Miracle-dz/UniFAR-FTUs huggingface dataset:
Monte-Carlo based simulations of photothermal response of nerve tissue for laser wavelengths of 1455 nm, 1490 nm, 1550 nm

Electrical nerve stimulation (ENS) technique has been tested on nerve mapping devices, which are intraoperative diagnostic tools. However, these technologies suffer from general limitations. Optical Nerve Stimulation (ONS) has been a developing technique as a potential alternative to ENS. This new technique using infrared laser radiation can offer many advantages, including a non-contact stimulation mode, improved spatial selectivity, and elimination of stimulation artifacts. However, the stimulation parameters, including laser power, beam diameter, and surface scanning speed, provide a large variable matrix that must be optimized for consistent and reliable nerve mapping using ONS. This preliminary study explores a computational tool to provide a guiding map for determining optimal stimulation parameters for laser-scanning subsurface ONS. It consisted of three parts: (1) Monte Carlo simulations for generating laser energy distribution in the tissue sample, (2) laser-scanning model by moving the heat source at the surface, and (3) thermal transfer simulations to calculate the tissue temperature. The tool was tested on laser wavelengths of 1455 nm, 1490 nm, and 1550 nm. According to the results of calculations, nerve temperature maps were generated for those wavelengths. Each map demonstrated specific optimal parameter values to reach the nerve activation temperature. Additionally, the results of laser power densities at the lowest scanning speeds of 0.4 mm/s in x-axis and 0.5 mm/s in yaxis showed proximate results with our previous study about ONS on rat model. With further development, this tool may hold promise in the development of an intraoperative optical stimulus device for surgical applications.
A NOTE ON EXPLICIT THREE-DERIVATIVE RUNGE-KUTTA METHODS (ThDRK)

Recently, the Runge-Kutta methods, obtained via Taylor’s expansion is exist in the literature. In this study, we have derived explicit methods for problems of the form y′ = f(y) including second and third derivatives , by considering available Two-Derivative Runge-Kutta methods (TDRK). The methods use one evaluation of first derivative, one evaluation of second derivative and many evaluations of third derivative per step. The methods can be named as ThreeDerivative Runge-Kutta methods, ThDRK shortly. We present methods with stages up to three and order up to seven. Comparisons is made with other some existing methods on some standard problems. The stability region of the methods are given.
Immunohistochemical expression of Ki-67 in gall bladder carcinoma

Introduction: Gall bladder carcinoma accounts for 0.3-0.7% of all cancers and has a peak incidence among women aged 70 and 79 years. Recently many molecular markers like Ki-67, cyclin D1, MUC1 and p53 with prognostic impact on GBC have been described. Ki-67 is a proliferative marker which is expressed in all active phases of the cell cycle and it can be detected in the nucleus of tumour cells indicating its proliferative activity. The aim of this study is to evaluate the expression of Ki-67 in carcinoma of gall bladder by immunohistochemistry and to correlate the mean Ki-67 labelling index with the various histological grades of gallbladder carcinoma. Materials and Methods: All the histopathologically proven cases of gall bladder malignancy from July 2014 to June 2017 (n=44) were examined for Ki-67 expression immunohistochemically.Ki-67 labelling index was calculated. ANOVA test and independent ‘t’ test were applied to see correlation of Ki-67 expression with various grades of gall bladder carcinoma. Results: The Ki-67 labelling index was minimum in well-differentiated adenocarcinoma of gall bladder and maximum in poorly differentiated adenocarcinoma of gall bladder. The p value amongst these groups was found to be statistically significantly different. Conclusion: 88.64% of Gall bladder carcinoma was positive for Ki-67 and the Ki-67 labelling index increased significantly as the histological grade increased.
Comparability of Conventional Network and Neural Network Techniques for Image Enhancement Methods

------------------------------------------------------------------- ABSTRACT ----------------------------------------------------------------- Image enhancement improves the quality (clarity) of images for human viewing. Neural Networks have been developed rapidly during the recent few years and it is extensively applied for the enhancement of the digital image. The primary purpose of this study is to propose a comparison between conventional network and the Neural Network. The evaluation criterion is based upon edge detection, face detection For this proposed comparison, the evaluation criteria parameters are implements and analyzes for both neural and conventional network. Experiments on images are implemented to confirm the validity of the proposed analysis. One of the purpose of the study was to identify the main factor affecting the image and result are obtained were validated with existing techniques. This paper focuses on two popular features of image enhancement that are face detection and edge detection. The number of experiments is done on the number of images which shows that in the edge detection of image used the counting of white pixels which are more than the counting of white pixels in conventional networks. The face detection method counts the single face and multiple faces in the image.
PRINCIPALS' PERSPECTIVES ON THE PERFORMANCE OF PRE-SERVICE ENGLISH TEACHERS AT QASSIM, SAUDI ARABIA

With the increased concerns about Saudi students' results in multiple ESL/EFL standardized tests, educational districts in Saudi Arabia are now, more than ever, working hard to ensure that students are receiving the best education and teaching practices possible. While research has well documented the importance of effective teachers for students' learning, it states that it is now essential for schools to identify them (Herrera, 2010). Schools' principals are by large considered important predictive individuals to identify the effective teachers, novice and veterans, from those who are not. The current study investigates the principals' assessment of the performance of pre-service English teachers in Saudi Arabia based on Danielson's first dimension of FFT framework, planning and preparation. Mixedmethods approached, namely classroom observations and semi-structure interviews, were used to collect the data. Twenty three pre-service English teachers who were observed, and three schools principals who had been as the school principal for three years or more were interviewed. The finding of the study indicates that, 1) the pre service English teachers obtained a relatively high scores on the performance with the mean score was 84.09 (sd = 11.71); 2) the highest mastery was in the component E, Designing Students Assessment, with a mean 19.6 and sd = 2.44; 3) all the principals interviewed stressed the importance of self-efficacy for the pre service teachers, and 4) all principals shared a common thought by gradually emerging them in schools' responsibilities is the key to pave the teaching road for them.
Segmentation of Lung Nodule Using Image Processing Techniques from CT Images

------------------------------------------------------------------- ABSTRACT ------------------------------------------------------------- Lung cancer is the most prevalent and hazardous disease in the world having highest mortality rate among all other types of cancers like breast, liver, brain, skin etc. There is a great need to detect it in its early stage to provide a great chance of survival to the patient. It is possible only when lung nodules will be automatically segmented through image modalities. The main aim of this study is to overcome the above problem from CT images. The medical image segmentation with accuracy is a prognostic factor in the diagnosis of lung cancer. Manual segmentation of lung nodules form CT image is a challenging & crucial task. A semi-automated segmentation method is proposed to segment lung nodules from CT images which can successfully segment a nodule provided that the parameters are set properly.
A Cognitive Approach to Localized Image Search from the multimedia websites

: This generation has potential usage of social networking web sites, like face book and picasa, filkcr, YouTube allow users to tag photos, add comment, share the data. The large-scale net genies meta-data not only facilitate users in using and arranging multimedia content, but provide useful statics to improve content searching and management. Personalized search serves as one of such examples where the web search experience is improved by generating the returned list according to the modified user search intents. In this paper, we exploit the social annotations and propose a novel framework simultaneously considering the user and query relevance to learn to personalized image search. The basic premise is to embed the user preference and query-related search intent into user-specific topic spaces. Since the users’ original annotation is too sparse for topic modeling, we need to enrich users’ annotation pool before user-specific topic spaces construction. The proposed framework contains two components: 1) A Ranking based Multi-correlation Tensor Factorization model is proposed to perform annotation prediction, which is considered as users’ potential annotations for the images; 2) We introduce User-specific Topic Modeling to map the query relevance and user preference into the same user-specific topic space. For performance evaluation, two resources involved with users’ social activities are employed. Experiments on a large-scale Flickr dataset demonstrate the effectiveness of the proposed method.
A machine learning Approach for Maximizing Ride Shared Route Using IABFM Framework

: Over the concept of Ride-Sharing (RS) is very important valuables of environment because it saving energy and destroy the traffic pressure or traffic congestion. In this paper, we propose a new model for maximizing the shared route. In this model, where each driver or rider requests, that driver shares a ride with a rider, and shared route percentage increased expectation rate of the driver. Shared route percentage is nothing but the radio of the shared route‟s distance to the driver‟s total distance. It proposes the best-first algorithm that it selected the drivers with high probability to be in the top-k results. Then, the drivers are already pruned, but that cannot be in the top-k results. The system introduces a new novel Active_seg model to gathering, defining and representing the uncertainty of trajectory. The best-first method implement efficiently compute the top-k drivers for a rider. The existing Ride-Sharing Framework is difficult in handling problem of Join-based and Search based RS large Spatial Network datasets. It is very important challenged to achieve Maximizing Shared Route efficiency, to address this problem the system introduces an IABFM Ride-Sharing Framework.
Diversification of Nigerian Economy; A Panacea of Economic Recession. How Economic Diversification Can Be Integrated Into Sustainable Development

Recently, a remarkably recession engulfed the Nigerian state, the causes as well as sense of threat and uncertainty induced by the crisis have been differently interpreted, particularly from the macro-economic, leadership and strategic stand points. This study would focus on the impact of the economic recession on Nigeria in the socio-economic context, its concepts, causes and implications for the wider economy and the need for economic diversification and how it can be integrated into sustainable development. The study will use multiple regression analysis of time series data on selected macroeconomic variables in two econometric models. With the research findings; policy makers and regulatory agencies/bodies in the country such as Central Bank of Nigeria (CBN), Office of the Economic adviser and the Ministry of finance, would be well equipped to guard and guide against future occurrence, the study will synthesize technical information on the concepts and theories of economic diversification to enhance the understanding of the subject which could be very significant to students, researchers and scholars who are interested in developing further studies on the subject matter. Keywords— Recession, Inflation, diversification, food security, unemployment, poverty, export, imports, Industrialization, Manufacturing and Economic Recovery, gross domestic product,
A Combinational approach towards Multioriented Videotext Detection and Recognition

— Video text detection, extraction and recognition is an important prerequisite for the high-level semantic information understanding and content-based Video analysis tasks.Inevitable computer vision based loopholes such as cluttered background, inconsistent colors and arbitrary orientations pose interesting challenges in video text content extraction and understanding.A Novel approach towards detection and recognition of Multioriented Videotext is proposed in the present paper. Initially fast and effective Morphological procedures are applied for text region detection followed by Maxi-mally Stable Extremal Regions(MSERs) extraction procedure.MSER detected Text regions are further verified by Covariance Matrix feature extraction based method.Also a novel Watershed and Threshold based videotext binarization method for Video text recognition is proposed.Operability and accuracy of proposed system are evaluated on the standard datasets results which successfully confirm the efficiency of the proposed method.
Maritime trap-jaw ants (Hymenoptera, Formicidae, Ponerinae) of the Indo-Australian region – redescription of Odontomachus malignus Smith and description of a related new species from Singapore, including first descriptions of males

Abstract The maritime trap-jaw ant Odontomachus malignus Smith, 1859 is thought to be widespread throughout islands in the Indo-Pacific and parts of the Oriental realm. Because of its unique nesting preference for harsh littoral habitat and distinct morphology, O. malignus has usually been assumed to consist of only one species. We, however, describe a new species similar to O. malignus found in the mangroves of Singapore, Southeast Asia – Odontomachus litoralissp. nov. We find strong evidence of both species existing in (near) sympatry, and also distinct morphological differences between O. malignus and the new species. Additional complementary DNA evidence in the form of COI barcodes (313 bp) supporting putative species identification and delimitation is provided. Defining morphological characteristics for the O. malignus species group (nested within the larger O. infandus clade) are given in detail for the first time. The worker and queen castes of the new species are described; a redescription of the worker caste of O. malignus, based on specimens from Singapore and the Philippines in addition to the holotype, is also given. The males of both species are also described for the first time, including male genitalia. A preliminary key to most known species of the O. infandus group based on the worker caste is provided.
Distributed cloud Storage Image Control Reliability and Obliging Provable Data and Confirmation

— Data integrity is very important while storing few data in multi-cloud. Distributed cloud storage is the method of storing the data in obliging provable data for the reliability confirmation. this paper proposes the integrity of data while storing distribute cloud this technique improve can improves overall enterprise performance by avoiding vender lock-in for customers to minimize the computation cost this technique also reduces cost while computation is reflected in performance analysis.
Species Richness of Avifauna in Four Long Term Ecological Research Sites in Mindanao, Philippines

The Philippines has diverse avifauna especially on the island of Mindanao which has the highest percentage of forest cover. This study was conducted to assess the species richness and distribution of avian species in four Long Term Ecological Research (LTER) sites in Mindanao, namely: Mts. Apo, Kitanglad, Hamiguitan, and Malindang. Mist netting for a total of 857net days and point surveys (62hours)were carried out inside and along the 1-ha permanent plot to document bird species in the area. Sixty-five bird species belonging to 30 families and 49 genera were recorded. Of the four forest ecosystems, Mt. Apo showed the highest species richness (38 species), endemism (58.33%), and species diversity while Mt. Hamiguitan showed the least species richness (20 species). Pachycephalaphilippinensis was the only species recorded in all LTER sites. Percentage similarity of the species composition across LTER sites was below 55% indicating that each of the four LTER sites showcased a unique avian composition.
Visibility Restoration of Degraded Images Captured in Realistic Environments

: AVisibility restoration is very important in the field of computer vision applications such as outdoor object recognition systems, obstacle detection systems, video surveillance systems, and intelligent transportation systems. The visibility of outdoor images is often degraded due to the presence of haze, fog, sandstorms, and so on.Haze causes trouble tomany computer graphics/vision applications as it reduces the visibility of the scene. Air light and attenuation are two basic phenomena of haze. Air light enhances the whiteness in scene and on the other hand attenuation reduces the contrast. The colour and contrast of the scene is recovered by haze removal techniques. Poor visibility caused by atmospheric phenomena causes failure in computer vision applications. In order to solve this problem, visibility restoration (VR) techniques have been developed. This paper proposes a novel VR method that uses a combination of three major modules: a depth estimation (DE) module; a color analysis (CA) module; and a Visibility Restoration (VR) module. The proposed DE module takes advantage of the median ﬁlter technique and adopts our adaptive gamma correction tec hnique. The CA module is based on the gray world assumption and analyses the color characteristics of the input hazy image. The VR module uses the adjusted transmission map and the color-correlated information torepair the color distortion in variable scenes captured during inclement weather conditions. This is one of the best method while comparing with the previous state of the art methods.
Robust output feedback control of positive switched systems with time-varying delays

www.ijarcet. org 1374  Abstract—This paper investigates the robust output feedback control of positive switched systems with time-varying delays. Firstly, by using the Lyapunov-Krasovskii functional and ADT approach, sufficient conditions are obtained to guarantee that the corresponding system is robustly exponentially stable. Then a static output feedback controller is designed and some sufficient conditions are obtained to ensure that the closed-loop system is robustly exponentially stable. Such conditions can be easily solved by linear programming. Finally, a numerical example is provided to show the effectiveness of the proposed method.
A Framework for Secure Sharing of Hierarchical Data in Cloud

— Data Security is an important aspect in Cloud storage. Nowadays, there are numerous algorithms that ensure the security for the data placed in the Cloud storage.One way of modeling our data is to structure it in a hierarchical format and then upload it to the Cloud. This represent a less tedious way of organization and searching of our data becomes less cumbersome. Hierarchical structures can be used to model a plenty of situations like Role Based Access Control (RBAC) model, patient’s medical records. We may want to share the data with others. This paper presents a study of various key management schemes used in hierarchical data models which focuses on key sharing. Also it provides a comparative study of different key management schemes. The key management schemes are divided into three sections: Key Derivation Schemes for predefined hierarchy, Compact-Sized key using symmetric encryption, and Key Management Schemes using Identity Based Encryption.
SIDE CHANNEL ATTACK USING POWER ANALYSIS

The ingenuity of the software involved in the theoretical basis of cryptographic algorithms is indeed phenomenally strong. But they can be broken only through the weakness of their implementations. This weakness of the theoretical base is manipulated to explore into the various dimensions and possibilities of Side Channel Attack (SCA). This in fact forms the core of the methodology employed in the study of SCA as described in this paper. This paper explores into the possibilities and uses of various Side Channel Attacks meticulously. SCA exploits the unintended information leakage from the implementation to extract the secret key. The information elicited via side channel attack may include power consumed by the system, timing parameters, electromagnetic information etc. The specific aim of this paper is directed towards eliciting side channel information through power analysis attack. The process also invariably makes use of a powerful Boolean technique, which utilises the Boolean form of extracted variables. This Boolean reasoning technique will try for all possible combinations and find out a true assignment, if there exist any. This system can be extended to attack cryptographic software implementations. SCA substantially reduces the complexity of performing cryptanalysis and defines it in a new light.
HEART DISEASE PREDICTION SYSTEM USING ANOVA, PCA AND SVM CLASSIFICATION

— Heart disease is a term that assigns to a large number of healthcare conditions related to heart. These medical conditions describe the unexpected health conditions that directly control the heart and all its parts. The main objective of this research is to develop an efficient heart disease prediction system using feature extraction and SVM classifier that can be used to predict the occurrence of heart disease. The heart disease prediction system helps the physician and healthcare professionals as a tool for heart disease diagnosis. To protect the life of a patient from heart diseases there have to be quick and efficient prediction technique such as PCA with SVM classification technique is to be followed. This technique is widely used to validate the accuracy of medical data. By providing the effective treatments, it also helps to reduce the treatment costs.
A comprehensive study on prolonged air pollution exposure and Cardio-Respiratory mortality

In the recent era of third generation scientific world’s population across the multicity urban environments, it has been found that the concentrations of ambient air pollution have been associated with a range of adverse health effects, particularly mortality and morbidity due to cardiovascular and respiratory diseases. In this review, we summarize the evidence from epidemiological studies on longterm exposure to fine and coarse particles, nitrogen dioxide (NO2) and elemental carbon on mortality from all-causes, cardiovascular disease and respiratory disease. We also sought to the findings on potentially susceptible subgroups across studies. After extensive study as well as review of multiples research articles from different scientific journals associated with medical health care and environmental sciences we could identify several remarkable studies through a search in the databases of Medline and Scopus and previous reviews until July, 2016 and performed a meta-analysis if more than five studies were available for the same exposure metric.