scholarly journals Digital Intelligence Banking of Adaptive Digital Marketing with Life Needs Control

2020 ◽  
Author(s):  
Ryosuke Konishi ◽  
Fumito Nakamura ◽  
Yasushi Kiyoki
Keyword(s):  
Machine Learning ◽  
Dynamic Environment ◽  
Information Provision ◽  
Living Environment ◽  
Goods And Services ◽  
Meaningful Information ◽  
Information Assets ◽  
The Individual ◽  
Over Time

While individuals benefit from the goods and services provided by companies that enrich their lives and that have adapted to a dynamic environment that is always changing, these companies pay a high communication cost to access opportunities to provide these goods and services and to seek a better understanding of individual customers’ changing needs. Although vast amounts of information can be obtained, databases and machine learning are playing an increasingly important role in extracting meaning from this information, turning it into meaningful information assets that consider circumstances and contexts, and individualizing the economy of information. I propose an implementation method for providing information to enrich the profiles of individual customers by consolidating different data, calculating the individual customers’ needs through the relationships between customers and products, evaluating the change in relationships between individual customers and products over time, and providing goods and services to suit different intervals of change to factors such as lifestyle and living environment. As there are different factors involved in estimating the incidence of needs, and different frequencies and rates at which they occur, based on the special characteristics of products, different data are required to estimate such needs. By profiling individuals over the long term, it is possible to build an information provision environment that is conducive to companies’ customer acquisition.

Eine bibliometrische Analyse/PPC and machine learning A bibliometric analysis

2020 ◽  
Vol 110 (04) ◽  
pp. 220-225
Author(s):  
Matthias Schmidt ◽  
Janine Tatjana Maier ◽  
Mark Grothkopp
Keyword(s):  
Machine Learning ◽  
State Of The Art ◽  
Dynamic Environment ◽  
Production Planning And Control ◽  
Manufacturing Companies ◽  
Comprehensive Review ◽  
Planning And Control ◽  
Individual Task ◽  
The Individual ◽  
And Control

Produzierende Unternehmen stehen in einem dynamischen Umfeld vor der Herausforderung eine zunehmende Datenmenge effizienter zu verarbeiten. In diesem Zusammenhang werden häufig Ansätze des maschinellen Lernens (ML) diskutiert. Der Beitrag stellt eine umfassende Aufarbeitung des Stands der Forschung bezogen auf den Einsatz von ML-Ansätzen in der Produktionsplanung und -steuerung (PPS) bereit. Daraus lässt sich der Forschungsbedarf in den einzelnen Aufgabengebieten der PPS ableiten.   In a dynamic environment, manufacturing companies face the challenge of processing an increasing amount of data more efficiently. In this context, approaches of machine learning (ML) are often discussed. This paper provides a comprehensive review of the state of the art regarding the use of ML approaches in production planning and control (PPC). Based on this, the need for research in the individual task areas of PPC can be derived.

A machine learning approach for the automatic long-term structural health monitoring

2018 ◽  
Vol 18 (3) ◽  
pp. 819-837 ◽  
Author(s):  
Giacomo Vincenzo Demarie ◽  
Donato Sabia
Keyword(s):  
Machine Learning ◽  
Data Acquisition ◽  
Structural Behavior ◽  
Practical Applications ◽  
Existing Structures ◽  
Machine Learning Approach ◽  
Modes Of Vibration ◽  
Engineering Parameters ◽  
Over Time

Measuring the response of a structure to the ambient and service loads is a source of information that can be used to estimate some important engineering parameters or, to a certain extent, to characterize the structural behavior as a whole. By repeating the data acquisition over a period of time, it is possible to check for variations in the structure’s response, which may be correlated to the appearance or growth of a damage (e.g. following some exceptional event as the earthquake, or as a consequence of materials and components aging). The complexity of some existing structures and their environment very often requires the execution of a monitoring plan in order to support analyses and decisions through the evidence of measured data. If the monitoring is implemented through a sensor network continuously acquiring over time, then the evolution of the structural behavior may be tracked continuously as well. Such approach has become a viable option for practical applications since the last decade, as a consequence of the progress in the data acquisition and storage systems. However, proper methods and algorithms are needed for managing the large amount of data and the extraction of valuable knowledge from it. This article presents a methodology aimed at making automatic the process of structural monitoring in case it is carried continuously over time. It relies on some existing methods from the machine learning and data mining fields, which are casted into a process targeted to delimit the need of the human being intervention to the training phase and the engineering judgment of the results. The methodology has been successfully applied to the real-world case of an ancient masonry bell tower, the Ghirlandina Tower (Modena, Italy), where a network made of 12 accelerometers and 3 thermocouples has been acquiring continuously since August 2012. The structural characterization is performed by identifying the first modes of vibration, whose evolution over time has been tracked.

Risk and Protective Factors for Depression in Youth

2006 ◽  
Vol 23 (1) ◽  
pp. 1-30 ◽  
Author(s):  
Alison L. Shortt ◽  
Susan H. Spence
Keyword(s):  
Protective Factors ◽  
Risk And Protective Factors ◽  
Ecological Framework ◽  
Preventive Interventions ◽  
Factors Associated ◽  
Health Promoting ◽  
Protective Processes ◽  
The Individual ◽  
Over Time

AbstractRisk and protective processes and mechanisms associated with depression in youth are discussed within a developmental–ecological framework. Risk factors at the individual (genetics, biology, affect, cognition, behaviour) and broader contextual levels (e.g., family, school, community) are proposed to interact, leading to the development of depression in youth. Transactions between these individual and contextual factors are suggested to be dynamic and reciprocal, and these transactions are expected to change over time and developmental course. The ‘best bet’ for the prevention of depression may be multicomponent and multilevel interventions that address the multiple risk and protective factors associated with depression. Preventive interventions need to focus on building protective factors within young people themselves, as well as creating health-promoting environments at home and at school. These interventions likely need to be long term and geared towards assisting youth across successive periods of development.

Peak Impact Accelerations during Track and Treadmill Running

2013 ◽  
Vol 29 (5) ◽  
pp. 639-644 ◽  
Author(s):  
Erin M.R. Bigelow ◽  
Niell G. Elvin ◽  
Alex A. Elvin ◽  
Steven P. Arnoczky
Keyword(s):  
Healthy Subjects ◽  
Treadmill Running ◽  
Acrylic Plate ◽  
Custom Made ◽  
The Individual ◽  
Long Term Impact ◽  
Wireless Accelerometer ◽  
Vertical Impact ◽  
Over Time

To determine whether peak vertical and horizontal impact accelerations were different while running on a track or on a treadmill, 12 healthy subjects (average age 32.8 ± 9.8 y), were fitted with a novel, wireless accelerometer capable of recording triaxial acceleration over time. The accelerometer was attached to a custom-made acrylic plate and secured at the level of the L5 vertebra via a tight fitting triathlon belt. Each subject ran 4 miles on a synthetic, indoor track at a self-selected pace and accelerations were recorded on three perpendicular axes. Seven days later, the subjects ran 4 miles on a treadmill set at the individual runner’s average pace on the track and the peak vertical and horizontal impact magnitudes between the track and treadmill were compared. There was no difference (P= .52) in the average peak vertical impact accelerations between the track and treadmill over the 4 mile run. However, peak horizontal impact accelerations were greater (P= .0012) on the track when compared with the treadmill. This study demonstrated the feasibility for long-term impact accelerations monitoring using a novel wireless accelerometer.

scholarly journals Mental Health in the Workplace (2) – Mental Health and Discrimination in Employment

2014 ◽  
Vol 1 (16) ◽  
pp. 194
Author(s):  
Kay Wheat
Keyword(s):  
Mental Health ◽  
Mental Health Problems ◽  
Health Problems ◽  
Employment Protection ◽  
Basic Premise ◽  
Goods And Services ◽  
Discrimination In Employment ◽  
Disability Discrimination Act ◽  
The Individual

<p align="LEFT">People with mental health problems are stigmatised and in particular there is concern about stigmatisation in employment. The Disability Discrimination Act 1995 (“the Act”) was introduced to address the problems of disabled people, both in employment and in the provision of education, goods and services and the legislation is concerned with mental as well as physical health. However, its basic premise is that disability has to be long-term and must be defined in terms of the individual disabled person. Many people with mental health problems are not disabled within the meaning of the Act, and because of the individualised approach what has been described as institutionalised discrimination has not been addressed. This article examines the current employment protection for those with mental health problems offered by the Act and elsewhere. It will be argued that there are particular problems associated with mental health that are not addressed by the current law and that recent attempts to address these have resulted in a missed opportunity, and that a more radical approach is necessary because of the nature of mental health and the perceptions and prejudices surrounding this area. </p>

Inconsistency-Induced Learning for Perpetual Learners

2013 ◽  
pp. 70-87 ◽  
Author(s):  
Du Zhang ◽  
Meiliu Lu
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Target Function ◽  
Data Sets ◽  
Revision Process ◽  
Learning Agents ◽  
Learning Agent ◽  
The One ◽  
Over Time

One of the long-term research goals in machine learning is how to build never-ending learners. The state-of-the-practice in the field of machine learning thus far is still dominated by the one-time learner paradigm: some learning algorithm is utilized on data sets to produce certain model or target function, and then the learner is put away and the model or function is put to work. Such a learn-once-apply-next (or LOAN) approach may not be adequate in dealing with many real world problems and is in sharp contrast with the human’s lifelong learning process. On the other hand, learning can often be brought on through overcoming some inconsistent circumstances. This paper proposes a framework for perpetual learning agents that are capable of continuously refining or augmenting their knowledge through overcoming inconsistencies encountered during their problem-solving episodes. The never-ending nature of a perpetual learning agent is embodied in the framework as the agent’s continuous inconsistency-induced belief revision process. The framework hinges on the agents recognizing inconsistency in data, information, knowledge, or meta-knowledge, identifying the cause of inconsistency, revising or augmenting beliefs to explain, resolve, or accommodate inconsistency. The authors believe that inconsistency can serve as one of the important learning stimuli toward building perpetual learning agents that incrementally improve their performance over time.

A changing economic vote in Western Europe? Long-term vs. short-term forces

2018 ◽  
Vol 11 (1) ◽  
pp. 91-108 ◽  
Author(s):  
Ruth Dassonneville ◽  
Michael S. Lewis-Beck
Keyword(s):  
Western Europe ◽  
Short Term ◽  
National Elections ◽  
European Elections ◽  
State Of The Economy ◽  
The Status ◽  
Economic Vote ◽  
The Individual ◽  
Over Time

AbstractConsiderable research shows the presence of an economic vote, with governments rewarded or punished by voters, depending on the state of the economy. But how stable is this economic vote? A current argument holds its effect has increased over time, because of weakening long-term social and political forces. Under these conditions, short-term forces, foremostly the economic issue, can come to the fore. A counter-argument, however, sees the economic vote effect in decline, due to globalization. Against these rival hypotheses rests the status-quo argument: the economic vote effect remains unchanged. To test these claims, we estimate carefully specified models of the incumbent vote, at both the individual and aggregate levels. Western European elections provide the data, with particular attention to Denmark, Germany, Great Britain, Italy, The Netherlands, Norway, and Sweden. Perhaps surprisingly, we find the economic vote to be stable over time, a ‘standing decision’ rule that voters follow in national elections.

scholarly journals Understanding usage style transformation during long-term smartwatch use

2021 ◽  
Author(s):  
Aku Visuri ◽  
Niels van Berkel ◽  
Jorge Goncalves ◽  
Reza Rawassizadeh ◽  
Denzil Ferreira ◽  
...  
Keyword(s):  
Large Scale ◽  
Previous Literature ◽  
Shared Understanding ◽  
Market Growth ◽  
Early Adoption ◽  
The Individual ◽  
Over Time ◽  
Usage Data

AbstractDespite large investments in smartwatch development, the market growth remains smaller than forecasted. The purpose of smartwatch use remains unclear, indicated by the lack of large-scale adoption. Thus, we aim to better understand the early adoption and everyday smartwatch use. We investigate a diverse usage data of smartwatches logged over a period of up to 14 months from 79 individuals between December 2015 and March 2017, one of the largest wearable datasets collected. First, we identify both explorative and accepted behaviours that users exhibit and further investigate how the individual usage traits and features differ between the two categories. Our analysis offers an insightful perspective on how smartwatch use evolves organically. Our results improve our shared understanding of smartwatch use and users adapting their use of smartwatch over time to match the capabilities of the technology by validating numerous findings from previous literature.

Indicators of Deprivation in People and Places: Longitudinal Perspectives

1998 ◽  
Vol 30 (6) ◽  
pp. 1055-1076 ◽  
Author(s):  
A Sloggett ◽  
H Joshi
Keyword(s):  
Predictive Power ◽  
Individual Characteristics ◽  
Housing Tenure ◽  
Area Deprivation ◽  
Spatial Mobility ◽  
Multivariate Models ◽  
National Statistics ◽  
The Individual ◽  
Over Time

The Office for National Statistics Longitudinal Study of England and Wales is used to describe the prevalence in individuals, over time, of a set of variables commonly used in the construction of indicators of area deprivation. These variables are: housing tenure, car access, low skill, and unemployment. Over three censuses between 1971 and 1991, these states appear neither completely permanent nor entirely random. The picture is one of changing fortunes; many individuals temporarily disadvantaged revolving around a core of those experiencing more long-term disadvantage. This is especially true of unemployment. Used in multivariate models to predict health and deprivation outcomes in 1991, the individual characteristics from both 1971 and 1981 have stronger predictive power than ward scores on deprivation indicators. The relation between spatial mobility and the health and social outcomes appears favourable only for young adults.

After ethnic civil war

2012 ◽  
Vol 49 (6) ◽  
pp. 817-831 ◽  
Author(s):  
Karin Dyrstad
Keyword(s):  
Civil War ◽  
International Relations ◽  
Control Group ◽  
Peace Agreement ◽  
Interethnic Relations ◽  
Long Term Stability ◽  
War Experiences ◽  
The Individual ◽  
Over Time

While the study of the causes of civil war is a well-established subdiscipline in international relations, the effects of civil war on society remain less understood. Yet, such effects could have crucial implications for long-term stability and democracy in a country after the reaching of a peace agreement. This article contributes to the understanding of the effects of warfare on interethnic relations, notably attitudes of ethno-nationalism. Two hypotheses are tested: first, that the prevalence of ethno-nationalism is higher after than before the war, and second, that individuals who have been directly affected by the war are more nationalist than others. The variation in ethno-nationalism is examined over time, between countries, and between ethnic groups. Three countries that did not experience conflict on their own territory serve as a control group. The effect of individual war exposure is also tested in the analysis. Sources include survey data from the former Yugoslavia in 1989, shortly before the outbreak of war in Croatia and Bosnia and Herzegovina, and in 2003, some years after the violence in the region ended. Contrary to common beliefs, the study shows that ethno-nationalism does not necessarily increase with ethnic civil war. The individual war experiences are less important than expected.

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