scholarly journals Database Private Security Jurisprudence: A Case Study using Oracle

2021 ◽  
Vol 13 (03) ◽  
pp. 01-21
Author(s):  
Madhuri N. Gedam ◽  
B. B. Meshram
Keyword(s):  
Security Policy ◽  
Real Life ◽  
Oracle Database ◽  
Fine Grained ◽  
Remote Server ◽  
Environment Variables ◽  
Database Encryption ◽  
Object Relational ◽  
Practical Guidelines

Oracle is one of the largest vendors and the best DBMS solution of Object Relational DBMS in the IT world. Oracle Database is one of the three market-leading database technologies, along with Microsoft SQL Server's Database and IBM's DB2. Hence in this paper, we have tried to answer the million-dollar question “What is user’s responsibility to harden the oracle database for its security?” This paper gives practical guidelines for hardening the oracle database, so that attacker will be prevented to get access into the database. The practical lookout for protecting TNS, Accessing Remote Server and Prevention, Accessing Files on Remote Server, Fetching Environment Variables, Privileges and Authorizations, Access Control, writing security policy, Database Encryption, Oracle Data Mask, Standard built in Auditing and Fine Grained Auditing (FGA) is illustrated with SQL syntax and executed with suitable real life examples and its output is tested and verified. This structured method acts as Data Invictus wall for the attacker and protect user’s database.

SonicFace

2021 ◽  
Vol 5 (4) ◽  
pp. 1-33
Author(s):  
Yang Gao ◽  
Yincheng Jin ◽  
Seokmin Choi ◽  
Jiyang Li ◽  
Junjie Pan ◽  
...  
Keyword(s):  
Facial Expressions ◽  
Microphone Array ◽  
Wearable Sensors ◽  
Real Life ◽  
Privacy Concerns ◽  
Fine Grained ◽  
Recognition Of Facial Expressions ◽  
Ubiquitous Sensing ◽  
Contact Free

Accurate recognition of facial expressions and emotional gestures is promising to understand the audience's feedback and engagement on the entertainment content. Existing methods are primarily based on various cameras or wearable sensors, which either raise privacy concerns or demand extra devices. To this aim, we propose a novel ubiquitous sensing system based on the commodity microphone array --- SonicFace, which provides an accessible, unobtrusive, contact-free, and privacy-preserving solution to monitor the user's emotional expressions continuously without playing hearable sound. SonicFace utilizes a pair of speaker and microphone array to recognize various fine-grained facial expressions and emotional hand gestures by emitted ultrasound and received echoes. Based on a set of experimental evaluations, the accuracy of recognizing 6 common facial expressions and 4 emotional gestures can reach around 80%. Besides, the extensive system evaluations with distinct configurations and an extended real-life case study have demonstrated the robustness and generalizability of the proposed SonicFace system.

Contamination Lab of Turin (CLabTo)

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Eleonora FIORE ◽  
Giuliano SANSONE ◽  
Chiara Lorenza REMONDINO ◽  
Paolo Marco TAMBORRINI
Keyword(s):  
University Students ◽  
Single Case ◽  
Real Life ◽  
Learning By Doing ◽  
Assessment Data ◽  
Entrepreneurial Skills ◽  
Fields Of Study ◽  
Education Levels ◽  
Positive Effect

Interest in offering Entrepreneurship Education (EE) to all kinds of university students is increasing. Therefore, universities are increasing the number of entrepreneurship courses intended for students from different fields of study and with different education levels. Through a single case study of the Contamination Lab of Turin (CLabTo), we suggest how EE may be taught to all kinds of university students. We have combined design methods with EE to create a practical-oriented entrepreneurship course which allows students to work in transdisciplinary teams through a learning-by-doing approach on real-life projects. Professors from different departments have been included to create a multidisciplinary environment. We have drawn on programme assessment data, including pre- and post-surveys. Overall, we have found a positive effect of the programme on the students’ entrepreneurial skills. However, when the data was broken down according to the students’ fields of study and education levels, mixed results emerged.

Participation and spatial transformation in large housing estates in Poland. Case study of Ursynów Północny

2018 ◽  
Vol 60 (1) ◽  
pp. 55-65
Author(s):  
Krystyna Ilmurzyńska
Keyword(s):  
Basic Assumption ◽  
Real Life ◽  
Business Environment ◽  
Spatial Transformation ◽  
Reciprocal Relationships ◽  
Spatial Transformations ◽  
Large Housing Estates ◽  
Existing Housing ◽  
Housing Estates

Abstract This article investigates the suitability of traditional and participatory planning approaches in managing the process of spatial development of existing housing estates, based on the case study of Warsaw’s Ursynów Północny district. The basic assumption of the article is that due to lack of government schemes targeted at the restructuring of large housing estates, it is the business environment that drives spatial transformations and through that shapes the development of participation. Consequently the article focuses on the reciprocal relationships between spatial transformations and participatory practices. Analysis of Ursynów Północny against the background of other estates indicates that it presents more endangered qualities than issues to be tackled. Therefore the article focuses on the potential of the housing estate and good practices which can be tracked throughout its lifetime. The paper focuses furthermore on real-life processes, addressing the issue of privatisation, development pressure, formal planning procedures and participatory budgeting. In the conclusion it attempts to interpret the existing spatial structure of the estate as a potential framework for a participatory approach.

Bleak Weather for Sun-Shine AG: A Case Study of Impairment of Assets

2014 ◽  
Vol 30 (2) ◽  
pp. 113-126 ◽  
Author(s):  
Dominic Detzen ◽  
Tobias Stork genannt Wersborg ◽  
Henning Zülch
Keyword(s):  
Real Life ◽  
Accounting Standards ◽  
Point Of View ◽  
Professional Judgment ◽  
Economic Point ◽  
Instructional Resource

ABSTRACT This case originates from a real-life business situation and illustrates the application of impairment tests in accordance with IFRS and U.S. GAAP. In the first part of the case study, students examine conceptual questions of impairment tests under IFRS and U.S. GAAP with respect to applicable accounting standards, definitions, value concepts, and frequency of application. In addition, the case encourages students to discuss the impairment regime from an economic point of view. The second part of the instructional resource continues to provide instructors with the flexibility of applying U.S. GAAP and/or IFRS when students are asked to test a long-lived asset for impairment and, if necessary, allocate any potential impairment. This latter part demonstrates that impairment tests require professional judgment that students are to exercise in the case.

Design and Real-life Deployment of a Smart Nanogrid: A Greek Case Study

2020 ◽  
Author(s):  
Apostolos C. Tsolakis ◽  
Angelina D. Bintoudi ◽  
Lampros Zyglakis ◽  
Stylianos Zikos ◽  
Christos Timplalexis ◽  
...  
Keyword(s):  
Real Life

scholarly journals Investigating the Potential of Network Optimization for a Constrained Object Detection Problem

2021 ◽  
Vol 7 (4) ◽  
pp. 64
Author(s):  
Tanguy Ophoff ◽  
Cédric Gullentops ◽  
Kristof Van Beeck ◽  
Toon Goedemé
Keyword(s):  
Computational Complexity ◽  
Object Detection ◽  
Network Optimization ◽  
Real Life ◽  
Optimization Techniques ◽  
Training Data ◽  
Single Shot ◽  
Standard Object ◽  
Number Of Classes

Object detection models are usually trained and evaluated on highly complicated, challenging academic datasets, which results in deep networks requiring lots of computations. However, a lot of operational use-cases consist of more constrained situations: they have a limited number of classes to be detected, less intra-class variance, less lighting and background variance, constrained or even fixed camera viewpoints, etc. In these cases, we hypothesize that smaller networks could be used without deteriorating the accuracy. However, there are multiple reasons why this does not happen in practice. Firstly, overparameterized networks tend to learn better, and secondly, transfer learning is usually used to reduce the necessary amount of training data. In this paper, we investigate how much we can reduce the computational complexity of a standard object detection network in such constrained object detection problems. As a case study, we focus on a well-known single-shot object detector, YoloV2, and combine three different techniques to reduce the computational complexity of the model without reducing its accuracy on our target dataset. To investigate the influence of the problem complexity, we compare two datasets: a prototypical academic (Pascal VOC) and a real-life operational (LWIR person detection) dataset. The three optimization steps we exploited are: swapping all the convolutions for depth-wise separable convolutions, perform pruning and use weight quantization. The results of our case study indeed substantiate our hypothesis that the more constrained a problem is, the more the network can be optimized. On the constrained operational dataset, combining these optimization techniques allowed us to reduce the computational complexity with a factor of 349, as compared to only a factor 9.8 on the academic dataset. When running a benchmark on an Nvidia Jetson AGX Xavier, our fastest model runs more than 15 times faster than the original YoloV2 model, whilst increasing the accuracy by 5% Average Precision (AP).

scholarly journals DOLARS, a Distributed On-Line Activity Recognition System by Means of Heterogeneous Sensors in Real-Life Deployments—A Case Study in the Smart Lab of The University of Almería

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 405
Author(s):  
Marcos Lupión ◽  
Javier Medina-Quero ◽  
Juan F. Sanjuan ◽  
Pilar M. Ortigosa
Keyword(s):  
Real Time ◽  
Activity Recognition ◽  
Real Life ◽  
Recognition System ◽  
Machine Learning Algorithms ◽  
Sensor Data ◽  
Heterogeneous Sensors ◽  
On Line ◽  
The University

Activity Recognition (AR) is an active research topic focused on detecting human actions and behaviours in smart environments. In this work, we present the on-line activity recognition platform DOLARS (Distributed On-line Activity Recognition System) where data from heterogeneous sensors are evaluated in real time, including binary, wearable and location sensors. Different descriptors and metrics from the heterogeneous sensor data are integrated in a common feature vector whose extraction is developed by a sliding window approach under real-time conditions. DOLARS provides a distributed architecture where: (i) stages for processing data in AR are deployed in distributed nodes, (ii) temporal cache modules compute metrics which aggregate sensor data for computing feature vectors in an efficient way; (iii) publish-subscribe models are integrated both to spread data from sensors and orchestrate the nodes (communication and replication) for computing AR and (iv) machine learning algorithms are used to classify and recognize the activities. A successful case study of daily activities recognition developed in the Smart Lab of The University of Almería (UAL) is presented in this paper. Results present an encouraging performance in recognition of sequences of activities and show the need for distributed architectures to achieve real time recognition.

scholarly journals Potential Impacts of Future Climate Change Scenarios on Ground Subsidence

Water ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 219 ◽  
Author(s):  
Antonio-Juan Collados-Lara ◽  
David Pulido-Velazquez ◽  
Rosa María Mateos ◽  
Pablo Ezquerro
Keyword(s):  
Climate Change ◽  
Land Subsidence ◽  
Ground Subsidence ◽  
Lower Percentage ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Fine Grained ◽  
Fine Grained Material ◽  
The Impact

In this work, we developed a new method to assess the impact of climate change (CC) scenarios on land subsidence related to groundwater level depletion in detrital aquifers. The main goal of this work was to propose a parsimonious approach that could be applied for any case study. We also evaluated the methodology in a case study, the Vega de Granada aquifer (southern Spain). Historical subsidence rates were estimated using remote sensing techniques (differential interferometric synthetic aperture radar, DInSAR). Local CC scenarios were generated by applying a bias correction approach. An equifeasible ensemble of the generated projections from different climatic models was also proposed. A simple water balance approach was applied to assess CC impacts on lumped global drawdowns due to future potential rainfall recharge and pumping. CC impacts were propagated to drawdowns within piezometers by applying the global delta change observed with the lumped assessment. Regression models were employed to estimate the impacts of these drawdowns in terms of land subsidence, as well as to analyze the influence of the fine-grained material in the aquifer. The results showed that a more linear behavior was observed for the cases with lower percentage of fine-grained material. The mean increase of the maximum subsidence rates in the considered wells for the future horizon (2016–2045) and the Representative Concentration Pathway (RCP) scenario 8.5 was 54%. The main advantage of the proposed method is its applicability in cases with limited information. It is also appropriate for the study of wide areas to identify potential hot spots where more exhaustive analyses should be performed. The method will allow sustainable adaptation strategies in vulnerable areas during drought-critical periods to be assessed.

scholarly journals Research on feeder network design: a case study of feeder service for the port of Kotka

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Yisong Lin ◽  
Xuefeng Wang ◽  
Hao Hu ◽  
Hui Zhao
Keyword(s):  
Control System ◽  
Numerical Experiment ◽  
Network Design ◽  
Evaluation System ◽  
Real Life ◽  
Objective Evaluation ◽  
Multi Objective Optimization ◽  
Real Life Data ◽  
The Mathematical Model

Abstract By exemplifying the feeder service for the port of Kotka, this study proposed a multi-objective optimization model for feeder network design. Innovative for difference from the single-objective evaluation system, the objective of feeder network design was proposed to include single allocation cost, intra-Europe cargo revenue, equipment balance, sailing cycle, allocation utilization, service route competitiveness, and stability. A three-stage control system was presented, and numerical experiment based on container liner’s real life data was conducted to verify the mathematical model and the control system. The numerical experiment revealed that the three-stage control system is effective and practical, and the research ideas had been applicable with satisfactory effect.

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