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With the developments of e-commerce markets, novel recommendation technologies are becoming an essential part of many online retailers’ economic models to help drive online sales. Initially, the purpose of this paper is to undertake an investigation of apparel recommendations in the commercial market in order to verify the research value and significance. Then, this paper reviews apparel recommendation techniques and systems through academic research, aiming to acquaint apparel recommendation context, summarize the pros and cons of various research methods, identify research gaps and eventually propose new research solutions to benefit apparel retailing market.

This study utilizes empirical research drawing on 130 academic publications indexed from online databases. The authors introduce a three-layer descriptor for searching articles, and analyse retrieval results via distribution graphics of years, publications and keywords.

This study classified high-tech integrated apparel systems into 3D CAD systems, personalised design systems and recommendation systems. The authors’ research interest is focussed on recommendation system. Four types of models were found, namely clothes searching/retrieval, wardrobe recommendation, fashion coordination and intelligent recommendation systems. The forth type, smart systems, has raised more awareness in apparel research as it is equipped with advanced functions and application scenarios to satisfy customers. Despite various computational algorithms tested in system modelling, existing research is lacking in terms of apparel and users profiles research. Thus, from the review, the authors have identified and proposed a more complete set of key features for describing both apparel and users profiles in a recommendation system.

Based on previous studies, this is the first review paper on this topic in this subject field. The summarised work and the proposed new research will inspire future researchers with various knowledge backgrounds, especially, from a design perspective.

A large-scale detection system with more data in short time bins, small dead space and small signal identification is the ideology the scientists pursuing. These proposed demands are able to be solved by 2.5 D integration. The substance of a 2.5 D integration is called silicon interposer, which consists of the through silicon via (TSV) and redistribution layer. However, the state-of-the-art silicon interposer is not able to sustain its own mechanical strength with the detector/readout array often sitting as standalone in large science facilities and fails to reduce the expansions on the installation of the components due to its insufficient thickness and size. This study aims to propose a moderation of current interposer with large-sized, standalone properties.

This paper proposes an interposer based on double-sided silicon vias (DSSVs) interconnection. Unlike conventional interposer that is interconnected by TSVs, DSSVs interposer is interconnected by top vias (T-vias) and bottom vias (B-vias).

The fabrication process of DSSVs interposer is introduced, and the superiority of the double-sided interconnection process with two etch-stop layers is described in detail. The impact of different T-vias depth on DSSVs interconnections in the same wafer is discussed and two times PI opening processes are proposed to eliminate air bubbles in the B-via. The relationship between the interposer thickness and warpage is studied by finite element analysis simulation and experiment. The prototype of the DSSVs interposer with a size of 100  × 100 mm and a thickness of 318.2 µm is fabricated, and electrical tests including short tests and continuity tests are carried out.

This paper proposes a large-sized and stand-alone interposer based on DSSVs interconnection.