Current progress in biosensors for organophosphorus pesticides based on enzyme functionalized nanostructures: a review

2018 ◽  
Vol 10 (46) ◽  
pp. 5468-5479 ◽  
Author(s):  
Sheng Xiong ◽  
Yaocheng Deng ◽  
Yaoyu Zhou ◽  
Daoxin Gong ◽  
Yuzhe Xu ◽  
...  
Keyword(s):  
Organophosphorus Pesticides ◽  
Research Area ◽  
Widespread Application ◽  
Significant Research

Organophosphorus pesticides analysis has become an increasingly significant research area due to their widespread application and contamination of the environment.

scholarly journals Synthesis, Characterization and Development of Energy Harvesting Techniques Incorporated with Antennas: A Review Study

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2772 ◽  
Author(s):  
Husam Hamid Ibrahim ◽  
Mandeep S. J. Singh ◽  
Samir Salem Al-Bawri ◽  
Mohammad Tariqul Islam
Keyword(s):  
Energy Harvesting ◽  
Research Area ◽  
Voltage Regulation ◽  
Input Power ◽  
Energy Sources ◽  
Promising Alternative ◽  
Significant Research ◽  
Rf Energy ◽  
Self Powered ◽  
The Military

The investigation into new sources of energy with the highest efficiency which are derived from existing energy sources is a significant research area and is attracting a great deal of interest. Radio frequency (RF) energy harvesting is a promising alternative for obtaining energy for wireless devices directly from RF energy sources in the environment. An overview of the energy harvesting concept will be discussed in detail in this paper. Energy harvesting is a very promising method for the development of self-powered electronics. Many applications, such as the Internet of Things (IoT), smart environments, the military or agricultural monitoring depend on the use of sensor networks which require a large variety of small and scattered devices. The low-power operation of such distributed devices requires wireless energy to be obtained from their surroundings in order to achieve safe, self-sufficient and maintenance-free systems. The energy harvesting circuit is known to be an interface between piezoelectric and electro-strictive loads. A modern view of circuitry for energy harvesting is based on power conditioning principles that also involve AC-to-DC conversion and voltage regulation. Throughout the field of energy conversion, energy harvesting circuits often impose electric boundaries for devices, which are important for maximizing the energy that is harvested. The power conversion efficiency (PCE) is described as the ratio between the rectifier’s output DC power and the antenna-based RF-input power (before its passage through the corresponding network).

scholarly journals The comparative study of text documents clustering algorithms

2015 ◽  
Vol 16 (SE) ◽  
pp. 133-138
Author(s):  
Mohammad Eiman Jamnezhad ◽  
Reza Fattahi
Keyword(s):  
Data Mining ◽  
Dna Analysis ◽  
Clustering Algorithms ◽  
Research Area ◽  
Large Set ◽  
Text Documents ◽  
Web Documents ◽  
Significant Research ◽  
The Comparative Study ◽  
F Measure

Clustering is one of the most significant research area in the field of data mining and considered as an important tool in the fast developing information explosion era.Clustering systems are used more and more often in text mining, especially in analyzing texts and to extracting knowledge they contain. Data are grouped into clusters in such a way that the data of the same group are similar and those in other groups are dissimilar. It aims to minimizing intra-class similarity and maximizing inter-class dissimilarity. Clustering is useful to obtain interesting patterns and structures from a large set of data. It can be applied in many areas, namely, DNA analysis, marketing studies, web documents, and classification. This paper aims to study and compare three text documents clustering, namely, k-means, k-medoids, and SOM through F-measure.

scholarly journals Optimal Deep Learning based Data Classification Model for Type-2 Diabetes Mellitus Diagnosis and Prediction System

2020 ◽  
Vol 9 (3) ◽  
pp. 1596-1604
Keyword(s):  
Deep Learning ◽  
Data Classification ◽  
Research Area ◽  
Classification Model ◽  
Prediction System ◽  
Pima Indians ◽  
Significant Research ◽  
Diabetes Mellitus Diagnosis ◽  
Simulation Results

In recent days, deep learning models become a significant research area because of its applicability in diverse domains. In this paper, we employ an optimal deep neural network (DNN) based model for classifying diabetes disease. The DNN is employed for diagnosing the patient diseases effectively with better performance. To further improve the classifier efficiency, multilayer perceptron (MLP) is employed to remove the misclassified instance in the dataset. Then, the processed data is again provided as input to the DNN based classification model. The use of MLP significantly helps to remove the misclassified instances. The presented optimal data classification model is experimented on the PIMA Indians Diabetes dataset which holds the medical details of 768 patients under the presence of 8 attributes for every record. The obtained simulation results verified the superior nature of the presented model over the compared methods.

scholarly journals Performance Analysis of Maximal Risk Evaluation Formulas for Spectrum-Based Fault Localization

2020 ◽  
Vol 10 (1) ◽  
pp. 398 ◽  
Author(s):  
Tingting Wu ◽  
Yunwei Dong ◽  
Man Fai Lau ◽  
Sebastian Ng ◽  
Tsong Yueh Chen ◽  
...  
Keyword(s):  
Risk Evaluation ◽  
Theoretical Study ◽  
Ordered Set ◽  
Fault Localization ◽  
Research Area ◽  
Theoretical Studies ◽  
Effectiveness Analysis ◽  
Significant Research ◽  
Program Spectrum ◽  
Better Than

The effectiveness analysis of risk evaluation formulas has become a significant research area in spectrum-based fault localization (SBFL). The risk evaluation formula is designed and widely used to evaluate the likelihood of a program spectrum to be faulty. There are numerous empirical and theoretical studies to investigate and compare the performance between sixty risk evaluation formulas. According to previous research, these sixty risk evaluation formulas together form a partially ordered set. Among them, nine formulas are maximal. These nine formulas can further be grouped into five maximal risk evaluation formula groups so that formulas in the same group have the same performance. Moreover, previous research showed that we cannot theoretically compare formulas across these five maximal formula groups. However, experimental data “suggests” that a maximal formula in one group could outperform another one (from a different group) more frequently, though not always. This inspired us to further investigate the performance between any two maximal formulas in different maximal formula groups. Our approach involves two major steps. First, we propose a new condition to compare between two different maximal formulas. Based on this new condition, we present five different scenarios under which a formula performs better than another. This is different from the condition suggested by the previous theoretical study. We performed an empirical study to compare different maximal formulas using our condition. Our results showed that among two maximal risk evaluation formulas, it is feasible to identify one that can outperform the others more frequently.

scholarly journals Artificial Intelligence Tools for Enhancing Customer Experience

2019 ◽  
Vol 8 (2S3) ◽  
pp. 700-706
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Academic Research ◽  
Customer Experience ◽  
Research Area ◽  
Customer Base ◽  
Significant Research ◽  
Narrative Literature ◽  
Narrative Literature Review ◽  
The Many

Customers are the key to any business and the major challenge for any established business is retaining an existing customer and acquiring a new customer. One of the many ways to reduce the churn rate and increase customer retention is to improve the customer experience. As businesses are growing, their customer base is also increasing. Each and every customer is different and needs different kind of motivators to engage with the business and hence we need to understand each and every customer uniquely. Artificial Intelligence tools can blend the gap between the business and the client, creating enormous information that can prompt further comprehension of the client’s preferences. Understanding these artificial intelligence tools and how these tools can assist organizations with retaining clients and help them give better involvement to their clients is significant. However, in academic research this significant research area stays under-focussed. Hence this study tries to address this gap by proposing a conceptual model for understanding how the Artificial Intelligence tools are can help in enhancing customer experience. The narrative literature review approach has been adopted for conceptualization of the model. The study provides implications to practitioners for designing and developing AI tools such that they enhance customer experience, to managers for designing the information technology strategy of their companies, to academicians as it helps explore new technologies in the marketing domain and to the society as it will help improve customer experience thereby leading to customer satisfaction.

scholarly journals A Weighted Frequent Item-Set Mining using WD-FIM Algorithm

2019 ◽  
Vol 8 (12) ◽  
pp. 4792-4796
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Research Area ◽  
Data Sets ◽  
Weight Factor ◽  
Smart Systems ◽  
Frequent Item ◽  
Significant Research ◽  
Downward Closure ◽  
The One

Smart systems are the one of the most significant inventions of our times. These systems rely on powerful information mining techniques to achieve intelligence in decision making. Frequent item set mining (FIM), has become one of the most significant research area of data mining. The information present in databases is in-general ambiguous and uncertain. In such databases, one should think of weighted FIM to discover item sets which are significant from end user’s perspective. Be that as it may, with introduction of weight-factor for FIM makes the weighted continuous item sets may not fulfil the descending conclusion property anymore. Subsequently, the pursuit space of successive item set can't be limited by descending conclusion property which prompts a poor time effectiveness. In this paper, we introduce two properties for FIM, first one is, weight judgment downward closure property (WD-FIM), it is for weighted FIM and the second one is existence property for its subsets. In view of above two properties, the WD-FIM calculation is proposed to limit the looking through space of the weighted regular item sets and improve the time effectiveness. In addition, the culmination and time productivity of WD-FIM calculation are examined hypothetically. At last, the exhibition of the proposed WD-FIM calculation is confirmed on both engineered and genuine data sets

Survey on Optimization Algorithms Used for Feature Selection Techniques in Web Page Classification

2019 ◽  
Vol 16 (2) ◽  
pp. 384-388 ◽  
Author(s):  
K. S. Ramanujam ◽  
K. David
Keyword(s):  
Machine Learning ◽  
Web Mining ◽  
Research Area ◽  
Web Pages ◽  
Web Page ◽  
Web Page Classification ◽  
Significant Research ◽  
Multiple Classifier ◽  
The Web ◽  
Page Classification

Web page classification refers to one of the significant research are in the web mining domain. Enormous quantity of data existing in the web demands the essential development of various effective and robust techniques to undergo web mining task that involves the process to categorizing the web page based on the data labels. It also includes various other tasks such as web crawling, analysis of web links and contextual advertising process. Existing machine learning and data mining techniques are being efficiently used for various web mining processes which include classification of web pages. Using of multiple classifier techniques are most promising research area while considering machine learning that works on the base of merging various classifiers with difference in base classifier and/or dataset distribution. With this several classification models are constructed that is highly robust in nature. This review paper, comparison has been done between FA, PSO, ACO, GA and IWT, to evaluate best fit algorithm for classifying web pages.

scholarly journals The Optimization of the Location of the Cargo in Three-Dimension Shelf: Employing the FP-Tree and the Artificial Fish Swarm Algorithms

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Shuiwang Zhang ◽  
Linping Fu ◽  
Rui Wang ◽  
Rong Chen
Keyword(s):  
Energy Consumption ◽  
Research Area ◽  
Three Dimension ◽  
Shelf Stability ◽  
Artificial Fish Swarm Algorithm ◽  
Location Allocation ◽  
Novel Approach ◽  
Swarm Algorithms ◽  
Significant Research ◽  
Artificial Fish Swarm

The allocation issues of the location of the cargo have affected the operational efficiency of retail e-commerce warehouses tremendously. Adjusting the cargo location with the change of the order and the operation of the warehouse is a significant research area. A novel approach employing the FP-Tree and the Artificial Fish Swarm Algorithms is proposed. Firstly, energy consumption and shelf stability are employed for the location-allocation. Secondly, the association rules among product items are obtained by the FP-Tree Algorithm to mine frequent list of items. Furthermore, the frequency and the weight of product items are taken into account to ensure the local stability of the shelf during data mining. Thirdly, another method of the location-allocation is obtained with the objectives of the energy consumption and the overall shelf stability along with the frequent items stored nearby that is conducted by the Artificial Fish Swarm Algorithm. Finally, the picking order distance is obtained through two methods of the location-allocation above. The performance and efficiency of the novel introduced method have been confirmed by running the experiment. The outcomes of the simulation suggest that the introduced method has a higher performance concerning criterion called the picking order distance.

Establishment of UN Cyber Peacekeeping Force: Prospects and Challenges

2019 ◽  
Author(s):  
Fahad Nabeel
Keyword(s):  
United Nations ◽  
Security Council ◽  
General Framework ◽  
Research Area ◽  
Peace Operations ◽  
Cyber Warfare ◽  
Un Peacekeeping ◽  
Un Security Council ◽  
Significant Research ◽  
Near Future

With the emergence of cyberspace as the fifth domain of warfare, the prospects of cyber conflicts have increased significantly. Around 300 state-sponsored cyber operations have been conducted since 2005. The future uncertainty of cyber-warfare has prompted calls for necessary measures to regulate the actions of states in cyberspace. In this regard, cyber-peacekeeping has also emerged as a significant research area to distinctively deal with the cyber component of future conflicts. Although, a number of challenges exist regarding materialization of full fledge cyber-peacekeeping force, it can be easily integrated into the current United Nations (UN) peacekeeping organizational structure. In legal terms, operationalization of cyber-peacekeeping force will depend on the mandate of peace operations approved by the UN Security Council (UNSC). This paper discusses the challenges confronting the creation of a cyber- peacekeeping force and also offers recommendations by presenting a general framework regarding how such a force can be operationalized. Despite the fact that a dedicated cyber-peacekeeping force seems a far sighted idea in present times, a distinct cyber unit can certainly be formed and integrated into UN peace operations in near future.

Numerical and Experimental Investigations of the Production Processes of Coextruded Al/Mg-Compounds and the Strength of the Interface

2009 ◽  
Vol 424 ◽  
pp. 129-135 ◽  
Author(s):  
Kai Kittner ◽  
Birgit Awiszus
Keyword(s):  
Extrusion Process ◽  
Research Area ◽  
Experimental Investigations ◽  
Wide Field ◽  
Widespread Application ◽  
Virtual Production ◽  
Use Of Resources ◽  
Production Processes ◽  
University Of Technology ◽  
Magnesium Compounds

Due to a changing environmental awareness and the improved use of resources, the application of light-weight materials, such as aluminium and magnesium, becomes increasingly important and partially substitutes the utilisation of conventional materials such as steel. However, a widespread application demands a better understanding of these materials. This concerns production processes of semi-finished products and the products itself. Coextruded aluminium-magnesium compounds are investigated in the subproject B3 (“Experimental and numerical investigations of the interface behavior of Al-Mg compounds”) which is part of the special research area 692 – HALS at the Chemnitz University of Technology. These compounds are characterized by a very good weight-strength-ratio and allow a wide field of application, for example in automotive industry. The compounds are manufactured in extrusion processes. The interface which is developed during the production is of special interest and the investigation of it is a shared aim of the Department of Experimental Mechanics and the Department of Virtual Production Processes. The two main tasks are the extrusion process optimisation and the microstructural, mechanical and thermal examination of the semi-finished product. The following paper gives an overview of the performed investigations in this subproject.

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