Enhancing the employability of fashion students through the use of 3D CAD

The textile and apparel industry has one of the longest and most intricate supply chains within manufacturing. Advancement in technology has facilitated its globalisation, enabling companies to span geographical borders. This has led to new methods of communication using electronic data formats. Throughout the latter part of the 20th Century, 2D CAD technology established itself as an invaluable tool within design and product development. More recently 3D virtual simulation software has made small but significant steps within this market. The technological revolution has opened significant opportunities for those forward thinking companies that are beginning to utilise 3D software. This advanced technology requires designers with unique skill sets. This paper investigates the skills required by fashion graduates from an industry perspective. To reflect current industrial working practices, it is essential for educational establishments to incorporate technologies that will enhance the employability of graduates. This study developed an adapted action research model based on the work of Kurt Lewin, which reviewed the learning and teaching of 3D CAD within higher education. It encompassed the selection of 3D CAD software development, analysis of industry requirements, and the implementation of 3D CAD into the learning and teaching of a selection of fashion students over a three year period. Six interviews were undertaken with industrial design and product development specialists to determine: current working practices, opinions of virtual 3D software and graduate skill requirements. It was found that the companies had similar working practices independent of the software utilised within their product development process. The companies which employed 3D CAD software considered further developments were required before the technology could be fully integrated. Further to this it was concluded that it was beneficial for graduates to be furnished with knowledge of emerging technologies which reflect industry and enhance their employability skills

Determination of the Argon Spectral Function From (e, e\u27p) Data

The E12-14-012 experiment, performed in Jefferson Lab Hall A, has measured the (e,e′p) cross section in parallel kinematics using a natural argon target. Here, we report the full results of the analysis of the data set corresponding to beam energy 2.222 GeV, and spanning the missing momentum and missing energy range 15 ≲ pm ≲ 300  MeV /c and 12 ≲ Em ≲ 80  MeV. The reduced cross section, determined as a function of pm and Em with ≈ 4% accuracy, has been fitted using the results of Monte Carlo simulations involving a model spectral function and including the effects of final state interactions. The overall agreement between data and simulations turns out to be quite satisfactory (χ2/d. o. f. =1.9). The resulting spectral function will provide valuable new information, needed for the interpretation of neutrino interactions in liquid argon detectors

Measurement of the Ar(e, e\u27 p) and Ti(e, e\u27 p) Cross Sections in Jefferson Lab Hall A

The E12-14-012 experiment, performed in Jefferson Lab Hall A, has collected exclusive electron-scattering data (e, e\u27p) in parallel kinematics using natural argon and natural titanium targets. Here we report the first results of the analysis of the data set corresponding to beam energy 2222 GeV, electron scattering angle 21.5 degrees, and proton emission angle -50°. The differential cross sections, measured with ≈ 4% uncertainty, have been studied as a function of missing energy and missing momentum, and compared to the results of Monte Carlo simulations, obtained from a model based on the distorted-wave impulse approximation

Automatically Improving Constraint Models in Savile Row through Associative-Commutative Common Subexpression Elimination

When solving a problem using constraint programming, constraint modelling is widely acknowledged as an important and difficult task. Even a constraint modelling expert may explore many models and spend considerable time modelling a single problem. Therefore any automated assistance in the area of constraint modelling is valuable. Common sub-expression elimination (CSE) is a type of constraint reformulation that has proved to be useful on a range of problems. In this paper we demonstrate the value of an extension of CSE called Associative-Commutative CSE (AC-CSE). This technique exploits the properties of associativity and commutativity of binary operators, for example in sum constraints. We present a new algorithm, X-CSE, that is able to choose from a larger palette of common subexpressions than previous approaches. We demonstrate substantial gains in performance using X-CSE. For example on BIBD we observed speed increases of more than 20 times compared to a standard model and that using X-CSE outperforms a sophisticated model from the literature. For Killer Sudoku we found that X-CSE can render some apparently difficult instances almost trivial to solve, and we observe speed increases up to 350 times. For BIBD and Killer Sudoku the common subexpressions are not present in the initial model: an important part of our methodology is reformulations at the preprocessing stage, to create the common subexpressions for X-CSE to exploit. In summary we show that X-CSE, combined with preprocessing and other reformulations, is a powerful technique for automated modelling of problems containing associative and commutative constraints

Tomonaga-Luttinger parameters for quantum wires

The low-energy properties of a homogeneous one-dimensional electron system are completely specified by two Tomonaga-Luttinger parameters $K_{\rho}$ and $v_{\sigma}$. In this paper we discuss microscopic estimates of the values of these parameters in semiconductor quantum wires that exploit their relationship to thermodynamic properties. Motivated by the recognized similarity between correlations in the ground state of a one-dimensional electron liquid and correlations in a Wigner crystal, we evaluate these thermodynamic quantities in a self-consistent Hartree-Fock approximation. According to our calculations, the Hartree-Fock approximation ground state is a Wigner crystal at all electron densities and has antiferromagnetic order that gradually evolves from spin-density-wave to localized in character as the density is lowered. Our results for $K_{\rho}$ are in good agreement with weak-coupling perturbative estimates $K_{\rho}^{pert}$ at high densities, but deviate strongly at low densities, especially when the electron-electron interaction is screened at long distances. $K_{\rho}^{pert}\sim n^{1/2}$ vanishes at small carrier density $n$ whereas we conjecture that $K_{\rho}\to 1/2$ when $n\to 0$, implying that $K_{\rho}$ should pass through a minimum at an intermediate density. Observation of such a non-monotonic dependence on particle density would allow to measure the range of the microscopic interaction. In the spin sector we find that the spin velocity decreases with increasing interaction strength or decreasing $n$. Strong correlation effects make it difficult to obtain fully consistent estimates of $v_{\sigma}$ from Hartree-Fock calculations. We conjecture that v_{\sigma}/\vf\propto n/V_0 in the limit $n\to 0$ where $V_0$ is the interaction strength.Comment: RevTeX, 23 pages, 8 figures include

Subjective Cognitive Decline in Older Adults: An Overview of Self-Report Measures Used Across 19 International Research Studies

Research increasingly suggests that subjective cognitive decline (SCD) in older adults, in the absence of objective cognitive dysfunction or depression, may be a harbinger of non-normative cognitive decline and eventual progression to dementia. Little is known, however, about the key features of self-report measures currently used to assess SCD. The Subjective Cognitive Decline Initiative (SCD-I) Working Group is an international consortium established to develop a conceptual framework and research criteria for SCD (Jessen et al., 2014, Alzheimers Dement 10, 844-852). In the current study we systematically compared cognitive self-report items used by 19 SCD-I Working Group studies, representing 8 countries and 5 languages. We identified 34 self-report measures comprising 640 cognitive self-report items. There was little overlap among measures- approximately 75% of measures were used by only one study. Wide variation existed in response options and item content. Items pertaining to the memory domain predominated, accounting for about 60% of items surveyed, followed by executive function and attention, with 16% and 11% of the items, respectively. Items relating to memory for the names of people and the placement of common objects were represented on the greatest percentage of measures (56% each). Working group members reported that instrument selection decisions were often based on practical considerations beyond the study of SCD specifically, such as availability and brevity of measures. Results document the heterogeneity of approaches across studies to the emerging construct of SCD. We offer preliminary recommendations for instrument selection and future research directions including identifying items and measure formats associated with important clinical outcome