A Middleware Architecture for Supporting Adaptable Replication of Enterprise Application Data

2006 ◽  
pp. 29-43 ◽  
Author(s):  
J. E. Armendáriz ◽  
H. Decker ◽  
F. D. Muñoz-Escoí ◽  
L. Irún-Briz ◽  
R. de Juan-Marín
Keyword(s):  
Enterprise Application ◽  
Application Data

Sistem Pendukung Keputusan Untuk Penerimaan Calon Karyawan Outsourcing Dengan Metode Simple Additive Weighting (SAW)

2018 ◽  
Vol 4 (1) ◽  
pp. 29-39 ◽  
Author(s):  
Otto Fajarianto ◽  
Ardiyanto S. Widodo ◽  
Muhammad Iqbal Hanafri ◽  
Arianto ◽  
Arif Muchlisin Fauzi
Keyword(s):  
Decision Making ◽  
Supporting System ◽  
Performance Result ◽  
Decision Supporting ◽  
Decision Supporting System ◽  
Application Data ◽  
Simple Additive Weighting

Decision making on hiring outsourcing employment candidate which still manually has impact on stucking application data, obstacle on placement process and unreal in scoring criteria. In deciding decision needs specific criteria for scoring performance result. This criterion can be standardized in deciding advisable candidate. The purpose of this study is building a decision supporting system, help the company in giving score and choosing new employment. SAW method uses for calculating criteria value base on the highest degree and calculating is taken from normalisation process. The data will be inputted in decision supporting system, and then it will be calculated base on specific criteria. The score from each criterion will be calculated to get the highest score. The result will give recommendation for company in deciding advisable candidate.

scholarly journals Design and Application Data-Based Employee Eat Barcode Scanner

2021 ◽  
Vol 1764 (1) ◽  
pp. 012065
Author(s):  
Ninik Sri Lestari ◽  
Sukirno ◽  
Hetty Fadriani ◽  
Ahmad Sujana ◽  
Yudi Herdiana ◽  
...  
Keyword(s):  
Application Data ◽  
Design And Application

scholarly journals A data model for enhanced data comparability across multiple organizations

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Patrick Obilikwu ◽  
Emeka Ogbuju
Keyword(s):  
Data Model ◽  
Current Practice ◽  
Population Analysis ◽  
Or Management ◽  
Assessment Scores ◽  
Enterprise Application ◽  
Data Comparability ◽  
Big Data Technologies ◽  
Geographical Locations ◽  
Meaningful Data

Abstract Organizations may be related in terms of similar operational procedures, management, and supervisory agencies coordinating their operations. Supervisory agencies may be governmental or non-governmental but, in all cases, they perform oversight functions over the activities of the organizations under their control. Multiple organizations that are related in terms of oversight functions by their supervisory agencies, may differ significantly in terms of their geographical locations, aims, and objectives. To harmonize these differences such that comparative analysis will be meaningful, data about the operations of multiple organizations under one control or management can be cultivated, using a uniform format. In this format, data is easily harvested and the ease with which it is used for cross-population analysis, referred to as data comparability is enhanced. The current practice, whereby organizations under one control maintain their data in independent databases, specific to an enterprise application, greatly reduces data comparability and makes cross-population analysis a herculean task. In this paper, the collocation data model is formulated as consisting of big data technologies beyond data mining techniques and used to reduce the heterogeneity inherent in databases maintained independently across multiple organizations. The collocation data model is thus presented as capable of enhancing data comparability across multiple organizations. The model was used to cultivate the assessment scores of students in some schools for some period and used to rank the schools. The model permits data comparability across several geographical scales among which are: national, regional and global scales, where harvested data form the basis for generating analytics for insights, hindsight, and foresight about organizational problems and strategies.

scholarly journals Reinforcement Learning to Send Reminders at Right Moments in Smartphone Exercise Application: A Feasibility Study

2021 ◽  
Vol 18 (11) ◽  
pp. 6059
Author(s):  
Shihan Wang ◽  
Karlijn Sporrel ◽  
Herke van Hoof ◽  
Monique Simons ◽  
Rémi D. D. de Boer ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Physical Activities ◽  
Lessons Learned ◽  
Just In Time ◽  
Healthcare Intervention ◽  
Adaptive Intervention ◽  
Mobile Healthcare ◽  
Crucial Component ◽  
Application Data ◽  
The Right

Just-in-time adaptive intervention (JITAI) has gained attention recently and previous studies have indicated that it is an effective strategy in the field of mobile healthcare intervention. Identifying the right moment for the intervention is a crucial component. In this paper the reinforcement learning (RL) technique has been used in a smartphone exercise application to promote physical activity. This RL model determines the ‘right’ time to deliver a restricted number of notifications adaptively, with respect to users’ temporary context information (i.e., time and calendar). A four-week trial study was conducted to examine the feasibility of our model with real target users. JITAI reminders were sent by the RL model in the fourth week of the intervention, while the participants could only access the app’s other functionalities during the first 3 weeks. Eleven target users registered for this study, and the data from 7 participants using the application for 4 weeks and receiving the intervening reminders were analyzed. Not only were the reaction behaviors of users after receiving the reminders analyzed from the application data, but the user experience with the reminders was also explored in a questionnaire and exit interviews. The results show that 83.3% reminders sent at adaptive moments were able to elicit user reaction within 50 min, and 66.7% of physical activities in the intervention week were performed within 5 h of the delivery of a reminder. Our findings indicated the usability of the RL model, while the timing of the moments to deliver reminders can be further improved based on lessons learned.

scholarly journals Alpha Amylase from Bacillus pacificus Associated with Brown Algae Turbinaria ornata: Cultural Conditions, Purification, and Biochemical Characterization

Processes ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 16
Author(s):  
Mona Alonazi ◽  
Aida Karray ◽  
Ahmed Yacine Badjah-Hadj-Ahmed ◽  
Abir Ben Bacha
Keyword(s):  
Biochemical Characterization ◽  
Alpha Amylase ◽  
Bacterial Symbionts ◽  
Terminal Sequence ◽  
Turbinaria Ornata ◽  
Substrate Analogs ◽  
Cultural Conditions ◽  
Initial Ph ◽  
Application Data ◽  
High Degree

We aimed in the current study, the identification of a marine bacterial amylase produced by Bacillus pacificus, which was associated with Turbinaria ornata. Cultural conditions were optimized for the highest amylase production on Tryptic soy broth media supplemented with starch 1% at initial pH 9, 55 °C for 24 h. The newly purified amylase was characterized for a possible biotechnological application. Data indicated that the obtained amylase with a molecular weight of 40 kD and the N-terminal sequence of the first 30 amino acids of amBp showed a high degree of homology with known alpha amylase, and was stable at 60 °C of pH 11. Among the tested substrate analogs, amBp was almost fully active on Alylose and Alylopectine (97%), but moderately hydrolyzed glycogen < sucrose < maltose < lactose. Therefore, the current amylase mainly generated maltohexaose from starch. Mg2+ and Zn2+ improved amylase activity up to 170%. While ethylenediamine tetraacetic acid (EDTA) similarly induced the greatest activity with purified amylase, PCMB had the least effect. Regarding all these characteristics, amylase from marine bacterial symbionts amBp has a new promising feature for probable therapeutic, industrial, and nutritional applications.

Query Processing of RFID Data with Object Trajectory in Manufacture and Logistics

2009 ◽  
Vol 16-19 ◽  
pp. 1043-1047
Author(s):  
Sun Wei ◽  
Li Hua Dong ◽  
Yao Hua Dong
Keyword(s):  
Pervasive Computing ◽  
Radio Frequency Identification ◽  
Object Identification ◽  
Data Set ◽  
Wide Range ◽  
Storage Scheme ◽  
Rfid Data ◽  
Frequency Identification ◽  
Application Data ◽  
Path Queries

In the domain of manufacture and logistics, Radio Frequency Identification (RFID) holds the promise of real-time identifying, locating, tracking and monitoring physical objects without line of sight due to an enhanced efficiency, accuracy, and preciseness of object identification, and can be used for a wide range of pervasive computing applications. To achieve these goals, RFID data has to be collected, filtered, and transformed into semantic application data. However, the amount of RFID data is huge. Therefore, it requires much time to extract valuable information from RFID data for object tracing. This paper specifically explores options for modeling and utilizing RFID data set by XML-encoding for tracking queries and path oriented queries. We then propose a method which translates the queries to SQL queries. Based on the XML-encoding scheme, we devise a storage scheme to process tracking queries and path oriented queries efficiently. Finally, we realize the method by programming in a software system for manufacture and logistics laboratory. The system shows that our approach can process the tracing or path queries efficiently.

Evaluation of Microbially Influenced Degradation as a Method for the Decontamination of Radio Actively Contaminated Concrete

1996 ◽  
Vol 465 ◽  
Author(s):  
R. D. Rogers ◽  
M. A. Hamilton ◽  
L. O. Nelson ◽  
J. Benson ◽  
M. Green
Keyword(s):  
Pilot Scale ◽  
Field Application ◽  
Department Of Energy ◽  
Laboratory Evaluation ◽  
Concrete Slabs ◽  
Initial Field ◽  
Acceptable Method ◽  
Application Data ◽  
The Cost ◽  
The U.S

ABSTRACTBecause there are literally square kilometers of radioactively contaminated concrete surfaces within the U.S. Department of Energy (DOE) complex, the task (both scope and cost) of decontamination is staggering. Complex-wide cleanup using conventional methodology does not appear to be feasible for every facility because of prioritization, cost, and manual effort required.We are investigating the feasibility of using microbially influenced degradation (MID) of concrete as a unique, innovative approach for the decontamination of concrete. Currently, work is being conducted to determine the practicality and cost effectiveness of using this environmentally acceptable method for decontamination of large surface concrete structures. Under laboratory conditions, the biodecontamination process has successfully been used to remove 2 mm of the surface of concrete slabs. Subsequently, initial field application data from an ongoing pilot-scale demonstration have shown that an average of 2 mm of surface can be removed from meter-square areas of contaminated concrete. The cost for the process has been estimated as $1.29/m2. Methodologies for field application of the process are being developed and will be tested. This paper provides information on the MID process, laboratory evaluation of its use for decontamination, and results from the pilot field application.

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