Performance Evaluation of the National Housing File (FNL) for the Development of E-Governance in the Housing Sector in Algeria

2019 ◽  
Vol 8 (4) ◽  
pp. 60-73
Author(s):  
Ouahiba Belhocine ◽  
Kahina Amal Djiar ◽  
Meriem Lagati
Keyword(s):  
Information Technology ◽  
Performance Evaluation ◽  
Decision Support Tool ◽  
Housing Sector ◽  
Housing Supply ◽  
Major Step ◽  
Support Tool ◽  
Noticeable Improvement ◽  
The Right ◽  
National Housing

The housing sector in Algeria has undergone huge transformations to improve the supply process. One of the major changes that has been operated is related to the introduction of information technology in the practice of controlling the eligibility of applicants for public housing. As a result, the National Housing File has been created, marking hereby a major step towards the development of e-governance in Algeria. Yet, despite this noticeable improvement, the housing supply process remains very complex. This is mainly linked to the multi-sectoral character of the procedure, which requires the involvement of various actors and institutions. The objective of this paper is to assess the strengths and weaknesses of the National Housing File, which has been conceived as a decision support tool to housing supply. The paper examines the process through which data is gathered and evaluation of potential beneficiaries is made. It sheds light on the issues that hinder the right functioning of the National Housing File and delay the development of e-governance in an effective way.

Transparency Issues Within a Transport Buyer and Provider Relationship

2020 ◽  
pp. 78-95
Author(s):  
Eirill Bø
Keyword(s):  
Supply Chain ◽  
Decision Support ◽  
Decision Support Tool ◽  
Food Distribution ◽  
Household Waste ◽  
Support Tool ◽  
Time Parameters ◽  
The Right ◽  
The Cost ◽  
The Relationship

Transport is an important function in the supply chain. This chapter focuses on how to buy a transport service, how to form a transport contract, and how a transparent relationship will influence the risk and the relationship between transport provider and buyer. By developing a decision support tool (DST-model) and calculating the cost and the time parameters, the right price and the cost drivers will appear. The cases described in this chapter are a large Norwegian wholesaler for food, distribution to the retailer, and two Norwegian municipalities collecting household waste. In these cases, the buyer and the provider are acting blind in setting the transport price. This means that there is a huge risk for either a bankruptcy by the transport provider or an overpriced transport for the buyer.

scholarly journals Towards Designing Tools for Universities’ R&D Performance Measurement on Mobile Platform

2019 ◽  
Vol 13 (04) ◽  
pp. 178
Author(s):  
Mohd Faizal Omar ◽  
Siti Rasifah Ahmad Roshidi ◽  
Jastini Mohd. Jamil ◽  
Fazillah Mohmad Kamal ◽  
Mohd Nasrun Mohd Nawi ◽  
...  
Keyword(s):  
Decision Making ◽  
Performance Indicator ◽  
Decision Support Tool ◽  
Education Institution ◽  
Mobile Platform ◽  
Support Tool ◽  
Prototype Development ◽  
The Moment ◽  
The Right ◽  
The Impact

<p class="Abstract">At the moment, there is a great interest in most universities to achieve higher ranking for better international standings and visibility. With shrinking resources such as financial and infrastructures, there is also a huge demand for the university to move forward and perform better in Research and Development (R&amp;D) in each evaluation year. Key Performance Indicator (KPI) is an excellent tool to enculturate research in a Higher Education Institution (HEI). The culture must be built upon HEI’s strength and weaknesses. Hence, the right decision making tool must be develop to priorities different agendas such as QSWUR, THE, etc. Mobile platform provide an efficient way to engage with stakeholders particularly to measure HEI performance on R&amp;D. There are three main activities involves for developing a decision support tool for measuring R&amp;D impact in HEIs i.e. development of decision model using multi criteria decision making, dashboard prototype development including and UI/UX for mobile platform. This paper describe the importance of measuring the impact of R&amp;D, prioritization technique and the process of prototype development. It is anticipates that our work could mitigate the gaps and improve the research ecosystem in HEIs.</p>

scholarly journals Intelligent system for recruitment decision making using an alternative parallel-sequential genetic algorithm

2021 ◽  
Vol 22 (1) ◽  
pp. 385
Author(s):  
Said Tkatek ◽  
Saadia Bahti ◽  
Otman Abdoun ◽  
Jaafar Abouchabaka
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Decision Support ◽  
Intelligent System ◽  
Decision Support Tool ◽  
Good Decision ◽  
Support Tool ◽  
Hr Managers ◽  
The Right ◽  
Recruitment Model

<p>The human resources (HR) manager needs effective tools to be able to move away from traditional recruitment processes to make the good decision to select the good candidates for the good posts. To do this, we deliver an intelligent recruitment decision-making method for HR, incorporating a recruitment model based on the multipack model known as the NP-hard model. The system, which is a decision support tool, often integrates a genetic approach that operates alternately in parallel and sequentially. This approach will provide the best recruiting solution to allow HR managers to make the right decision to ensure the best possible compatibility with the desired objectives. Operationally, this system can also predict the altered choice of parallel genetic algorithm (PGA) or sequential genetic algorithm (SeqGA) depending on the size of the instance and constraints of the recruiting posts to produce the quality solution in a reduced CPU time for recruiting decision-making. The results obtained in various tests confirm the performance of this intelligent system which can be used as a decision support tool for intelligently optimized recruitment.</p>

Radiation Considerations

2015 ◽  
Author(s):  
Andrew J. Einstein
Keyword(s):  
Nuclear Cardiology ◽  
Insurance Coverage ◽  
Decision Support Tool ◽  
Radiological Protection ◽  
Appropriateness Criteria ◽  
Patient Centered ◽  
Support Tool ◽  
Nuclear Cardiac Imaging ◽  
High Doses ◽  
The Right

Radiation considerations are an integral part of the practice of nuclear cardiac imaging. Concern regarding radiation has increased in recent years, reflected in statements by many professional societies, and likely attributable both to rapid growth in use of nuclear cardiology as well as high doses received by some nuclear cardiology patients. The fundamental principles of medical radiological protection are justification (ensuring that the right test is performed for the right patient at the right time), optimization (ensuring that the test is performed in the right manner), and dose limitation, which while applicable to healthcare workers is not operative regarding patients. Three "As" facilitate and serve as an organizing principle for justification: awareness, appropriateness, and audit. Awareness incorporates knowledge of the benefits and risks of testing involving radiation and effective communication of these to the patient. Appropriateness in nuclear cardiology can be assessed using the American College of Cardiology's appropriateness criteria. Methods that have been demonstrated to improve appropriateness include using a collaborative learning model, a point-of-order decision support tool, and a multifaceted intervention including threatened loss of insurance coverage. A variety of strategies should be considered for optimization to ensure patient-centered imaging. These including strategic selection of both the protocol, e.g. selecting a stress-first protocol and performing stress-only imaging in patients without a high pre-test probability of abnormal findings on stress imaging, or using PET, and also the administered activity, e.g. by using weight-based dosing and/or software- or hardware-based advances in camera technology. Special considerations are required for pregnant, nursing, and pediatric patients.

scholarly journals Identifying Health Information Technology Needs of Oncologists to Facilitate the Adoption of Genomic Medicine: Recommendations From the 2016 American Society of Clinical Oncology Omics and Precision Oncology Workshop

2017 ◽  
Vol 35 (27) ◽  
pp. 3153-3159 ◽  
Author(s):  
Kevin S. Hughes ◽  
Edward P. Ambinder ◽  
Gregory P. Hess ◽  
Peter Paul Yu ◽  
Elmer V. Bernstam ◽  
...  
Keyword(s):  
Information Technology ◽  
Health Information Technology ◽  
Health Information ◽  
Genomic Medicine ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Knowledge Bases ◽  
Test Case ◽  
Precision Oncology ◽  
Support Tool

At the ASCO Data Standards and Interoperability Summit held in May 2016, it was unanimously decided that four areas of current oncology clinical practice have serious, unmet health information technology needs. The following areas of need were identified: 1) omics and precision oncology, 2) advancing interoperability, 3) patient engagement, and 4) value-based oncology. To begin to address these issues, ASCO convened two complementary workshops: the Omics and Precision Oncology Workshop in October 2016 and the Advancing Interoperability Workshop in December 2016. A common goal was to address the complexity, enormity, and rapidly changing nature of genomic information, which existing electronic health records are ill equipped to manage. The subject matter experts invited to the Omics and Precision Oncology Workgroup were tasked with the responsibility of determining a specific, limited need that could be addressed by a software application (app) in the short-term future, using currently available genomic knowledge bases. Hence, the scope of this workshop was to determine the basic functionality of one app that could serve as a test case for app development. The goal of the second workshop, described separately, was to identify the specifications for such an app. This approach was chosen both to facilitate the development of a useful app and to help ASCO and oncologists better understand the mechanics, difficulties, and gaps in genomic clinical decision support tool development. In this article, we discuss the key challenges and recommendations identified by the workshop participants. Our hope is to narrow the gap between the practicing oncologist and ongoing national efforts to provide precision oncology and value-based care to cancer patients.

scholarly journals Modelo construtivista para apoiar o processo de gestão da Universidade Federal de Tocantins

2016 ◽  
Vol 15 (2) ◽  
pp. 122-129
Author(s):  
Leonardo Ensslin ◽  
Ademar Dutra ◽  
Renard Pereira Martins ◽  
Vinicius Dezem
Keyword(s):  
Performance Evaluation ◽  
Secondary Data ◽  
Decision Support Tool ◽  
Assessment Model ◽  
Multicriteria Decision Aid ◽  
Main Question ◽  
Management Tools ◽  
Support Tool ◽  
Strategic Objectives ◽  
A Performance

Higher education institutions have a direct impact in promoting economic growth and social development. Specially of the environment on which they operate. Their results are expected by governments, businesses and society. For this reason, there is a need for management tools that can support decision-making processes. In this context, this present study main question is how a Performance Assessment Model can contribute to Araguina Campus management process of the Federal University of Tocantins (UFT)? To answer the question, the goal is to structure a performance evaluation multicriteria model to support the management of Araguaína campus of the Federal University of Tocantins. The developed case study has exploratory character with qualitative and quantitative approach, collecting primary and secondary data. The intervention instrument used was the Multicriteria Decision-Aid Methodology – Constructivist (MCDA-C). Methodology that meets the foundations of performance evaluation as a decision support tool. We identified 8 strategic objectives, operationalized by 134 performance indicators. Among these, 33 are in compromising performance, highlighting the need for intervention. The model facilitated the overview of this situation and provided a process for proposing improvement actions. Thus, enabling the monitoring and improvement of the current situation.

scholarly journals Selection of the Transport Mode Using the AHP Method Within Distribution Logistics of Motor Fuels

2021 ◽  
Vol 33 (6) ◽  
pp. 905-917
Author(s):  
Roman Hruška ◽  
Matej Kmetík ◽  
Jan Chocholáč
Keyword(s):  
Decision Support Tool ◽  
Ahp Method ◽  
Analytic Hierarchy ◽  
Support Tool ◽  
Transport Mode ◽  
Motor Fuels ◽  
Distribution Logistics ◽  
Mode Of Transport ◽  
The Right ◽  
Selection Of

To remain competitive and respond to rapidly changing markets, we need to increase flexibility in today's global marketplace. In this respect, the selection of the appropriate mode of transport is one of the most important functions to be performed by logistics. The selection of the appropriate mode of transport is a multi-criteria problem involving both quantitative and qualitative criteria. This paper deals with the selection of the mode of transport using the Analytic Hierarchy Process method (AHP). AHP is a method of decomposing a complex unstructured situation into simpler components to create a hierarchical system problem. This paper describes a general model of selection of transport mode using AHP including its application to a manufacturing company that selects the appropriate mode of transport from three potential transport modes. The aim of this paper is to create a useful decision support tool for selection of the transport mode using the AHP method within distribution logistics of motor fuels. This tool helps companies to make the right decision on the choice of transport mode by taking into account different importance of the different criteria that influence the decision-making process.

scholarly journals SISTEM PENDUKUNG KEPUTUSAN PENERIMAAN CALON MAHASISWA BARU JALUR PRESTASI DI SEKOLAH TINGGI TEKNOLOGI ADISUTJIPTO MENGGUNAKAN SIMPLE MULTI ATTRIBUTERATING TECHNIQUE

2017 ◽  
Vol 7 (2) ◽  
pp. 31
Author(s):  
Anton Setiawan Honggowibowo
Keyword(s):  
Information Technology ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Decision Support Tool ◽  
Educational Institutions ◽  
Web Based ◽  
Support Tool ◽  
New Students

In the era of globalization, educational institutions are required to follow the development of information technology. Information technology required and can be applied as a decision support tool managerial activities at the college. This research aims to develop a decision support system for the Sekolah Tinggi Teknologi Adisutjipto (STTA), namely the acceptance of new students, especially the path of achievement, using the Simple Multi Attribute Rating Technique of Web based, where in the method is choosing alternative criteria that have value and weight has been determined, getting the new students he deserves. Based on the results of testing the system, it was concluded that the method is Simple Multi Attribute Rating Technique is effective enough to be applied in determining the admission of new students in STTA.

scholarly journals Early-, Late-, and Very Late-Term Prediction of Target Lesion Failure in Coronary Artery Stent Patients: An International Multi-Site Study

2021 ◽  
Vol 11 (15) ◽  
pp. 6986
Author(s):  
Elisabeth Pachl ◽  
Alireza Zamanian ◽  
Myriam Stieler ◽  
Calvin Bahr ◽  
Narges Ahmidi
Keyword(s):  
At Risk ◽  
Coronary Artery ◽  
Phase I ◽  
Decision Support Tool ◽  
Target Lesion ◽  
Post Intervention ◽  
Support Tool ◽  
Coronary Artery Stent ◽  
Target Lesion Failure ◽  
The Right

The main intervention for coronary artery disease is stent implantation. We aim to predict post-intervention target lesion failure (TLF) months before its onset, an extremely challenging task in clinics. This post-intervention decision support tool helps physicians to identify at-risk patients much earlier and to inform their follow-up care. We developed a novel machine-learning model with three components: a TLF predictor at discharge via a combination of nine conventional models and a super-learner, a risk score predictor for time-to-TLF, and an update function to manage the size of the at-risk cohort. We collected data in a prospective study from 120 medical centers in over 25 countries. All 1975 patients were enrolled during Phase I (2016–2020) and were followed up for five years post-intervention. During Phase I, 151 patients (7.6%) developed TLF, which we used for training. Additionally, 12 patients developed TLF after Phase I (right-censored). Our algorithm successfully classifies 1635 patients as not at risk (TNR = 90.23%) and predicts TLF for 86 patients (TPR = 52.76%), outperforming its training by identifying 33% of the right-censored patients. We also compare our model against five state of the art models, outperforming them all. Our prediction tool is able to optimize for both achieving higher sensitivity and maintaining a reasonable size for the at-risk cohort over time.

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