Reviewerly/exHarmony huggingface dataset:
Real Time Object Detection for Visually Impaired Person Using Tensor Flow Lite

Real Time Object Detection Using Tensor Flow Lite system has been developed to help visually impaired people for navigation and surrounding objects detection.This system is based on raspberry pi, a single board compute model and Tensor Flow lite framework.The algorithm developed is tested for detecting objects like a table, a chair, a TV, a laptop, a mouse, a cell phone, a bottle etc.This system is capable of detecting people as well as objects.The detection accuracy of 70% is achieved.The testing is done in varying light, background, and distance in indoors as well as outdoor scenarios.This system uses Google based sample quantized SSDLite-MobileNet-v2 object detection model, which is trained of the MSCOCO dataset and converted to run on TensorFlow Lite.The information regarding the detected object is converted into audio for guiding the visually challenged person
The Moderation Role of Transformational Leadership between Human Capital and Organizational Innovation in Abu Dhabi Government

Transformational leadership with human capital, and innovation are key success factors for modern organizations. Effective leadership style that encourages innovation among human resources will add competitve advantage to the organization. The aim of this study is to examine the moderation role of transformational leadership between human capital and organizational innovation. To achieve this aim, this study adopted quantitative and a survey by collecting data from employees of public sector in Abu Dhabi. Descriptive and inferential statistics was used to analyses the quantitative data. The result of this study shows transformational leadership moderates the association between human capital and organizational innovation. This study is one of the first, to the best of the researcher’s knowledge to test moderation tole of transformation leadership in UAE. Therefore, the author recommends the leaders in public organizations in UAE to focus on the factors associated with human capital in particular knowledge, skill, and attitude of employees in order to improve the level of innovation in their organization. The outcome of this study revealed that, the vision of transformation leader is very important to achieve competitive advantage for organizations in UAE through encouraging human capital towards innovation in work and business. Thus, it is highly recommended to assign transformational leaders in UAE organizations to enhance innovation within workplace as one of the main characteristics of transformation leaders is supporting human capital towards innovation.
A Cloud Storage Monitoring System using Deduplication and File Access Pattern

Cloud computing is important on current demanding business requirements and it has been emerged as unavoidable technology. The usage of memory storage for Cloud Computing IaaS Service is expanding exponentially every year. The cloud storages are used by the cloud user due to less storage cost compare with other storage methods. The replication of files provides high availability, reliability. It helps in attractive the data availability which reduces the overall access time of the files, but at the same time it occupies more storage space and yielded high storage cost. The cloud user holds storage space twice than which is needed. It is a dire need of a system to find unwanted files in the cloud and the frequency of file access in order to optimize the storage space in cloud. This paper proposed a system, Cloud Storage Monitoring (CSM) system, which is monitoring the IaaS storage usage and analyzes the file access patterns by various parameters to identify the frequency of access, size, future access prediction, replication of files in the cloud storage. This proposed system generates a ranking for each file which is also predicts future access pattern. The CSM system generates a dashboard to the user to reorganize or delete or archive the files to eliminate duplicate files in the cloud storage which can increase the availability of the files. The CSM system is experimented in the Cloud Sim environment, the results showed that the availability have been increased and the storage space is reduced as 10.91% lower than the normal system.
A Novel Fuzzy Based Assessment Method for Learning Outcomes

Outcome based education (OBE) is a recent development in student-centered teaching-learning model that emphases on measuring student performance through outcomes. Outcomes include knowledge, skills and attitudes suggested in Blooms taxonomy. The OBE approach encourages students to become active learners because it focusses on student attainment in comparison to teacher-centered learning approach. The level of the attainment of Course Outcomes (COs) is the indicator of the skill, knowledge and behavior that students acquired at the end of the course. In Outcome Based Education every activity performed in the class room is linked with the measurable course outcomes. In this paper, we present an effective fuzzy based approach to assess the attainment of outcomes by mapping every assessment activity performed in the class room with the Course Outcomes (CO) and eventually to Program Outcomes (PO). The attainments of outcomes by the students are also expressed as fuzzy memberships which can also be represented graphically. The entire work is based on the OBE implementation case study of Marian College Kuttikkanam, (MCK)
Quantum Algorithm to Construct Linear Approximation of an S-Box

Linear cryptanalysis, a Known-Plaintext Attack, for symmetric block cipher works by constructing linear approximations of the non-linear components of the cipher. The only component which introduces non-linearity in the symmetric block cipher is an S-box. Using classical computing algorithms, the best known solution to find a linear approximation of a non-linear function, in this case an S-box, requires queries to the S-box and time-complexity, where is the input size of the S-box and is the output size. In this paper, a quantum algorithm is presented which can produce best linear approximations of a non-linear S-box using only queries to S-box with time-complexity. The proposed algorithm shows a significant improvement over the classical algorithm. Correctness proof of the proposed quantum algorithm is presented along with an example.
Hardware and Software Complex for Restoring Motor Functions Based on Virtual Reality and Brain-Computer Interface

In this paper, we consider a hardware-software complex based on virtual reality and a non-invasive EEG neurocomputer interface, designed to restore motor functions of the limbs in patients with the consequences of severe acquired brain lesions through ideomotor training. The complex is a flexible system that allows to train any movements of both the upper and lower extremities in any virtual environment with varying degrees of immersiveness. The proposed method for assessing desynchronization of the sensorimotor rhythm during imagining movements and the developed algorithm for ideomotor training have been successfully tested on healthy volunteers.
A Decentralized Accountability Framework for Enhancing Secure Data Sharing Through ICM in Cloud

The Cloud substitutes a computing criterion where shared configurable resources are afforded as an on-demand service over the Internet. Moreover, the cloud environment provides resources to the users on the basis of services like SaaS, PaaS and IaaS. Generally, a cloud can be referred as private cloud or public cloud. When a Cloud Service Provider (CSP) imposes upon public cloud resources to compile their private cloud, the result is demonstrated as a virtual private cloud. Private or public, the imperious intent of cloud computing is to provide simplistic, reliable usage of various computing resources. One of the significant features of cloud is that the outsourced data are accessed through any anonymous machines over the Internet. On the other hand, it creates an issue that user’s fear of unknown access of data, which can become a major difficulty to the wide implementation of cloud. In this paper, a decentralized accountability framework is developed to monitor the actual usage and access of the data that is shared on cloud. For that, a logging mechanism that includes authentication for each user to access the data has also been provided. Moreover, some procedures for providing the data under the control of data owner includes Integrity Checking Mechanism (ICM) have also been developed. The overall process strengthens the security constraints over cloud. And the experimental results reveal that the approach affords secure and scalable data sharing with reduced memory utilization and processing time.
Assessing Threats and Vulnerable Attacks of Health Care Data in Cloud-Based Environment

What: Healthcare industries have been unified with the advent of cloud computing and Internet of Medical Things in recent past. How: As simplicity in access and transfer of medical reports increased, so does the impact of losing potential information. Adopting a cloud environment has eased the work of medical practitioners and provided world class medical attention to patients from remote corners of a nation. It has added the responsibility of cloud service providers to improvise the existing standards for protecting information in a virtual platform. A number of benefits not limitedto universal access, advice from renowned medical experts for deciding on diagnosis plan, alerting patients and hospitals in real timeand reducing the workload of labor are achieved by cloud environments. Hospital Information Systems (HIS) are the evolved data forms maintained manually in medical institutions and they are preferred in a cloud platform to improve interoperability. The information carried in such medical systems possesses critical information about patients that need to be protected over transmission between independent environments. This becomes a mandatory requirement for designing and implementing an access control mechanism to identify intention of users who enter into the environment. Relaxations in access control architectures will compromise the security of entire architecture and practice. Why: Intention - Demand Tree is proposed in this paper to limit the access rights of users based on their roles, requirements and permissions to monitor the usage of Health Information Systems. Investigative results illustrate that the risks of losing credible information has been limited and convenient than previous standards.
Analysis of Teaching Optimization of Chinese Language and Literature under the Background of Times of Internet Plus era

With the development of Chinese’s economy and the progress of the times, the Internet + era has already acquired a certain degree of scale, which has also had a greater impact on education and teaching. If education cannot keep pace with the times in reality, it may not be able to better meet the needs of cultivating talents and interpret the true essence of education. From the perspective of Chinese language and literature professional teaching, only by combining the Internet + era background and rationally optimizing the Chinese language and literature professional teaching can we better meet the actual needs and promote student progress. Based on this, this work analyzes the related issues of Chinese language and literature teaching optimization under the background of the Internet + era, hoping to be of benefit to reality.
Artificial Intelligent Nonlinear Auto-Regressive External Input Neural Network Modeling, Design and Control of a Sea Wave Electro-Mechanical Power Generating System

Utilization of the sustainable and renewable sea wave energy has recently received special attention by the virtue of being a free, clean and zero-carbon footprint power source.This paper presents a novel approach to model, design, analyze and control a sea wave electric power generating system using an artificial intelligent nonlinear auto regressive with external input neural networks (NARX-NN).Modeling design, and analysis of an electro-mechanical power-generating system using linear permanent magnet generator attached to a dual spring-mass-damper platforms is introduced.The purpose of this proposed generator is to convert sea and ocean wave kinetic energy into a useful electrical power generated as a result of the linear motion core through an electromagnetic stator.One of the direct applications of the sea wave generator is to install one or more units on shipboard to contribute to its power utility needs whether it is moving or floating.The dynamical stability and compensator control of the spring-mass damper generator platform is analyzed along with its associated electric power.Faraday's law based results show that the output induced voltage ranges from -60 to 60 volts (120 volts p-p).Moreover, artificial intelligent nonlinear auto-regressive neural networks are used to train, validate, and test the sea wave electric generator output.Two-layer NN are used to train the dynamical input-output relationship of the proposed system using one hidden layer that contains of 10 neurons.Two delays are used, one for motion input and one for voltage output.The NARX-NN training demonstrates that the network is being trained efficiently and tracks the actual sea wave electric generator output with a very low mean-squareerror performance response without the need to measure the variables.
A Bigdata Process for Practical Privacy-Preserving Utilizing k-Means Clustering

Now a day’s privacy preservation is the big issue on growing big data in various field such as medical, engineering and physical with the fast growing network. One of the most important challenges in handling big data is security issues. To overcome such security issues cryptographic concepts have been used in this paper to provide high security of big data’s with the low consumption of time for both encryption and decryption process. In this paper the proposed method is Indexed RSA (IRSA) which is developed with modified scheme. We offered a method to index the keyword before encrypting the file and based on the indexed keyword the search has been done. Finally the security analysis was carried out and the analysis showed that our modified scheme can meet the security requirement against brute force attack and SQL injection attack.
Medical Image Compression using Neural Network with HGAPSO Optimization

Lossy medical image compression has become increasingly attractive due to a drastic increase in the number of images used for diagnosis and treatment. The work focused on developing a feed-forward neural network for compression of medical images with optimization of weights using hybrid genetic and particle swarm (HGAPSO) optimization technique. The neural network can achieve a better compressed &amp; decompressed image only with the proper training and optimized weights. Training algorithms such as back-propagation algorithm (BPA) traps to local minima rather than the global one which degrades the quality of a reconstructed image. In this work, HGAPSO optimization is adopted to overcome the drawback of BPA. HGAPSO parameters are carefully chosen to have better exploitation &amp; exploration in the search area, which avoids the algorithm from trapping to the local minima. High-quality results of Genetic Algorithm (GA) obtained using selection, crossover and mutation can provide quality guidance for PSO which improves the results of the proposed system. The performance of the proposed work is evaluated on a raw medical image database based on PSNR, MSE, and CR. The experiment is simulated for 16-4-16 neural network architecture and a compression ratio of 75 % is achieved. The results obtained indicated that with proper training PSNR could be improved by 1.98 %.
Research on Matching Design Methods of Lightweight Hydraulic Oil Source for Legged Robot

摘要: 液压油源是足式机器人液压驱动系统的核心供能元件,将电能产生的机械能转化为油液的压力能,为驱动机器人各关节运动提供动力源。液压油源质量一般占据足式机器人整机质量超过20%,实现油源的轻量化,将有助于提升足式机器人的续航能力、机动性和承载能力。传统液压油源设计过程中更关注性能,在轻量化匹配设计方面还有待进一步完善。首先进行足式机器人轻量化液压油源的原理设计;其次将液压油源以功能为依据进行模块划分,分析液压油源各模块质量影响参数;针对质量与体积占比较大的电机泵进行匹配研究,针对蓄能器模块进行参数轻量化分析;针对集成阀块的轻量化设计,研究流道构建与元件排布原则;成功研发一种轻量化液压油源样机;最终形成了一种足式机器人轻量化液压油源匹配设计方法,有助于实现足式机器人液压驱动系统的轻量化。
Analisis Kepuasan Pengguna Electronic Health Record (EHR) dengan Menggunakan Metode Delone and Mclean di Unit Rekam Medis RSUPN dr. Cipto Mangunkusumo

The rapid development of technology requires humans to move forward to compensate for this. Ease thatis obtained along with technological advancements in carrying out all activities so that the time spentbecomes efficient and can reach wider society. RSUPN Dr. Cipto Mangunkusumo has followedtechnological developments by using EHR which is used to facilitate the process of service in the medicalrecord unit from the patient coming to the patient coming out. EHR at RSUPN Dr. Cipto Mangunkusumostill has shortcomings that is loading long enough 5 minutes for 1 file search that inhibits storage officersand agreement officers in providing patient medical records, other conditions are some menus related toreports are not appropriate and still cannot be accessed so officers must process data in advance to beused as a report and the unavailability of EHR learning modules specifically for new users. The study aimsto analyze the satisfaction of users of EHR at RSUPN Dr. Cipto Mangunkusumo using DeLone andMcLean methods with 6 indicators namely system quality, information quality, use, user satisfaction,individual impact and organizational impact. This type of research used qualitative research with 20respondents. Based on the analysis of user satisfaction it is known that the EHR facilitates the work ofofficers, the information provided is of high quality, the functions provided help the work of officers. It isexpected that the analysis of user satisfaction with EHR can be used as an effort to improve electronicmedical records by adding report print menus, updating servers and creating EHR learning modules.
A new dominant point detection technique for polygonal approximation of digital planar closed curves

On the visual perception, the real-world objects are the collection of irregular polygons. Representation and understanding the irregular polygon is an interesting and major task in various research areas. However, an approximation of the polygon is quite complex and challenging in different views. In this paper, a new approximation algorithm is proposed to represent the irregular polygon. Using centroid most of the weak points are suppressed and elimination of noise is integrated to produce better results. Iterative insertion of the dominant point is followed with suppression until the required approximation. The proposed method detects the dominant points which have a high impact on the shape and suppress the weak points. The obtained approximated polygon is with fewer vertices/points and retain the original shape with less approximation error. The experiments of the proposed algorithm are conducted using MPEG shape datasets to show its performance both in quantitative and qualitative aspect.
A Probe on Document Clustering Methodologies and Its Performance Metrics

Due to the huge growth of internet usage, large volume of information flow has also been increased, which leads to the problem of information congestion. In unsupervised learning, clustering is consider as most important problem. Big quality, high dimensionality and complicated semantics are the difficult issue of document clustering.it focus on the way of identifying a structure from an unlabeled data collection. A cluster is a method in which the data items are identified and grouped based on the resemblance between the objects from a dissimilar object set. Decision of a good cluster, can be demonstrated that there is no absolute “best” criterion independent of the final objective of the clustering. A good document clustering scheme’s primary objective is to minimize intra-cluster distance between papers while maximizing inter-cluster distance(using a suitable document distance measure).A distance measure(or, dually, measure of resemblance)is therefore at the core of document clustering. This assessment gives an implication about the different methods(Vector Space Model, Latent Sematic Indexing, Latent Dirichlet Allocation, Singular Value Decomposition, Doc2Vec Model, Graph model), distance measures(Euclidean Distance, Cosine Similarity, Jaccard Coefficient, Pearson Correlation Coefficient)and evaluation parameters of document clustering. This work is theoretical in nature and aims to corner the overall procedure of document clustering.
A Survey on Virtual Personal Assistant

Ongoing advancements in smart home automation and smart assistants are recently drawing in the intrigue and interest of customers and scientists. Discourse empowered remote helpers offer a wide assortment of system arranged administrations. The majority of those gadgets intensely depend on cloud-based administrations, in this manner transmitting conceivably delicate information to remote servers. To annihilation such issues probably the most exceptional procedures in computer vision, deep learning, speech generation and recognition, and artificial intelligence, into a virtual assistant architecture for smart home automation systems are utilized. One of the objectives of Artificial intelligence is the acknowledgment of normal exchange among people and machines. as of late, the exchange frameworks, otherwise called intuitive conversational frameworks are the quickest developing region in AI. Numerous organizations have utilized the discourse frameworks innovation to build up different sorts of Virtual Personal Assistants dependent on their applications and territories. VPAs are utilized to build the association among people and the machines by utilizing various innovations, for example, motion acknowledgment, picture/video recognition, speech recognition, the huge exchange furthermore, conversational information base, and the general learning base.
Virtuoso mapping for the Electrumpet, a hyperinstrument strategy

This paper introduces a new Electrumpet control system that affords for quick and easy access to all its electro-acoustic features. The new implementation uses virtuosic gestures learned on the acoustic trumpet for quick electronic control, showing its effectiveness by controlling an innovative interactive harmoniser. Seamless transition from the smooth but rigid, often uncommunicative sound of the harmoniser to a more noisy, open and chaotic sound world required the addition of extra features and scenarios. This prepares the instrument for multiple musical environments, including free improvised settings with large sonic diversity. The system should particularly interest virtuoso improvising electroacoustic musicians and hyperinstrument player/developers that combine many musical styles in their art and that look for inspiration to use existing virtuosity for electronic control.
MYRIOI

What would it be like to have a shared VR experience and to be present---to really feel presence together---in immersive worlds unimagined, from the atomic to the cosmic?