Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Quality Function Deployment To Improve Customer Satisfaction In Hotel Industry (A case study in a 5-star Hotel)

Satisfying customers is usually pursued by identifying their needs and translating their demands into design targets and thereby assessing the implementation of improvements on a continuous basis in order to attain the set targets. Quality function deployment is a planning tool used to fulfill customer expectations and in-depth evaluation of a product. The presented research aimed to get QFD model to improve service quality using customer needs priorities in a 5-star hotel of Indore. In the research customer satisfaction and importance degree of each need is investigated using survey method. Information was collected from the customers, employees and managers of the hotel to determine the factors affecting the customer satisfaction. After identifying the factors one questionnaire was given to the customers to rank their satisfaction received from the hotel. Selected sample size of the customers was 150. QFD team consisted of 5 managers and senior employees whose opinions were considered to determine the technical requirements to fulfill customer demands. Inter relationship matrix was constructed to evaluate the relationship between voice of customers and technical requirements. Co relationship matrix constructed to show the relationship among the technical requirements. Then customer competitive evaluation was done and finally competitive technical analysis was done to evaluate the degree of efforts by competitors to achieve customer satisfaction. Final results show that from view point of customers making bills correctly, Personal attention, Clean rooms, qualified food, Professional staff and affordable price are more important. Quality function deployment (QFD) is a comprehensive quality system used to achieve customer satisfaction and busi- ness growth in almost all types of industries like Hotel indus- try, Manufacturing industry, Ship building industry, Automo- bile industry, product design, product service, project man- agement and after sales service etc. Quality Function Deploy- ment has achieved remarkable popularity around the world in a wide variety of service sectors. QFD identify the flaws and bridge the gap between present level and standard level of Technical requirements then leads to invent and deploy better quality of services. QFD improves the number of satisfied customers in the business which leads to higher profit genera- tion and Business growth. Consequently brand name and goodwill of the particular industry improve among their com- petitors. In Akao's words, QFD "is a method for developing a de- sign quality aimed at satisfying the consumer and then trans- lating the consumer's demand into design targets and major quality assurance points to be used throughout the production phase. QFD is a way to assure the design quality while the product is still in the design stage. " As a very important side benefit he points out that, when appropriately applied, QFD has demonstrated the reduction of development time by one- half to one-third (3).
Comparison of gastrointestinal helminthes in dogs and awareness of zoonotic infection among dog owners in calabar, South Eastern Nigeria

A comprehensive study was carried out from October 2012 to November 2013 in dogs attending veterinary clinic and household dogs, to determine the prevalence status of gastrointestinal helminthes in both groups in order to intensify control measures of zoonotic helminthes in Calabar, South Eastern Nigeria. Prevalence of gastrointestinal helminthes eggs detected in dogs attending veterinary clinic and household dogs were Ancylostoma caninum 49.51% and 35.71%, Diplylidium caninum 36.0% and 28.57%, Toxocara canis 7.83% and 18.75%, Ascaris species 3.33%, and 10.71% Taenia canis 0.98% and 0.00%, Coccidia oocyst 1.57% and 0.00% and Trichuris vulpis 0.78% and 6.25% respectively. There was no statistical significant difference (P < 0.05) in helminth infections between age groups, sex and breed of dogs in 2013. The age group, breed, restricted and unrestricted movement of dogs in 2011-2012 significantly affected the prevalence of zoonotic parasites (P < 0.001), Dogs in 2011-2012 study group were found more likely to be parasitized and presented higher infection rates than household dogs in 2013. In view of the persistent A. caninum, T. canis and D. caninum infection of dogs in 2013, there is an urgent need to intensify control intervention in this community to reduce transmission of zoonotic helminths.
EFFICACY OF TWO DIFFERENT VESTIBULAR REHABILITATION APPROACHES FOR DIZZINESS IN VESTIBULAR DYSFUNCTION IN HEARING IMPAIRED CHILDREN

Introduction: Dizziness is one of the most common symptoms of vestibular dysfunction. Gaze stability exercises and Brandt Daroff exercises are two most commonly used vestibular rehabilitation approaches used for vestibular dysfunction. Vestibular dysfunction is common in hearing impaired children mainly, the reason being that hearing and vestibular impulses are both sent via the vestibule-cochlear nerve. This study mainly compares the efficacy of gaze stability exercises and BrandtDaroff exercises for dizziness in hearing impaired children with vestibular dysfunction. Objectives: 1. To study the effect of Gaze Stability exercises on dizziness in hearing impaired children with vestibular dysfunction 2. To study the effect of BrandtDaroff exercises on dizziness in hearing impaired children with vestibular dysfunction 3. To compare the effect of gaze stability exercises and Brandt – Daroff exercises on dizziness in hearing impaired children with vestibular dysfunction. Methodology: Thirty one hearing impaired children between the ages of 10 to 17 with positive symptoms of vestibular dysfunction in any two tests out of the following four tests Dix Hall Pike maneuver, Fukuda Step test, Roll’s test and Sharpened Romberg’s test were selected. Baseline evaluation for dizziness was done using Motion Sensitivity Quotient. The values obtained before and after intervention were recorded. Children were divided into two groups, Group A received Gaze Stability exercises and the Group B received BrandtDaroff exercises. The duration for treatment for both groups was 10 days. Results: There was significant improvement (p<0.001) in dizziness for Motion Sensitivity Quotient in both the groups. Both groups showed improvement in dizziness. However, the group which received Gaze Stability exercises showed more improvement than the BrandtDaroff exercise group for dizziness. Conclusion: The results of this study conclude that Gaze Stability exercises and BrandtDaroff exercises are effective in treating vestibular dysfunction in hearing impaired children and helps improve dizziness. Gaze Stability exercises clinically showed a better outcome than BrandtDaroff exercises for dizziness.
Moving Object Detection Using FPGA

: Visual surveillance has attracted much attention in the computer vision community due to its potential applications. The making of real time video surveillance systems requires fast and reliable algorithm for moving object detection. This paper an algorithm to detect moving objects in a scene acquired by a stationary camera. As algorithm has low calculation complexity, it is suitable for real time embedded system. Accuracy of this algorithm is tested by implementing this algorithm in MATLAB tool. Same algorithm is implemented by Micro blaze soft core processor. The algorithm is written in system C Language and tested in SPARTAN-3 XC3S200TQ-144 FPGA by interfacing a test circuit with the PC using the RS232 cable.
The Effect of Principal Leadership, Teacher Performance and Learning Facilities on Student Achievement in SMPN 1 Kepanjen Malang, Indonesia

The purpose of this study was to determine the effect of school principal leadership, teacher performance and learning facilities on student achievement in SMP Negeri 1 Kepanjen. The design of this research is causality design with a quantitative approach. The population and sample in this study were all teachers of SMP Negeri 1 Kepanjen, amounting to 50 people with the data collection techniques in the form of questionnaires and documentation of data. The technique of data analysis used in this study is multiple linear regression analysis techniques. The results of this study indicate that learning facilities have no effect on student achievement, leadership and teaching performance. Headmaster Significantly influences student achievement, and teacher performance has a dominant influence on student achievement.
An Efficient Video Surveillance System Using Video Based Face Recognition on Real World Data

— Video surveillance systems were used in many domains in the last few decades such as crime prevention, human behavior understanding, activity analysis, traffic monitoring etc. Video based face recognition is the process of detecting and recognizing the faces captured by a video camera. Face recognition in video has gained wide attention as it plays an important role in designing automatic surveillance systems. The main challenges in the video based face recognition are the limitation of the camera hardware, the arbitrary poses captured by the camera as the subject is non cooperative, changes in the resolutions due to different lighting conditions, noise and blurriness. Therefore a video based face recognition system must be robust to the changes in the illumination, scale, pose and expression. It must perform the detection and recognition rapidly in real time. In order to minimize the human interaction with the system, it has to be automated. A system capable of recognizing faces from video data in real time is proposed herewith. It is expected that the proposed system will be better than existing system in terms of accuracy, robustness, flexibility and compactness.
Challenges and Opportunities in Extending Cloud with Fog Computing

The present “cloud based internet of things (IoT) frameworks” are facing the challenges because of digital improvement from the “Artificial Intelligence, Tactile Internet, IoT, Virtual Reality, and 5G provisions”. These require “low latency access” that is normally attained by moving computation towards the edge of the network. One result for this is to decentralize management, applications, and information analytics into the system itself utilizing an associated and distributed approach and this model is named as “Fog Computing”. The IoT sensors used to generate the data management is the main issue faced when deploying an IoT framework. Whether they correctly integrated, then cloud platforms and fog platforms might support a wide range of “optimized services”. These services might be poised to take benefit of the complimentary profits in both structures. To make an integrated platform, the “cloud virtualization layer” should increase beyond the data center to reach the “fog nodes”. To enable this expansion, a network management that helps virtualization should spread to the edges. This manuscript portrays the idea of “Fog Computing” along with challenges and its opportunities
Recognition of Emotions by Facial Geometry Using a Capsule Neural Network

The article is devoted to the problem of improving the efficiency of neural network means of emotion recognition by the geometry of the human face. It is shown that one of the most significant drawbacks of modern neural network means of emotion recognition, which are used in General-purpose information systems, is the lack of recognition accuracy under the influence of characteristic interference. It is proposed to improve the accuracy of recognition through the use of capsule neural network model, which has increased adaptability to the analysis of noisy images. As a result of the research, a neural network model of the CapsNet type was developed, designed to recognize basic emotions taking into account such interference as face rotation. It is shown experimentally that in the analysis of undistorted images CapsNet slightly exceeds the accuracy of the classical convolutional neural network type LaNet, which is approximately equal to its resource intensity. The accuracy of CapsNet recognition of undistorted images is somewhat inferior to modern types of convolution networks, which have a much higher resource consumption compared to it. When detecting emotions on rotated images, the accuracy of CapsNet is comparable with the accuracy of modern types of convolution networks and significantly exceeds the accuracy of LaNet. Prospects for further research in the field of neural network recognition of emotions on the geometry of the face can be associated with the improvement of architectural solutions of the capsule neural network in the direction of reducing the number of training iterations while ensuring acceptable recognition accuracy.
An Different Similarity Measures with N-Grams For Text Documents Comparison

— Data analysis is a new, emerging field in research area and business. The huge numbers of documents are available in form of unstructured, semi-structured and structured data. Estimating similitude between writings is a critical errand for a few applications. In the existing many similarity algorithms has been proposed for text similarity calculation based on distance between documents in the text processing field. The increased attention has led to many of techniques for measuring semantic based document similarity algorithms. The document similarity application teachers or other users can easily search documents containing some specific terminology. In this paper propose a different type of document similarity calculation based on cosine similarity, Jaccard similarity and Euclidean distance with n-grams algorithms. The similarity metrics between documents can be defined in several ways depending on the representation of the documents. The experimental result compares that three similarity algorithms and finally evaluate which is best similarity measure.
A Time Efficient Task Allocation Algorithm

: Abstract - Grid computing is a form of distributed computing that involves sharing of resources that are heterogeneous and geographically distributed to solve various complex problems and develop large scale applications. In 1990’s, the term ‘Grid’ was originated to denote a proposed distributed computing architecture for advanced science and engineering. In today’s competitive environment the goals and objectives of the producers (also called resource owners) and consumers (also called end users) are different. Computational grid has been considered as the best paradigm for handling large scale systems that are distributed having geographically allocated resources. Task allocation algorithms are important in the research of network applications. In this paper we present an algorithm which reduces the average execution time and cost of the tasks. This method considers both time and cost constraints. The proposed algorithm is implemented with Gridsim toolkit which can simulate a decentralized module. The GridSim toolkit abstracts the behavior and features of complex fundamental grid elements such as grid tasks, grid resources and grid users. The algorithm provides services like resource management. For evaluation purpose a comparison of execution time and total cost of proposed algorithm and other similar algorithm is also given in this paper. Results support the proposed approach.
Teeth Bleaching: A Closer View

Tooth whitening nowadays is one of the most frequently requested cosmetic dental procedures by patients who want a “perfect white smile” [1]. Usually, vital tooth bleaching can be categorized generally as in-office (professionally administered), at-home (professionally dispensed) or over-the-counter (self-administered). Advantages of in-office dental bleaching over at home or over-the-counter bleaching techniques include professional control, avoidance of soft tissue exposure and material ingestion, reduced total treatment time, and the possibility of immediate results [2,3]. Most bleaching solutions contain hydrogen peroxide or carbamide peroxide as the active ingredient delivered through various carrier designs [4] that are applied with or without light activation. Proponents of light-activated bleaching claim that this procedure reduces total in-office bleaching time by energizing hydrogen peroxide through the use of various light sources [1,2,5]. The theoretical advantage is the ability of the light source to heat the hydrogen peroxide, thereby increasing the rate of decomposition of oxygen and accelerating the release of free radicals with higher kinetic energy, thus enhancing the rupture of stain-containing molecules Abstract Background: Tooth bleaching is a popular cosmetic procedure that can give someone a brighter smile and the appearance of youth by reducing discoloration on stained teeth. These stains occur due to the consumption of certain foods, drinks, and the use of certain medications. Discoloration may also results from traumatic injury or pulpal death. There are a variety of bleaching techniques which include: in-office procedures and home treatments. The results of both are generally successful, although a common side effect is an increase in tooth sensitivity.
Adaptive Control Mechanism for Snake with Intelligent Distributed Controller (SiD)

—The ability to comprehend and decide the trajectory defines the intelligence and the adaptability of the snake robot. The proper selection and distribution of the controllers helps every segment of the snake body to execute manifold gait and easy obstacle avoidance. Differential drive for DC motor connected at each wheel is generated by a DSP processor to control the segment following the path. This paper holds a thorough discussion on generation of differential drive signal with both, PWM and continuous pulse train control for right and left wheel and intelligent decision of trajectory by the SiD with the help of obstacle sensor and control pattern generator placed at the rear head of the designed adaptive snake robot. Phase differences between each segment of snake body and stability analysis of the controller part are also shown. Finally the compensation technique for designing the controller is justified for a given set of robot parameters in TMS320C6713 DSP platform.
An Efficient and Secured Framework for Mobile Cloud Computing

By and by days the market of PDA is creating at a quick. Everyone has a versatile, tablet, fablet (tablet with calling office). Flexible customer will accomplish 6.5 billion preceding the completion of 2012,6.9 billion preceding the completion of 2013.Together with a perilous improvement of the convenient applications and ascending of appropriated figuring thought, compact disseminated registering (MCC) has been familiar with be a potential development for adaptable organizations. MCC consolidates the disseminated figuring into the flexible condition and beats obstacles related to the execution (e.g., battery life, amassing, and information transmission), condition (e.g., heterogeneity, flexibility, and openness), and security (e.g., steadfastness and insurance) discussed in compact enlisting. This paper gives an information about adaptable disseminated figuring application security, issues . The issues, existing plans and procedures are discussed.
Privacy-Preserving Multi-keyword Ranked Search Over Encrypted Cloud Data

The innovation in cloud computing has encouraged the data owners to outsource their data managing system from local sites to profitable public cloud for excessive flexibility and profitable savings. But people can like full benefit of cloud computing, if we are able to report very real secrecy and security concerns that come with loading sensitive personal information. Allowing an encrypted cloud data search facility is of great significance. In view of the huge number of data users, documents in the cloud, it is important for the search facility to agree multi keywords query and arrange for result comparison ranking to meet the actual need of data recovery search and not regularly distinguish the search results. Related mechanisms on searchable encryption emphasis on single keyword search or Boolean keyword search, and often sort the search outcomes. In this system, we explain and solve the interesting problem of privacy preserving multi keywords ranked search over encrypted cloud data, and create a set of strict privacy necessities for such a safe cloud data application system to be effected in real. We first offer a basic idea for the multi keyword ranked search over encrypted cloud data (MRSE) based on effective comparison measure of coordinate matching, i.e. as many matches as possible, in order to capture the significance of data documents to the search query. Then we give two considerably developed multi keywords ranked search encryption schemes to reach many tough privacy requirements in two differ threat models.
Multi Label Document classification approach using Machine Learning Techniques: A Survey

: - Multi-label classification is an important machine learning task wherein one assigns a subset of candidate labels to an object. In this paper, we propose a new multi-label classification method based on Conditional Bernoulli Mixtures. Our proposed method has several attractive properties: it captures label dependencies; it reduces the multi-label problem to several standard binary and multi-class problems; it subsumes the classic independent binary prediction and power-set subset prediction methods as special cases; and it exhibits accuracy and/or computational complexity advantages over existing approaches. We demonstrate two implementations of our method using logistic regressions and gradient boosted trees, together with a simple training procedure based on Expectation Maximization. We further derive an efficient prediction procedure based on dynamic programming, thus avoiding the cost of examining an exponential number of potential label subsets. For the testing we will use and show the effectiveness of the proposed method against competitive alternatives on benchmark datasets with pdf. An increasing number of data mining tasks includes the analysis of complex and structured types of data and make use of expressive pattern languages. Most from these applications can't be solved using traditional data mining algorithms. This is the cause of main motivation for the multi-disciplinary field of Multi-Relational Data Mining (MRDM).
Pharmacognostic and phytochemical properties of Ficus carica Linn –An overview

Ficus carica grows in tropical and subtropical regions of India, it is used in indigenious system of medicine like ayurveda, siddha, unani and homoeopathy. Different biologically active compounds were isolated form this plant. The barks, leaves,fruits are considered to be very effective in various treatments, such as diabetes, skin diseases, ulcers, dysentry, diarrohoea, stomachache, piles . Latex is widely used for warts, skin ulcers and sores, and taken as a purgative and vermifuge. The present review is therefore, an effort to give a detailed survey of the literature on its Pharamacognosy, phytochemistry, and traditional properties.