Technological innovations in the work environment and the career of the millennium generation

Purpose – The purpose of this paper is to identify the relationship of career anchors with three aspects: themillennials’ professional skills, the millennials’ awareness of the replacement of jobs with new technologiesand the technological stress in the millennials’ working environment.Design/methodology/approach – The responses of 200 questionnaires were analyzed using descriptiveand variance analysis techniques.Findings – Among the three hypotheses raised, two were confirmed, showing that these young peoplerecognize the development of professional skills through new technologies, but are not highly sensitive to thestress associated with technological innovations.Originality/value – The paper contributes to a recent debate, which emphasizes the impact of theapplication of new technologies on the nature of study and employment levels

Reducing Carbon Footprint Using Renewable Energy, Distributed Generation and Smart Government Policies

With continued and increased global outcry to the insidious effects of continued exploitation of fossil fuels and gas flaringon the environment as evidenced by climate change, attention has in recent times be turned to alternative and more efficientmeans of energy generation that pose less threats or damage to the environment. Utilizing such alternative means of energygeneration has seen an increase in technological advancements as regards exploitation of such natural elements as sunlight,wind, tides, hydro etc. in meeting our varied energy demands. These alternative energy sources commonly referred to asrenewable energy sources (RES) now constitute the global trend as not only are they providing access to clean energy indistant and remote areas, but also redefining the way our electricity grid now works. With the enormous problems associatedwith centralized generation and transmission of electricity vis-à-vis line losses and system reliability, coupled with theinability of the grid to effectively cover every nook and cranny of the country, attention is being put on practical andeffective means and ways of integrating these RES into our electricity network. One of such means that have been evolved isDistributed Generation (DG) which seeks to decentralize electricity generation and displace demand by generating at loadcentres. Acting as stand-alone systems, their presence in Nigeria is gradually beginning to be felt. This paper seeks toexamine the impact of RES and DG in select cities around the world in addressing issues of poverty eradication, climatechange, transmission line losses etc., while also appraising the impact government policies have had in influencing theirgrowth. Existing policies on renewable energy and DG (if any) in Nigeria would be reviewed while solutions would also beproffered as Nigeria strives to meet the objectives of the Millennium Development Goals (MDGs), 2015, especially endingextreme hunger and poverty.Keywords: insidious, environment, climate change, renewable energy, distributed generation, policies, poverty, hunger

Practice Makes Perfect: an iterative approach to achieve precise tracking for legged robots

Precise trajectory tracking for legged robots can be challenging due to their high degrees of freedom, unmodeled nonlinear dynamics, or random disturbances from the environment. A commonly adopted solution to overcome these challenges is to use optimization-based algorithms and approximate the system with a simplified, reduced-order model. Additionally, deep neural networks are becoming a more promising option for achieving agile and robust legged locomotion. These approaches, however, either require large amounts of onboard calculations or the collection of millions of data points from a single robot. To address these problems and improve tracking performance, this paper proposes a method based on iterative learning control. This method lets a robot learn from its own mistakes by exploiting the repetitive nature of legged locomotion within only a few trials. Then, a torque library is created as a lookup table so that the robot does not need to repeat calculations or learn the same skill over and over again. This process resembles how animals learn their muscle memories in nature. The proposed method is tested on the A1 robot in a simulated environment, and it allows the robot to pronk at different speeds while precisely following the reference trajectories without heavy calculations.Comment: 6 pages, 4 figure

Real-time human detection from depth images with heuristic approach

Abstract. The first industrial robot was built in the mid-20th century. The idea of the industrial robots was to replace humans in assembly lines, where the tasks were repetitive and easy to do. The benefits of these robots are that they are able to work around the clock and only need electricity as compensation. Over the years, robots capable of only doing repetitive tasks have evolved to operate fully autonomously in challenging environments. Some examples of these are self-driving cars and service robots that can work as customer servants. This is mainly accomplished through advancements in artificial intelligence, machine vision, and depth camera technologies. With machine vision and depth perception, robots are able to construct a fully structured environment around them and this allows them to properly react to sudden changes in their surroundings. In this project, a naive detection algorithm was implemented to separate humans from depth images. The algorithm works by removing the ground plane, after which the floating objects can be separated more easily. The floating objects are further processed, and the human detection part is then achieved using a heuristic approach. The proposed algorithm works in real time and reliably detects people standing in a relatively open environment. However, because of the naive approach, human-sized items are wrongly detected as humans in some scenarios.Tiivistelmä. Ensimmäinen teollisuusrobotti rakennettiin 1900-luvun puolivälissä. Teollisuusrobottien tarkoitus oli korvata ihmiset tehtaiden kokoonpanolinjoilla, joissa työtehtävät olivat pääsääntöisesti yksinkertaisia ja itseään toistavia. Näiden robottien etuna on, että ne kykenevät työskentelemään kellon ympäri pelkän sähkön varassa. Vuosien mittaan robotit ovat kehittyneet yksinkertaisista koneista roboteiksi, jotka kykenevät toimimaan täysin itsenäisesti haastavissakin olosuhteissa. Itseajavat autot ja asiakaspalvelijana toimivat palvelurobotit ovat näistä hyviä esimerkkejä. Tällaiset saavutukset ovat olleet mahdollisia tekoälyn, konenäön ja syvyyskameroiden kehityksen myötä. Kone- ja syvyysnäön avulla robotit pystyvät muodostamaan itselleen selkeän kuvan ympäristöstään, mikä mahdollistaa nopean reagoinnin yllättäviinkin muutoksiin ympäristössä. Tässä työssä toteutettiin naiivi havaitsemisalgoritmi erottelemaan ihmiset syvyyskuvista. Algoritmi poistaa maatason, jonka jälkeen ilmassa leijuvat esineet voidaan erotella toisistaan. Erotetut esineet jatkokäsitellään, jonka jälkeen ihmisten havaitseminen toteutetaan heuristisella menetelmällä. Työssä esitelty algoritmi toimii reaaliajassa ja pystyy luotettavasti havaitsemaan ihmiset suhteellisen avoimessa ympäristössä, vaikkakin joissain tapauksissa ihmisen kokoiset esineet luokitellaan väärin ihmisiksi naiivin lähestymistavan vuoksi