measure smartphone display screens quotation

Not all projects are suitable for Screen Logic solutions. Rather than wait for a Screen Logic representative to schedule an appointment let us give you a close estimate of costs so you know if this fits your budget or not. Photos can tell a thousand words and measurements (within 5-6 inches of accuracy) will put us in a close range of the actual cost. Let us know what you want to solve (e.g. sun, wind, bugs, privacy). Please supply us with the following and we’ll help you determine if Screen Logic fits within your budget.

PhotographsTake photos with your smartphone. Take more than one, please! We don’t need a high-resolution photo, but take them when there is plenty of light.

Our roll down systems requires electric power where our large door screens do not. If you’re thinking of enclosing a porch area, then take a picture of where the power is located if there is a source like an outlet or soffit lights.

Moasure leverages its patented motion measuring technology.It puts in your hands one tool that can measure any distance, height, width, level, angle or incline. All you need to do is move and tap.

As you touch down from one point to another Moasure plots each position and calculates all the relevant measurements at the same time. So, if you take a straight-line measurement from one wall to another, Moasure will calculate the A to B measurement, but it will also be able to calculate the difference in height, level or angle between the two points.

Moasure is an incredibly smart measure, working powerfully with all the data it collects. Touch the diagonal corners of a room and Moasure will produce length and width measurements and calculate the 2D area of the room all at the same time. It can just as simply calculate 3D measurements and volume of any object whether that’s a box for packing or a round table or piece of furniture to put in storage.

Moasure can also adjust measurements to ignore obstacles, so if you need to move around furniture or move through doors to get from one room to another, it will measure as if the obstacles and walls are not there. Moasure can also adjust measurements if you cannot reach in a straight line across a room.

Moasure takes more than 500 sensor measurements every second as you move. Complex software algorithms process this data and calculate how far Moasure has been moved and rotated

As Moasure plots and measures at the same time, all you need to do is move and Moasure will track its position from point to point and give you the measurement. This means it is as easy to measure across a room from one wall to another, as it is the whole length of a garden; and as easy to measure a flat surface as it is a curved wall or a cylinder or something irregular like a run of pipe round the wall of the house.

Participants" smartphone screen-time exposure was on average approximately 3.7 minutes per hour, centered as expected primarily during the daytime. Those who were younger, Black, and Other race/ethnicity had greater screen-time exposure. Longer average screen-time was associated with shorter duration of sleep and reduced sleep efficiency. Given that screen-time after self-reported sleeping hours and near an individual’s bedtime was associated with reduced sleep efficiency and greater sleep onset latency, the relationship between overall smartphone use and sleep may be driven by exposure near bedtime.

Since the advent of the modern smartphone in 2007, the adoption and use of these devices has been rapid and widespread [13]. As of 2015, approximately 64% of all American adults owned a smartphone, including 85% of those aged 18 to 29 [1]. While the demographics of individuals that purchase smartphones has been studied, the frequency of use based upon an objective measure has not previously been described. We found that younger individuals on average have greater screen-time, in agreement with survey-based demographic and marketing research [1,13]. Our finding that African Americans and Hispanics exhibit longer screen-time is consistent with the fact that racial and ethnic minorities have fewer desktop and laptop computers at home and are more frequently dependent on their smartphone for internet access [1]. Of interest, neither income nor education was associated with average screen-time after multivariable adjustment, suggesting that something cultural aside from socio-economic status may be driving increased smartphone use in these populations.

While there has been concern for both the negative and positive impact of smartphones on depression [14,15], screen-time exposure was not associated with mood after multivariable adjustment. It is also noteworthy that unlike TV watching [16,17], smartphone screen-time was not associated with physical activity level or BMI. This may in part be due to the multi-functionality of smartphones, different modes of media consumption, or perhaps the use of smartphones during physical activities (i.e., running apps). Finally, despite the fact that searching for medical information is one of the most common activities carried out with smartphones [1], none of the medical conditions evaluated were associated with average screen-time.

In addition to how smartphones are changing modern life, the impact of screen exposure on sleep is a major concern. Poor sleep has been shown to decrease performance at school and work, is associated with depressed mood, and is established as a risk factor for obesity, cardiovascular disease, stroke, and death [4,18,19]. Smartphones are often nearby at night, and 68% of owners store their phone on a bedside table while they sleep [20]. Prior studies regarding watching television, conventional computer use, and video-games have demonstrated that use at nighttime and particularly in the bedroom is associated with poor sleep and insomnia [2,7]. Exposure to blue light from such backlit screens suppresses production of melatonin, thereby delaying sleep onset and reducing sleep duration and quality [21]. A recent randomized cross-over trail found hospitalized patients took longer to fall asleep and had reduced quality of sleep after reading a backlit eReader compared to a paper book before bedtime [22]. However, this and other experimental studies may not generalize to typical at-home screen exposure and experiences with eReaders may not extrapolate to smartphone use. At-home screen-time obtained by self-report has been associated with poor sleep [23], but a study that used an app to measure smartphone screen-time in a small group of Taiwanese university students found that participants underestimated their screen-time by approximately 9 hours per week (equivalent to an average of 3.2 minutes/hour) [24].

Our objectively measured screen-time was associated with reduced quality of sleep. That increased screen-time in the hour of and after bedtime, but not the hour before, was associated with greater sleep onset latency agrees with the notion that screen use just before attempting to fall asleep may be particularly problematic.

This study has several important limitations. First, we analyzed a self-selected group of participants that elected to enroll in the Health eHeart Study and download the Ginger.io app, which may not be representative of the general population. Compared to the U.S. census, the cohort is better educated, wealthier, and consists of a greater proportion of whites and females [25,26]. The relative older age of our cohort may be surprising in a study requiring smartphone ownership. However, as demonstrated by the standard deviations in age, the cohort generally represented those in their early 30s to those in their mid 60s. This likely demonstrates the age groups most representative not only of smartphone ownership, but also those most willing, interested, and able to engage with an internet-based research study. On the other hand, we could only record screen-time on Android phones, owners of which tend to have lower socio-economic status compared to iPhone owners [27,28]. Similarly, analyses on screen-time and sleep were limited to a subset who had both types of data available, and analyses on screen-time near bedtime were in a further subset with no missing screen-time data, both of which are susceptible to selection bias. Demographic, medical, and sleep information were obtained by self-report, although well-validated standardized scales (PSQI, PHQ-9, IPAQ) were used. In addition, self-report of medical conditions within the Health eHeart Study has previously proven to exhibit high accuracy [29]. App-recorded screen-time is subject to some measurement error. Screen-time when the app was actively turned off or the phone was in airplane mode was not captured, there could be multiple users of a single smartphone, or the screen could be on while a participant was not aware (such as when the screen is on while in a pocket). We also focused specifically on smartphone screen-time exposure and did not have information on the use of other back-lit devices (TV, computer, tablets). We analyzed 30-day windows with the least amount of missing screen data in an attempt to maximize the accuracy of the screen-time measure, but this could also have induced bias. Still, incomplete capture of smartphone screen exposure, and the absence of data on exposure to other types of screens, should only decrease sensitivity for associations with other participant characteristics. Finally, in regards to the analyses related to screen-time and sleep; although screen-time was collected prospectively and compared to sleep characteristics at baseline, we cannot exclude “effect-cause”—poor sleep could lead to more screen-time.

Our study also has some notable strengths. This is the first time smartphone screen-time exposure has been recorded prospectively and compared to demographic and medical information. Screen-time was measured unobtrusively during “at home” use over a 30 day period and thus is more comparable to every-day long term use than prior experimental studies. Furthermore, since enrollment and consent in the Health eHeart study is performed remotely, the cohort is not limited to a particular geographic location or clinical population.

Our findings suggest that smartphone screen-time is an important exposure associated with worse sleep. Since poor sleep has important health consequences, further investigation to determine the causal relationship between smartphone use and sleep is necessary. This study took advantage of an app to measure smartphone screen-time, but sleep habits were measured once via a survey. Future work may benefit from using an app to collect data on nightly sleep quality. A measure of overall screen-time from multiple devices would also be helpful in this regard. Since certain activities may be more stimulating (e.g. thumbing through Facebook posts), future work might explore how screen-time, smartphone activities, and sleep interact. Ultimately, a deeper understanding of the situational and cultural factors driving smartphone use will be needed to guide studies on interventions aimed at reducing screen-time to improve sleep.

An 18-item screen time online questionnaire was created to quantify use of commonly used screen-based devices (please see Additional file 1: Screen Time Questionnaire). Five different categories of devices were created – TV, TV-connected devices (e.g. streaming devices, video game consoles), laptop/computer, smartphone, and tablet – based on the classification scheme used by publicly available reports on screen time usage among the American population [15, 23,24,25]. These categories were believed to appropriately reflect the purpose of the questionnaire, which is to quantify different forms of screen time use among American adults. For instance, it was important to differentiate between TV and TV-connected devices because of the growing trend of adults watching subscription-based video and on-demand content instead of regularly programmed television [26, 27].

Data were analyzed using the Statistical Package for the Social Sciences (SPSS) version 21.0. Because all variables under investigation were found positively skewed violating normality assumptions, even after transformation attempts, screen time variables are presented as medians and interquartile ranges. Test-retest reliability of the screen-time questionnaire was assessed via two different approaches. Relative reliability was assessed through intra-class correlation coefficients (ICCs) using a two-way mixed effects, single measurement, absolute agreement model. Values represent the following: less than 0.40 - poor reliability, between 0.40 and 0.59 – fair reliability, between 0.60 and 0.74 - good reliability, and greater than 0.75 - excellent reliability [34]. Relative reliability refers to consistency of the position of individuals in the group relative to others, and hence allows for the determination of how well participants can be distinguished from each other regardless of measurement errors [34, 35].

where σ e2 is the error variance in a repeated measures analysis of variance (ANOVA). In addition, two-sided 95% confidence intervals were estimated from the following formula:

where SSE is the sum of squares error from the repeated measures ANOVA, x2a, dfe is the chi-square value for the probability level alpha and dfe is the degrees of freedom associated with SSE. Absolute reliability or agreement refers to the consistency of scores of individuals, and therefore indicates how similar the scores for repeated measures are when measurement error (systematic and random) is present [34, 35].

I bought an older house with a basement full of screens that I couldn’t figure out how or where to install. The hardware for the old screens was installed and I had 5 new screens made for windows which had no screens.

What a great experience!!! I had been messing with these screens for almost a year with absolutely NO understanding of what went where and how to get them to stay there if I could figure out where they went! The company’s wonderful owner told me that it was unlikely that I would have a basement full of screens that wouldn’t fit somewhere (which was reassuring as it is a large home with wicket screens and the fewer I needed to make the less costly it was likely to be!) We made an appointment for the following Tuesday for which the technichian (Davin – a real jewel) arrived promptly. Davin got all of the screens out of my basement and started measuring screens and windows. He was able to match up all of the wicket screens with the windows. I got busy and got the gunk off the screens while he made screens for the 3 regular and one wicket screen that I wanted to place immediately as well as drilling a couple of holes for the hardware to hold the wicket screens in place that somehow weren’t there previously. Yippee! Now when I get a warm day, I can open the windows without being invaded by bugs (BIG YUCK!) He was clean, fast, helpful and did his job! In fact, he got extra points for 1) picking up a giant bee from my dining room floor with a cup I gave him and putting it outside (to say that I am particularly freaked out about stinging bugs is an understatement!!!) Thank you again, Davin! Additionally, he was really kind with regard to my dogs. My grandpuppy is AFRAID of people wearing hats (not just strangers, she’s scared of us when we wear hats too). I told Davin that I would appreciate his leaving his cap outside so that she would just do the normal greeting barking and not be afraid. He took off his hat and she reacted to him peacefully. The other dogs thought he was great too, but they would have liked him whether or not he was wearing a hat!! The screens he made were perfect. The overall experience was a joy! I would NEVER use anyone else to work on my screens!!!

Over the past 20 years, cell phones have evolved from simple devices made for mobile calling to smartphones that serve as mini computers. As phones got smarter, so did their screens. Take a journey back in time to see how modern phone displays came to be.

In 1992, 8 years before the new millennium, IBM debuted the first smartphone: the Simon Personal Communicator. It featured a black-and-white 160 x 293 LCD touchscreen measuring 4.5 inches by 1.4 inches. In fact, Simon is believed to be the first commercially available phone with a touchscreen, and it came with a stylus for streamlined navigation.

For the rest of the 1990s and into the 2000s, black-and-white passive matrix screens were the norm. The rows and columns combined to create text, giving off a blocky appearance.

In 2001, Nokia released the first smartphone to feature a monochromatic display. The Nokia 8250 allowed users to change the background from gray to a bright blue. That same year, the Sony Ericsson T68m and Mitsubishi Trium Eclipse were released, offering 256 colors.

Released in June 2007, the iPhone introduced many firsts. It was the first phone with an operating system, responsive touchscreen, and touch interface that replaced the traditional QWERTY keyboard. The phone screen itself comprised a video graphic array (VGA) display and offered a resolution of 320 x 480 – far exceeding other phones at the time.

Let’s start with LCDs. TFT LCD displays are considered the most common. They deliver quality images and higher resolutions. IPS LCDs, which are mainly found in higher-end smartphones, offer improved battery life and deliver wider viewing angles. These types of displays are often found in iPhones, but by Apple’s proprietary names, “Retina,” or “Super Retina.” Then, there are capacitive touchscreen LCDs, which rely on the touch of a human finger for input.

OLEDs are considered an up-and-coming display technology – they don’t require any backlighting to display pixels. Fundamentally, each pixel emits it own light, allowing for darker blacks and brighter whites. AMOLEDs combine a TFT display with an OLED display for energy savings, while Super AMOLED displays deliver even brighter screens and more power savings.

When choosing a new Net10 phone, you may feel overwhelmed with all the display options available. First, consider the phone screen size. The bigger the phone screen, the bigger the phone. If you’d like to be able to slip your phone easily inside a pocket or purse, opt for a smaller phone size, such as 4-inch, 4.7-inch, or 5-inch. If you’d prefer a bigger screen size for gaming or watching videos, you’ll benefit from choosing a phone with a 5.5-inch, 6.4-inch, or similar size.

Next, you’ll need to consider the display technology. OLED screens are known for their faster response times, better contrast, and longer battery lives. LCD screens, on the other hand, are better for outdoor viewing, deliver a natural color reproduction, and offer sharper images.

Use a Stocks widget to check stocks at a glance on your iPhone Home Screen. You can choose the size of the Stocks widget and the amount of information the widget displays—choose one of the options to monitor several symbols, or the option to monitor the performance of a single symbol. See Add widgets on iPhone.

StayFree - Screen Time & Limit App Usage is a self control, productivity and phone addiction controller app that allows you to show how much time you spend on your smartphone and helps you focus by restricting the usage of apps. You can set usage limits for your apps and receive alerts when exceeding those usage limits. You can also view the details of your usage and statistics on your usage history.

LED is the brightest display technology, making it the clear choice for outdoor solutions. Video wall brightness is measured in nits. The higher nit rating, the higher the brightness. Outdoor panels require a minimum brightness rating of 5,000 nits to allow for visibility under direct sunlight, and can reach as high as 10,000+ nits.

An LED panel’s resistance to nature’s elements is measured with its IP rating. An IP rating (short for ingress protection rating) is written as “IP” followed by 2 digits. The first digit indicates the panel’s protection against solids (such as dirt and dust), and the second indicates protection against liquid (such as rain).

Pixel pitch is the unit of measurement for how tightly packed together these pixels are. Pixel pitch is the distance, in millimeters, between the center of 2 pixels on an LED panel. Pixel pitch is often written as P(number). For example, a P10 screen would have a pitch of 10mm, meaning that the pixels are spaced 10 millimeters apart from each other.

Video wall panels are usually between 1 and 4 square meters in size. The bigger the screen, the more panels required to form the display. Farther away viewing distances require larger sizes. When determining the size of your video wall, it is important to factor in viewing distances, budget, and the look and feel that you would like to capture.

The aspect ratio of a screen is a measurement of a screen’s proportion of its width to its height. A screen with a 1:1 or square aspect ratio would have a width equal to its height. A 2:1 aspect ratio screen would have a width of double its height, and so-on. The standard aspect ratio of most video is 16:9.