of some pharmacist prescribing models

Issue 14 Summer 2008 This review aims to provide an overview of models of pharmacist prescribing outside and within the UK. Since pharmacist prescribing was pioneered in the US, most of the literature available originates within the US. Where little information was found in the literature, pharmacy societies were contacted to provide further information. Both the Australian and South African societies responded; however no information was obtained from Canada. Overall, little information is available from Canada and South Africa particularly since pharmacist prescribing in the latter case has been withdrawn. Table 1 accompanies the text below and aims to summarise different modes of pharmacist prescribing. Practice
Computer Aided Lung Cancer Detection and Tumor Staging in CT image using Image Processing

Lung cancer is one of the death threatening diseases among human beings. Early and accurate detection of lung cancer can increase the survival rate from lung cancer. Computed Tomography (CT) images are commonly used for detecting the lung cancer. Nowadays the lung cancer is staged according to the TNM staging method where T means Tumor, N means Nodule and M means Metastates. The existing lung cancer detection algorithms cannot stage cancer according to the TNM staging method. The proposed system can identify the T stage of the cancer accurately. The proposed system includes different stages such as preprocessing, segmentation, feature extraction, tumor detection and tumor stage identification. The proposed system promises better result than the existing systems, which would be beneficial for the radiologist for the accurate and early detection of cancer. The method has been tested on 200 slices of CT images of various stages of cancer obtained from Regional Cancer Centre Trivandrum and is found to give good results. The accuracy of the proposed method in this dataset is 94.4% General Terms Algorithms, Classification, Staging
Combined Bone Marrow Stem Cell Therapy

Ischemic heart disease (IHD) is a major cause of mortality and morbidity worldwide. It caused 1 of every 6 deaths in the United States in 2008 [1]. It is also the major contributor to heart failure (HF) which has become a burgeoning disease. According to American Heart Association (AHA) projections, HF prevalence will increase by 46% from 2012 to 2030 [2]. Patients with serious IHD usually, have events such as myocardial infarction (MI) that can result in irreparable loss of viable cardiac mass dramatically affecting their cardiac functions. Despite the important advances achieved in revascularization procedures and medical therapy, many of these patients are left with significant disability [3]. Considering the unclear efficacy of coronary artery bypass grafting (CABG) surgery for these patients and the shortage of donor hearts, a rationale to develop a novel stem cell-based regenerative therapy was provided. Numerous studies using animal models have documented that bone marrow stem cells (BMSC) transplantation in ischemic cardiomyopathy and acute MI is associated with reducing infarct scar size and improving cardiac functions [4]. These promising results of preclinical studies have led to several clinical trials evaluating the feasibility, safety, and efficacy of combining CABG with BMSC therapy in treating patients with serious IHD. Since the first trial of combined CABG and BMSC transplantation by Stamm et al. [5], several clinical trials that followed have been able to prove both safety and feasibility of this novel approach. However, the efficacy of this therapeutic approach remains controversial as larger, randomized, and multicenter trials are still needed to prove the beneficial effects of this approach [6-8].
SNR investigation for Visible Light Communication for Hospitals

This paper examines SNR characteristics of a hazardless alternative for data transfer using Visible Light communications (VLC) for radio frequencies (RF) restricted indoors areas such as aircrafts and health care systems. This communication system will be used for patients’ health monitoring in addition to providing the users with high data rate for multimedia contents applications. Since RF can be hazardous for patient’s health and could potentially damage the expensive instruments of the hospital, Visible light emerges victorious in communication battle. Room illumination and lux distribution simulations are created using Dialux evo and optical power distribution and power calculations are simulated in MATLAB. Further, the effects of three major factors in the wireless optical communication including Distance, Modulation and Data Rate are analyzed based on the SNR and BER of the communication channel.
In Information Filtering used of Maximum Matched Pattern based Model

-Many methods are used for information Filtering but in all previous process suffered from some advantages and disadvantages . As per aim of information filtering to generate user interest document by removing unwanted document . existing model I.e. pattern based model, term based model suffered with polysemy and synonymy ,noise generated by this model . All this model only consider that user interested in in only one topic but in situation user are interested in at time many topic in the filled on information filtering . we are focused on maximum matched pattern to represent topic . this pattern consider user interest in many topic rather than single topic . so, this pattern can be efficiently and effectively used for represent and rank the document.
The Relationship between Life Cycle and Cost of Equity on the Firms Listed In Tehran Stock Exchange (TSE)

The difference of cost of equity in different life cycles of firms from growth to decline can help the firms to provide finance and understand the effect of life cycle in costs of financial provision with the important consequences in strategic planning of firms. This research investigates the stages of life cycle of firms and costs of equity with data from 113 firms of The Firms Listed in Tehran Stock Exchange from 2003 to 2014. Testing the hypotheses, multiple regressions was used based on the combined data. The results showed that the cost of equity in the stages of decline increases and in growth and mature stage decreases than that in shake out stage. The findings of this research are consistent with life cycle theory of firms.
Emerging role of Stem cells of dental origin in dentistry -A Review

In recent years, the greatest findings show that stem cells have been used to treat several diseases. Studies conducted with stem cells highly interest the scientific field due to their ability in stimulating tissue regeneration and, as a consequence, presenting many therapeutic perspectives. Such facts enable stem cells to be used in different dental procedures of which aim is to recover the quality of patients’ oral health. Stem cells are primordial cells that can differentiate and regenerate failing cells in different parts of the body such as heart, bones, muscles and nervous system. Till date, five major human dental stem cells have been isolated and characterized: Dental Pulp Stem Cells (DPSCs), stem cells from exfoliated deciduous teeth (SHED), periodontal ligament stem cells (PDLSCs), stem cells from apical papilla (SCAP), and dental follicle progenitor cells (DFPCs). These post-natal populations possesses mesenchymal stem cell (MSC) qualities, with the capability for multiline age differentiation potential and self-renewal. The dental stem cells are derived and isolated from specialized tissue with potent capacities to differentiate into osteogenic, neurogenic, chondrogenic, adipogenic, odontogenic cells. For this review article we performed a search on PubMed, Medline Plus, Science Direct, google scholar, science direct etc for all English-language articles published in the last 10 years. We used the keywords were "adult stem cells", “dental stem cells, “dental stem cells banking”, “stem cells from human exfoliated deciduous teeth (SHED)”. The aim of this review is to give outline of the stem cell types being investigated in the dental field including their tissue sources, properties, differentiation potential, and assessment of their advantages for tissue engineering.
Exploring the Emergence of Social Networks in Collaborative Software Development

: Collaborative software development has been around as it has been made possible with groupware software. In such scenario, it is important to have coordination and planning among the team members involved in collaborative work.In such development tasks are divided into work items while sharing and tracking the work done. Exploration of tagging for resolving communication concerns in collaborative software development environment is the problem to be addressed. The existing system explores tagging for resolving communication concerns in collaborative software development environment is the problem to be addressed where different kinds of tags are used by various stakeholders to categorize and organize the work items. The tags that will be generated are used to support finding of different tasks, the articulation work, and the information exchange.different type of mechanisms like Implicit, explicit mechanisms have come up to manage the tag vocabulary. The Software that is used in the current day environment of collaborative software development focuses on individual development but not the group work.Most of the software that are used by the developers that are used in their daily work are tailored towards the work performed by an individual but hardly supports team work. The aim of the proposed system is that to explore which social networks emerge in the software development between the author of the work items, owners of the work items and tag authors . This will increase our basic understanding of the team dynamics in the software development cycle and may ultimately result in a better collaborative software tool support for a productive outcome of the product being developed . Thus the social network can provide you an insight of how the communication patterns plays a major role in preventing build failures in a system .
A New Approach to Find Predictor of Software Fault Using Association Rule Mining

-In this paper, we use a new method to find the best predictor of software fault using association rule mining. The method, first of all select all the association rules having confidence greater than 40% and support greater than 30% using Apriori algorithm. After that our aim is to select top ‘n’ association rules out of a pool of ‘k’ association rules based on heuristic analysis. The method ranks association rules giving weight to a larger set of parameters than used by standard methods. The role of correlation has been emphasized in this method which also tries to eliminate issues faced in incorporating correlation, support and confidence expressively into a single fitness function. A least square regression analysis has been done to establish the best rules in a set of “good” rules and allows for pruning of misleading rules that are often suggested by standard algorithms like the Apriori method. Furthermore, we investigate which OO-metrics are related to each other by best rules. The metrics on the antecedent part make sure the occurrence of the consequent part metrics. So, those OO-metrics which are present in the rule at antecedent part in most of the rules can be used as best predictor in software fault. It is found that applying this method results in both accurate and comprehensible rule sets as well as best predictor of fault.
Identifying indicators to evaluate the green performance of the units of department of water and Wastewater Company of Gazvin

In this paper, we identify indicators to evaluate the green performance of the units of department of water and wastewater of Gazvin using of the improved approach green balanced scorecard. So, the causal relationship between master perspectives and Priority between them is determined with DEMATEL method. To identify indicators, at first literature is reviewed and collected 34 indicators. Then, to interview with expert persons, 18 indicators related to the five perspectives of the balanced scorecard performance are selected.
Metamorphic Cryptography: A Technique for Providing Security on Video Files

: The science of securing a data by encryption is Cryptography whereas the method of hiding secret data inside cover data is Steganography, so that the secret’s very existence is concealed. The term Steganography describes the method of hiding cognitive content in another medium to avoid detection by the intruders. This paper introduces an approach wherein cryptography and steganography are combined to encrypt the data as well as to hide the encrypted data in cover medium so the fact that a data being sent is concealed. Combining both cryptography and steganography results to a new technique-Metamorphic Cryptography. The secret video is encrypted using AES algorithm and further encrypted video is embedded with cover video using LSB Algorithm, which results to double layer security to video files being transmitted over the network.
Formation of human Capital in the informal and its interaction in the Congolese economy

This reseach aims to highlight the formation of human capital in the informal sector as well as its collective and individual valorization in Congolese economic. The socioeconomic reproduction of formal education in the informal sector, with 70.1% of activities and 75% of jobs in the Congo, makes it possible to overcome market and state failures. The formation of human capital in informality passes through channels linked to social, physical and natural capital through interand extra-referential interaction, which contribute to the integration of populations, to the development of their capabilities and to the Consolidation of human capital in the determination of endogenous growth. The modeling of informal and formal interaction shows that the expected utility of the informal with an intensity of 72 seems more important than that of the formal one evaluated at 59. The two sectors are complementary and allow the populations to improve their property Be in one as in the other according to the capacities of each and the economic opportunities with a view to ensuring social stability and security.
Carbon Nanotubes- A Nanotechnolgy Based Drug Delivery System and its Recent Trends: A Review

CNTs are allotropes of carbon with a nanostructure which are cylindrical in its shape. There are single walled as well as double walled nanotubes. They have many biological and biomedical applications not because of its small size alone but to their remarkable optical, electric and magnetic properties . They are promising candidates for targeted drug delivery as they can detect and deliver drugs to neoplastic cells. They are a new alternative and efficient tool for transport and translocation of therapeutic molecules as they have easy access to cytoplasm and nucleus without immunogenic response or toxicity. CNT even serve as a very simple, rapid, sensitive and electrical sensor. The known uses of CNTs are briefly reviewed in this article.
The Influence of Corporate Governance And Firm’s Characteristics on The Extent of Compliance With Masb Standards Among Malaysian Listed Companies

This paper contributes to our understanding of compliance with mandatory accounting standards. Specifically, we examine the efficacy of agency related mechanisms on the degree of disclosure compliance with the Malaysian Accounting Standards Board (MASB) accounting standards. Using data drawn from a sample of 170 Malaysian companies listed on the Kuala Lumpur Stock Exchange (KLSE) in 2004, we show that although overall disclosure compliance is high (85.2% of the items of information being disclosed). We employ an ordinary least square (OLS) regression model to establish whether selected company-specific and corporate governance characteristics (proxying for agency-related mechanisms) are related to the degree of disclosure compliance. Our results indicate that only leverage is positively associated with the degree of compliance. The other variables consisting of board independence, audit committee independence, the existence of qualified accountant in the audit committee, CEO duality, the extent of outside blockholdersâ€™ ownership and firm size do not show any significant relationship with degree of compliance. These results have important implications for policy because they suggest that whilst agency-related mechanisms may motivate compliance with mandatory standards, full compliance may be unattainable without regulations.
Efficient Algorithms for Mining Closed Frequent Itemset and Generating Rare Association Rules from Uncertain Databases

---Dealing with uncertainty has gained increasing attention in the past few years in both static and streaming data management and mining. Data uncertainty is inherent in emerging applications such as location-based services, sensor monitoring systems and data integration. Specifically some privacy– preserving data stream mining applications like banking sectors operate on uncertain data and they need to mine frequent itemsets. There are many existing works on mining frequent itemsets from uncertain databases. They use the expected support of an itemset from an uncertain database to define whether it is frequent or not. Itemsets are considered frequent if its expected support exceeds the minimum support threshold. There are two main problems with this approach of mining frequent itemsets from uncertain databases. The first problem is that often too many frequent itemsets are generated many of which may prove to be irrelevant. The second is that only expected support is calculated to define frequent itemsets as being those whose expected support exceeds the minimum support. To overcome both these problems closed frequent itemset mining can be used. An itemset X is said to be closed, if and only if none of its superset has the same support. The mining process can be done by using Poisson Binomial Distribution. Closed frequent itemsets are extracted by an approximate mining algorithm which can effectively and accurately discover closed frequent itemsets in large uncertain databases. It can be extended to generate the rare association rules within the given support and confidence framework. In a practical scenario, there can be some itemsets which have significance and can provide useful knowledge but their support counts are relatively less. To extract the relationship among those itemsets having less frequency of occurrences, rare association rule mining came into existence.
PROPOSED MODEL FOR MOBILE MARKETING SYSTEM WITH PUSH NOTIFICATION

: These days, the quantity of information on the Internet is increasing day after day. With this amount of information becomes difficult to be monitored by users, since searching for specific information and follow this search may cost a lot of time and effort. Likewise, the use of smart phone is also increasing and make the information delivered through push notification to the users extremely easier. For this reason, This study introduces a new mobile marketplace application which provides follow search service to cater for these difficulties. The paper described the way to gather the requirements, develop Iraq Market-place (IQM) mobile application and provide follow search service by sending push notification to users. Finally, it tests the usability of the application. The paper found that the prototype has a positive result in both system satisfaction and usability with how easy using the system.