Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel Distance Metric for Touch less Footprint Based Identification Technique

In this fast-paced technology-driven today's era, biometrics is not the new buzzword in the information security domain. Biometrics uses any physiological or/ and behavioral attribute/s of an individual for personal identification and/or verification. In biometrics, so many traits, like a fingerprint, face, palm, retina, iris, ECG, gait, voice, and signature, etc., have been used from ages to uniquely identify a human being. Biometrics based on Footprints is the latest practice for personal identification. Like fingerprints and palmprints, footprints of individuals carry uniqueness; hence can be used in biometrics for personal recognition. This work investigates the powerfulness of footprints by extracting texture and shape features using Principal Component Analysis (PCA) method based upon Eigenfeet and introduces a new distance metric during the matching phase. Experimental results show that the new distance metric shows better results in comparison to the Euclidean, Manhattan and Mahalanobis distances.
Assorted Sentiment Model for Publically Available Page of Facebook

ecommerce industries expose public page in the social network site (Facebook, twitter etc) for the intention of improving of business strategy. They extract public mood about the social network page in the forms of total likes, the total share of the page and sentiment of all comments to the social network page similar way celebrities expose public page in the social network sites for the intention of improving its fame. We have developed an assorted model for publicly available page of Facebook. This assorted model is the combination of data extractor model, language convertor and cleaned model, and sentiment analyzer model. Our data extractor model extract comments on all the posts of publicly expose Facebook page in the less span of time. Language convertor and cleaned model would work for conversion of text written in different Indian language to the English language and after that English written text would be cleaned through cleaned model. Language convertor is made after implementing CILTEL model. CILTEL model converts comments written in the Indian languages in the English language. Cleaning model will clean all the comments of all the posts on the Facebook page. Finally, sentiment extraction model will extract sentiments of all the comments of the Facebook page. We have implemented classification using three machine learning algorithm, namely naïve bayes algorithm, perceptron algorithm and rocchio algorithm for checking the performance of our sentiment analysis model. Our assorted sentiment analysis model is beneficial to users like marketing industry, election parties and celebrities
International Journal of Innovative Technology and Exploring Engineering (IJITEE)

In video analytics, out of all the known challenges, (a) adverse unconstrained environmental condition resulting low illumination/ contrast and (b) mutual motion between camera assembly and object of interest are definitely the major ones. The challenges become multi-fold when the scene of interest gets impacted by both the aforementioned simultaneously. The first part of the current work has proposed a novel hierarchical scene categorization methodology based on selected spatiotemporal features. The procedure of determination of feature hierarchy and the detailed description of step by step methodology of the same has been provided along with comprehensive results. The second part of the current work proposes a novel method of processing rainy videos in different mutual motion scenarios by dynamic bilateral filtering and deep auto-encoder on time-sliced video frames. The proposed idea exploited the strength of range-domain filtering of bilateral filter, saliency extraction of deep auto-encoder and spatiotemporal model of time-slicing. Quantitative results of extensive experiments showed the effectiveness of our proposed algorithm in different degree of environmental degradation. The proposal of the scene categorization not only classifies the scenes based on mutual motion between camera assembly and object of interest, but it also triggers and influences the algorithm of deraining dynamically by offering required modulation.
Citizens’ Positive Safety Perceptions in Public Spaces

Urban environments can be stressful places and as a majority of people now tend to live in cities, innovative ways to tackle citizens’ in securities and fears are needed. Smart decisions in planning safe urban places should be guided by the question of how citizens’ perceived safety in cities can be improved. In this paper, using an exploratory approach of visual and narrative methods, we develop a framework that captures aspects, which lead to safety perceptions as positive experience. It contains three main themes that support safety perceptions in public spaces: place, perceived social presence and perceived information. We argue that safety perceptions are always a combination of multiple dimensions and aspects, and although safety is often divided into physical and mental safety, participants do refer to both of these interchangeably. Overall, our study contributes to the recent discussions about alternative approaches to safety, offers conceptual insights into the nature of safety as a positive experience and uncovers the broad spectrum of safety understandings as defined by citizens.
Building Graph for Events and Time in Natural Language Text

Events and time are two major key terms in natural language processing due to the various event-oriented tasks these are become an essential terms in information extraction. In natural language processing and information extraction or retrieval event and time leads to several applications like text summaries, documents summaries, and question answering systems. In this paper, we present events-time graph as a new way of construction for event-time based information from text. In this event-time graph nodes are events, whereas edges represent the temporal and co-reference relations between events. In many of the previous researches of natural language processing mainly individually focused on extraction tasks and in domain-specific way but in this work we present extraction and representation of the relationship between events- time by representing with event time graph construction. Our overall system construction is in three-step process that performs event extraction, time extraction, and representing relation extraction. Each step is at a performance level comparable with the state of the art. We present Event extraction on MUC data corpus annotated with events mentions on which we train and evaluate our model. Next, we present time extraction the model of times tested for several news articles from Wikipedia corpus. Next is to represent event time relation by representation by next constructing event time graphs. Finally, we evaluate the overall quality of event graphs with the evaluation metrics and conclude the observations of the entire work
Energy Efficient Target Tracking Method for Multi-Sensory scheduling in Wireless Sensor Networks

Data collection utilizing wireless sensors networks (WSNs) has been utilized for surveillance, monitoring environment, animal etc. Target tracking of maneuvering objects is an essential need of modern life. Nonetheless, because of diverse nature of sensor and complex environment, sensors measurement errors need to be minimized considering diverse motion states in process of tracking (sensing) operation. Enhancing network lifetime (i.e., reducing energy dissipation of sensor nodes) and improving tracking quality are major concern of target tracking using WSN. Form improving network energy efficiency, multi-sensory target tracking method has been modelled using Kalman Filter (KF) by existing target tracking method. The KF based model are affected due to presence of noise or missing data. For overcoming research issues this paper present an H-infinity filter (HF) to evaluate fusion for maneuvering target tracking in WSN. Further, to minimize the estimation errors and reduces/controlling the effects of outliers fuzzy H-infinity (FHF) filter for target tracking WSN is presented. Experiment outcome shows proposed HF and FHF fusion model attain better performance than existing KF based method for clustered based WSN in terms of positional and velocity root mean square error and energy dissipation.
Scene Recognition using Significant Feature Detection Technique

Scene classification is basic problem in robotics and computer vision application. In Scene classification focused on complete view or event that contains both low and high level features. The main purpose of scene classification is to diminish the semantic gap in between social life & computer system. The main issue in scene classification is recognizing tall buildings, mountain, open country and inside city. We applied combination algorithms of feature extraction on trained datasets. Our proposed algorithm is hybrid combination of SIFT+ HOG named as HFCNN. As compare with the existing CNN architecture, HFCNN perform betters with high accuracy rate. Accuracy rate for proposed architecture is more than 96% as calculated with better time consumption and cost effective.
Program Designing the Improvement of Excavator’s Maintenance Team Competencies (Case Study in a Sandstone Mine Company PT XYZ)

The heavy equipment maintenance system cannot be separated from the problems of Human Resources (HR). Some literature has defined HR as a success factor for the successful implementation of maintenance systems. The Asset Maintenance Division as an organization which responsible to maintain the Company's assets routinely, including the Doosan S500’s 50-tonne class excavator. But in fact, excavators that are currently still operated often breakdown and its physical condition are in a bad condition. From the observation of 9 (nine) units excavators, the Key Performance Indicator (KPI) target was still not achieved, especially on the items Mean Time To Repair (MTTR) and Mean Time Between Failure (MTBF). Mechanic’s technical competencies needed in achieving KPI are divided into four sub competencies: Maintenance, Repair & trouble shooting, Remove & install and Overhaul. This study aims: analyzing mechanic’s competencies against company‘s standards, analyzing the influence of mechanic’s competencies on achieving KPI targets, providing recommendations on the influence of mechanic’s competencies for achieving KPI targets. The primary data used in the study were obtained through interviews and the questionnaires as well as secondary data obtained from various literatures, research results and supporting books. The method of processing and analyzing data uses the method of gap analysis and the Non-Parametric Statistics (Multiple Regression). The results of the gap analysis are known that there are still gaps in the actual competence of employees with competency standards set by the company. Factors that cause the competency gap are generally known because of a lack of understanding of the basic skills required, mastery of work techniques and consistency in applying work quality standards. Recommendations from this study as an effort to improve the skills and knowledge of mechanics to improve work effectiveness that affects MTTR and the quality of work that affects MTBF so that the KPI are consistently achieved. Keywords―Preventive Maintenance, Downtime, Physical Availability, MTTR, MTBF, Gap Analysis.
Urea Ammonium Nitrate Solution Treated with Inhibitor Technology: Effects on Ammonia Emission Reduction, Wheat Yield, and Inorganic N in Soil

Urea is the most used fertilizer nitrogen (N), and is often applied as urea ammonium nitrate (UAN), which may be an ammonia (NH3) emission source after application. This study examined whether the addition of urease inhibitors reduced NH3 emission, and, in combination with nitrification inhibitors, enhanced fertilizer N crop uptake. In three experiments, NH3 emission was measured from plots (100 m2) to which UAN was added with and without inhibitors. In March and May, the plots were covered with Triticum aestivum L. , Sheriff (var), and in July, the soil was bare. The inhibitor mixed with urea was N-(n-butyl) thiophosphoric triamide (NBPT) and a mixture of NBPT and the new nitrification inhibitor DMPSA (3,4-Dimethylpyrazole succinic acid). Ammonia emissions were negligible from all plots after the first application of UAN due to the wet and cold weather while an average of 7% of applied UAN was emitted after application of UAN in April, where no significant effect of additives was observed. The harvest yield was low due to drought from May till August. Yield was highest when UAN was mixed with NBPT and lowest for untreated UAN. The highest emission from the bare plots was obtained from untreated UAN (17% of N), in contrast to 11% of N from the plots with added UAN + NBPT (not significant) and 7% from the plots with added UAN + NBPT + DMPSA (significantly different). Under the conditions of the current study, urease inhibitors reduce NH3 emissions in periods where the risk of emission is high, and the combination of urease and nitrification inhibitors increased yields.
Inflammatory Bowel Disease in Japan-Is It Similar to or Different from Westerns?-

Ulcerative colitis and Crohn's disease, the most common types of inflammatory bowel disease, are idiopathic, intractable disease characterized by chronic inflammation in the intestine. In recent years, studies elucidating the clinical characteristics of these diseases and basic researches have suggested that the diseases are induced by the immunological abnormalities through the involvement of environmental factors with their predisposition. In Japan, significant progress of basic and epidemiological researches has been developed for these diseases and the clinical guidelines have been established. However, no fundamental treatment for these diseases has been established yet. The current number of patients in Japan continues to increase, with at least 180,000 patients suffering from ulcerative colitis and 40,000 suffering from Crohn's disease. Thus, further studies are required to understand these diseases and improve medical treatments.
Bochdalek hernias associated with intrathoracic kidney: A case report and systematic review of outcomes including renal function

Background: An intrathoracic kidney is a very rare form of ectopic kidney. Though increasingly recognized in the literature, impact on renal function is less well described. We report the case of a 67-year-old South Asian gentleman who presented with intrathoracic kidney and chronic kidney disease. We carried out a systematic review of the available literature on intrathoracic kidney, in order to characterize the typical clinical features, and describe likely clinical course and possible renal and extra-renal complications associated with this form of ectopia. Materials and methods: A structured search using PubMed identified all relevant published case reports from 1988 to 2018, with search restricted to papers in English, and to adult cases only (> 18 years of age). 124 records were identified, and after screening for eligibility, 34 case reports were analyzed. Results: Median age was 53.5 years, with no gender predominance. 68% (27/34) of cases were symptomatic. 29% (10/34) had a significant complication associated with their intrathoracic kidney, with 3 cases with either documented chronic or end-stage kidney disease. 26% (9/34) required surgical intervention. Conclusion: Though previously regarded as a benign entity, results from our systematic review, bearing in mind susceptibility to publication bias, suggests an appreciable risk of symptoms, complications, and in the minority a risk to kidney function. We recommend close biochemical and imaging surveillance of affected patients, with low threshold for intervention in those with renovascular stenosis, reflux, or hydronephrosis.
A Case of Frequently Relapsing Minimal-Change Nephrotic Syndrome with Steroid-Induced Psychiatric Syndrome Treated by Low-Dose, Short-Term Steroid Therapy in Combination with Cyclosporine

Adults with minimal-change nephrotic syndrome (MCNS) generally receive oral prednisolone (PSL) at an initial dosage of 1.0 mg/kg/day for a minimum of 4 weeks, with 80% of patients achieving clinical remission. However, relapses are frequent, necessitating repeated treatment with high-dose PSL. Long-term treatment with high-dose steroids increases the risk of steroid toxicities, such as diabetes mellitus, gastric complications, infections, osteoporosis, and steroid-induced psychiatric syndrome (SIPS), which may compromise the patient’s quality of life. Strategies are therefore needed to reduce the dosage and duration of steroid therapy for frequently relapsing MCNS (FRNS). Here, we suggest a new combination therapy of low-dose and short-term steroid with cyclosporine (CsA). We encountered an adult patient who developed recurrence of FRNS with depression arising from SIPS and was treated using low-dose, short-term PSL combined with CsA. He was successfully treated with PSL at an initial dosage of 0.3 mg/kg/day (20 mg/day) for just 2 weeks combined with CsA, allowing earlier induction of complete remission. We then promptly reduced the dose of PSL to below a physiological dosage (5 mg/day) over 3 weeks without relapse after episodes of SIPS and quickly resolved psychiatric symptoms. CsA in combination with PSL can reduce the initial dosage of PSL, shorten the time to remission, and easily maintain clinical remission. This protocol appears clinically useful and potentially applicable as a future treatment strategy for FRNS troubled by SIPS.
The miR-372-ZBTB7A Oncogenic Axis Suppresses TRAIL-R2 Associated Drug Sensitivity in Oral Carcinoma

miR-372 has been shown a potent oncogenic miRNA in the pathogenesis of oral squamous cell carcinoma (OSCC). The zinc finger and BTB domain containing 7A protein (ZBTB7A) is a transcriptional regulator that is involved in a great diversity of physiological and oncogenic regulation. However, the modulation of ZBTB7A in OSCC remains unclear. Tissue analysis identifies a reverse correlation in expression between miR-372 and ZBTB7A in OSCC tumors. When OSCC cells have stable knockdown of ZBTB7A, their oncogenic potential and drug resistance is increased. By way of contrast, such an increase is attenuated by expression of ZBTB7A. Screening and validation confirms that ZBTB7A is able to modulate expression of the death receptors TRAIL-R1, TRAIL-R2, Fas and p53 phosphorylated at serine-15. In addition, ZBTB7A transactivates TRAIL-R2, which sensitizes cells to cisplatin-induced apoptosis. The ZBTB7A-TRAIL-R2 cascade is involved in both the extrinsic and intrinsic cisplatin-induced pathways of apoptosis. Database analysis indicates that the expression level of and the copy status of ZBTB7A and TRAIL-R2 are important survival predictors for head and neck cancers. Collectively, this study indicates the importance of the miR-372-ZBTB7A-TRAIL-R2 axis in mediating OSCC pathogenesis and in controlling OSCC drug resistance. Therefore, silencing miR-372 and/or upregulating ZBTB7A would seem to be promising strategies for enhancing the sensitivity of OSCC to cisplatin therapy.
Lessons Learned From Failures and Success Stories of HIV Breakthroughs: Are We Getting Closer to an HIV Cure?

There is a continuous search for an HIV cure as the success of ART in blocking HIV replication and the role of CD4+ T cells in HIV pathogenesis and immunity do not entirely eradicate HIV. The Berlin patient, who is virus-free, serves as the best model for a ‘sterilizing cure’ and many experts are trying to mimic this approach in other patients. Although failures were reported among Boston and Essen patients, the setbacks have provided valuable lessons to strengthen cure strategies. Following the Berlin patient, two more patients known as London and Düsseldorf patients might be the second and third person to be cured of HIV. In all the cases, the patients underwent chemotherapy regimen due to malignancy and hematopoietic stem cell transplantation (HSCT) which required matching donors for CCR5Δ32 mutation – an approach that may not always be feasible. The emergence of newer technologies, such as long-acting slow-effective release ART (LASER ART) and CRISPR/Cas9 could potentially overcome the barriers due to HIV latency and persistency and eliminate the need for CCR5Δ32 mutation donor. Appreciating the failure and success stories learned from these HIV breakthroughs would provide some insight for future HIV eradication and cure strategies.
Project Westdrive: Unity City With Self-Driving Cars and Pedestrians for Virtual Reality Studies

Virtual environments will deeply alter the way we conduct scientific studies on human behavior. Possible applications range from spatial navigation over addressing moral dilemmas in a more natural manner to therapeutic applications for affective disorders. The decisive factor for this broad range of applications is that virtual reality (VR) is able to combine a well-controlled experimental environment together with the ecological validity of the immersion of test subjects. Until now, however, programming such an environment in Unity® requires profound knowledge of C# programming, 3D design, and computer graphics. In order to give interested research groups access to a realistic VR environment which can easily adapt to the varying needs of experiments, we developed a large, open source, scriptable, and modular VR city. It covers an area of 230 hectare, up to 150 self-driving vehicles and 655 active and passive pedestrians and thousands of nature assets to make it both highly dynamic and realistic. Furthermore, the repository presented here contains a stand-alone City AI toolkit for creating avatars and customizing cars. Finally, the package contains code to easily set up VR studies. All main functions are integrated into the graphical user interface of the Unity® Editor to ease the use of the embedded functionalities. In summary, the project named Westdrive is developed to enable research groups to access a state-of-the-art VR environment that is easily adapted to specific needs and allows focus on the respective research question.
Application of the Nano-Drug Delivery System in Treatment of Cardiovascular Diseases

Cardiovascular diseases (CVDs) have become a serious threat to human life and health. Though many drugs acting via different mechanism of action are available in the market as conventional formulations for the treatment of CVDs, they are still far from satisfactory due to poor water solubility, low biological efficacy, non-targeting, and drug resistance. Nano-drug delivery systems (NDDSs) provide a new drug delivery method for the treatment of CVDs with the development of nanotechnology, demonstrating great advantages in solving the above problems. Nevertheless, there are some problems about NDDSs need to be addressed, such as cytotoxicity. In this review, the types and targeting strategies of NDDSs were summarized, and the new research progress in the diagnosis and therapy of CVDs in recent years was reviewed. Future prospective for nano-carriers in drug delivery for CVDs includes gene therapy, in order to provide more ideas for the improvement of cardiovascular drugs. In addition, its safety was also discussed in the review.