**3. Intellectual property rights — Its aims and relevance**

Forms of intellectual property rights (IPR) are copyright, trademark (including service mark and geographical indication), trade secret, and patent. Depending on the type, government granted rights enable owners to select who may access and use their property and to protect it against infringement. Since the protections granted by a government vary from jurisdiction to jurisdiction, the acquisition, registration, or enforcement of IPR must be pursued or obtained separately in each territory of interest. Intellectual properties, in general, are creative ideas and expressions of the human mind that have commercial value. The owner of an intellectual property can generally transfer (with or without consideration), license (or rent), or mortgage it to third parties. Most exclusive rights are nothing more than the right to sue an infringer. Those wishing to use an intellectual property held by another, must license it from the owner. In many jurisdictions the law places limits on the restrictions the licensor can impose on the licensee.

A *license* results if the IP owner transfers less than all of his IP rights. The party receiving the license is called the licensee. If the license is given to only a single person and pursuant to the terms of the license is not permitted to license others, the license is termed an *exclusive license*. If licenses are given to multiple parties or to one person reserving the right to license it to others at a future date, the license is termed a *nonexclusive license*. In the case of an exclusive license, the owner of the intellectual property cannot make, use, or sell the intellectual property unless he has expressly reserved the right to do so in the license agreement. If all the rights are transferred to someone, it is known as an *assignment*. Variations in the terms of a license agreement are virtually limitless, depending upon the needs, desires, and bargaining positions of the parties involved.

#### **3.1. Copyright**

organism's genome can be cut at any desired location. Since its invention in 2012, the CRISPR/ Cas system has been widely used for gene editing (silencing, enhancing or changing specific genes) in basic research. The importance of the CRISPR/Cas adaptive immune system is that it is a prokaryotic immune system that confers resistance to foreign genetic elements such as plasmids and phages and provides a form of acquired immunity. CRISPR spacers recognize and silence these exogenous genetic elements like RNAi in eukaryotic organisms. It is in building the elaborate system of DNA-cutting proteins and guide RNA sequences that requires extensive engineering to function in eukaryotic cells, and to insert new genes where the targeted host DNA is excised. For a quick introduction to CRISPR technology, see [22].

On 15 April 2014, the USPTO issued the first patent (US8697359, CRISPR-Cas systems and methods for altering expression of gene products) to cover CRISPR-Cas9 gene editing technology to Feng Zhang, the sole inventor, just six months after the patent application was filed on 15 October 2013. The patent is assigned to MIT, and the Broad Institute with Broad managing the patent's licensing. The patent claims a modified version of the CRISPR-Cas9 system that is found naturally in bacteria and which microbes use to defend themselves against viruses. The patent, *inter alia*, claims methods for designing and using CRISPR's molecular components. It is widely expected that Broad will adopt a liberal licensing policy that would

CRISPR is already revolutionizing biomedical research because it provides a very efficient way of recreating disease-related mutations in lab animals and cultured cells. It also holds the promise of treating genetic diseases in humans in unprecedented ways, *e.g.*, by directly correcting mutations on a patient's chromosomes. Mental illnesses too may find similar remedies. Since 2012, CRISPR's use in research has spread like wildfire. The chemistry behind

The first generation DNA sequencing developed in 1975 by Edward Sanger [23] remained the gold-standard for two and a half decades. It was used in the Human Genome Project that cost \$3 billion and 13 years to sequence the human genome and was completed in 2003. In com‐ parison, next-generation sequencing (NGS) use non-Sanger based, high-throughput technol‐ ogies to sequence millions and billions of DNA strands in parallel, are much faster and cheaper. In fact, an entire genome can be sequenced in a day. And when it is coupled with powerful computational algorithms, say, to answer questions related to mutational spectrum of an organism on a genome-wide scale, we have phenomenal opportunities to understand our biological selves. Targeted sequencing facilitates discovery of disease causing mutations for diagnosis of pathological conditions, and of genes and regulatory elements associated with disease [24, 25]. For trends in DNA sequencing costs, see http://www.genome.gov/sequen‐ cingcosts/. (In 2014, it was less than \$0.1 per raw mega-base of DNA sequence compared to about \$1k in 2004; during 2007-2010, the cost fell sharply.) NGS is not yet ready for clinical use. For recent advances in CRISPR-Cas9 technology see [26]. In principle, NGS and CRISPR technology together would allow one to change a genome at will to almost anything one wants and even elicit enough detailed information about disease risks, ancestry

make the technology available to scientists for research around the world.

the Cas9 protein is still being explored.

**2.4. NGS + CRISPR technologies**

200 Biotechnology

Copyright is an exclusive right conferred by a government on the creator of a work (*e.g.*, original literary, dramatic, musical, artistic works in books, recordings, films, videos, etc.) to exclude others from reproducing it, distributing it to the public, performing it in public, or displaying it in public. Copyright law protects the holder's right to decide how and where his material is used, not just the right to earn profits from the work. Copyright protection comes into effect immediately upon the creation of something that can be protected and is 'fixed' in some way, *e.g.*, on paper, on film, on electronic media (including the Internet), etc. It is not necessary to register a copyright or take any official action to obtain it. However, registration is advisable as it strengthens the owners claim to copyright in litigation. The doctrine of fair use allows non-owners of a copyright work to use such work in a limited way without being accused of infringement.

Things that cannot be copyrighted include abstract ideas, procedures, processes, systems, methods of operations, concepts and principles, regardless of how they are expressed, whether it be by words, illustration, or in some three-dimensional form. Of course, the manner in which they are expressed may be copyrighted, but not the labour that goes into creating a work. Unfortunately, the line between copyrighted material and non-copyrightable ideas, wherever it is drawn, will seem arbitrary to many.

#### **3.2. Trademark and other marks**

A mark used in trade—trademark, service mark, certification mark, collective mark, geo‐ graphical indication—is any sign which can distinguish the goods and services, as appropriate, of one trader from those of another. A mark may be words, logos, pictures, shape of a product or container, or a combination of these. (Certain kinds of marks are not permitted, *e.g.*, marks which are immoral, deceptive, or scandalous, national symbols, national flags, etc.) A trade‐ mark serves to identify the origin of goods and creates goodwill for the owner; it signifies that all goods bearing the mark come from or are controlled by a single source and are of specified quality.

#### **3.3. Trade secret**

It is any device or information that gives an advantage over competitors who do not know about it or do not use it. Its value lies in its secrecy. Its owner is responsible for protecting it (*e.g.*, through non-disclosure agreements, by restricting access, etc.). Infringement of a trade secret is a type of unfair competition. The subject matter of trade secrets usually includes sales methods, distribution methods, consumer profiles and advertising strategies, lists of suppliers and clients, and manufacturing processes. The Coca Cola recipe is a famous example of a trade secret. What information constitutes a trade secret is case specific. Unfair practices related to trade secrets obviously include industrial or commercial espionage, breach of contract, and breach of confidence.

#### **3.4. Patent**

A patent is a limited period monopoly property right granted to an inventor for his invention by a Government subject to prescribed conditions, which include that the invention must be novel, nonobvious to those ordinarily skilled in the art, useful, and fully disclosed. Four types of inventions are eligible for such utility patents: process, machine, manufacture, or composi‐ tion of matter. They are known as statutory subject matter. In exchange of a patent, the inventor describes the secrets related to the invention, publishing them as per law for all to see, absorb, and improve upon but not infringe. This description must be so clear and detailed as to enable a person skilled in the technologies relevant to the said invention to independently reproduce the invention (enablement requirement) without undue extra-solution activity, such as further research, data gathering, etc. on his part. In fact, this description should leave no doubt that the patent applicant was in possession of the claimed invention at the time of filing his application. Patents may be sought on non-trivial improvements over existing inventions. The life of a granted patent is usually 20 years from the filing date of the first valid patent appli‐ cation claiming the invention.

material is used, not just the right to earn profits from the work. Copyright protection comes into effect immediately upon the creation of something that can be protected and is 'fixed' in some way, *e.g.*, on paper, on film, on electronic media (including the Internet), etc. It is not necessary to register a copyright or take any official action to obtain it. However, registration is advisable as it strengthens the owners claim to copyright in litigation. The doctrine of fair use allows non-owners of a copyright work to use such work in a limited way without being

Things that cannot be copyrighted include abstract ideas, procedures, processes, systems, methods of operations, concepts and principles, regardless of how they are expressed, whether it be by words, illustration, or in some three-dimensional form. Of course, the manner in which they are expressed may be copyrighted, but not the labour that goes into creating a work. Unfortunately, the line between copyrighted material and non-copyrightable ideas, wherever

A mark used in trade—trademark, service mark, certification mark, collective mark, geo‐ graphical indication—is any sign which can distinguish the goods and services, as appropriate, of one trader from those of another. A mark may be words, logos, pictures, shape of a product or container, or a combination of these. (Certain kinds of marks are not permitted, *e.g.*, marks which are immoral, deceptive, or scandalous, national symbols, national flags, etc.) A trade‐ mark serves to identify the origin of goods and creates goodwill for the owner; it signifies that all goods bearing the mark come from or are controlled by a single source and are of specified

It is any device or information that gives an advantage over competitors who do not know about it or do not use it. Its value lies in its secrecy. Its owner is responsible for protecting it (*e.g.*, through non-disclosure agreements, by restricting access, etc.). Infringement of a trade secret is a type of unfair competition. The subject matter of trade secrets usually includes sales methods, distribution methods, consumer profiles and advertising strategies, lists of suppliers and clients, and manufacturing processes. The Coca Cola recipe is a famous example of a trade secret. What information constitutes a trade secret is case specific. Unfair practices related to trade secrets obviously include industrial or commercial espionage, breach of contract, and

A patent is a limited period monopoly property right granted to an inventor for his invention by a Government subject to prescribed conditions, which include that the invention must be novel, nonobvious to those ordinarily skilled in the art, useful, and fully disclosed. Four types of inventions are eligible for such utility patents: process, machine, manufacture, or composi‐ tion of matter. They are known as statutory subject matter. In exchange of a patent, the inventor

accused of infringement.

202 Biotechnology

it is drawn, will seem arbitrary to many.

**3.2. Trademark and other marks**

quality.

**3.3. Trade secret**

breach of confidence.

**3.4. Patent**

Patent monopoly differs from market monopoly; a patent is a right to exclude, a right to prevent trespassing. In this sense it is similar to, say, the right to keep one's personal properties free from trespassers. A patent grants its owner the right to exclude others from making, using, selling or offering to sell, and importing the claimed invention in the country of grant; it does not confer any right to practice the invention. This is because in practicing the invention, one may well need complementary patents held by others unwilling to license or there may be other laws, rules or regulations that prevent its practice. Patents are issued only to the first inventor (or group of joint inventors) of an invention who files a legally valid patent applica‐ tion; all others are barred, even if they independently created the invention. Consequently, those other inventors must get a license from the first inventor if they wish to practice the invention. Although grant of patents is subject to country-specific constraints, there is univer‐ sal agreement among nations that patents seeking pre-emptive monopoly of abstract ideas (*e.g.*, mathematical formulas), laws of nature, natural phenomena, and products of nature are ineligible. What else to exclude from patent monopoly is a national prerogative, largely dependent on government policy related to prevailing socio-economic conditions it must manage, and international treaty obligations.

Two recent rulings by the Supreme Court of the United States (SCOTUS) are of importance to the biotechnology industry since it invokes the dictum that "laws of nature, natural phenom‐ ena and abstract ideas" are not patentable. In March 2012, the court ruled against Prometheus Laboratories in California observing that it could not patent metabolite levels to guide drug dosing [28]. Then, in June 2013, the court struck down a patent claim by Myriad Genetics of Utah that linked certain DNA sequences to female breast cancer [29]. It held that a naturally occurring DNA segment is a product of nature and its mere isolation does not make it patentable. However, cDNA may be patentable as it is not a naturally occurring substance. Thus to get a gene patent one will have to show that it is significantly different from any natural gene. However, in a diametrically opposite ruling, the Federal Court of Australia in *D'Arcy v Myriad Genetics Inc.* [2014] FCAFC 115 on 05 September 2014 ruled unanimously that isolated DNA and RNA are patentable subject matter under Australian law (Patents Act 1990 (Cth) s 18(1), Statute of Monopolies s 6). To say the least, this makes gene patenting a complex issue if such patents are sought in multiple countries.

Governments grant patents to human inventors only. Post-grant they may be assigned to people or institutions. A patent granted by a government is enforceable only in the territory it governs. One may, however, seek patents for the same invention from multiple countries. Patent laws of a country do not over-ride its other laws that might regulate the invention's use. Patent laws of a country may take into account moral, cultural, ethical, social, environmental, or scientific concerns of society. Patent rights may be exercised by the patentee, his heirs or assigns. When a patent expires, the related invention becomes the common heritage of mankind.

Limited period patent monopoly may provide an enormous first mover advantage to an entrepreneur, especially if it involves new technology that could lead to a natural monopoly.

#### **3.5. Traditional knowledge**

The World Health Organisation (WHO) defines traditional medicine as [30]:

Traditional medicine is the sum total of the knowledge, skills, and practices based on the theories, beliefs, and experiences indigenous to different cultures, whether explicable or not, used in the maintenance of health as well as in the prevention, diagnosis, improvement or treatment of physical and mental illness.

This knowledge, much of it undocumented and available only to small groups of people through oral transmission from generation to generation, predates molecular biology by centuries and hence belongs to prior art (public domain). Its importance to synthetic biology is that such knowledge may provide promising directions of research in the hunt for exotic genes.


**4.1 Stress analysis**

The full 3-D FE models of the anode (50:50 NiO:YSZ weight percentage composition) and cathode (50:50 LSM:YSZ weight percentage composition) are shown in Figure 7. The FE anode model consists of 406,465 elements and 473,181 nodes. The cathode model has 244,584 elements and 395,131 nodes.

Fig. 7. Three-dimensional FE models of anode (left) and cathode (right)


*Edited by David Wagner*

This book is a compilation of reviews about the complication of Type 1 Diabetes. T1D is a classic autoimmune disease. Genetic factors are clearly determinant but cannot explain the rapid, even overwhelming expanse of this disease. Understanding etiology and pathogenesis of this disease is essential. The complications associated with T1D cover a range of clinical obstacles. A number of experts in the field have covered a range of topics for consideration that are applicable to researcher and clinician alike. This book provides apt descriptions of cutting edge technologies and applications in the ever going search for treatments and cure for diabetes.

ISBN 978-953-307-788-8

Type 1 Diabetes Complications

Photo by Shutterstock


**5. Regulation of the secretions of the definitive and foetal areas in the adrenal gland**

Both the foetal and the definitive areas of the adrenal gland are stimulated by ACTH and αmelanocyte stimulating hormone (MSH). Both hormones are secreted by the foetal pituitary gland [16, 35]. As possible stimulators of the adrenal gland, angiotensin, prolactin, growth hormone (GH) and epidermal growth factor have also been suggested. Progesterone and deoxycorticosterone secretions decrease as pregnancy goes by, suggesting that the enzymatic systems for their transformation into aldosterone and cortisol become active, as these hormones levels increase at the end of pregnancy.

With respect to the medulla secretions, it is known that the corticosterone synthesized *in situ* by the foetus is required for negative feedback suppression of the hypothalamus-pituitaryadrenal axis and for catecholamine synthesis in adrenal medulla [36]. In addition, the maternal catecholamines can go across the placenta [16].


**4. Biomechanics**

The biomechanistic aspect of head trauma is composed of two forces: translation or linear (LA) and rotational (RA) accelerations. The former results from direct impact measured in gravitational force unit (g), whilst the latter results from indirect or whiplash impact and is measured as radians per second squared (rad/s2 ). Upon sudden impact with a surface, the head experiences deformation and deceleration in the same direction as the initial force and result in LA. The bending of the skull produces a wave-like pattern which causes tension propagating from the outer to inner skull. Tension propagation magnitude and direction determine the ensuing fracture initiation.

Intracranial damage occurs as a consequence of either brain motion or pressure gradient established by the LA. Brain motion is proposed to potentiate focal hematoma directly. Other authors proposed that the focal site of an impact is exposed to positive gradient resulting in focal injury and the distal site is exposed to negative gradient resulting in shear stress and cavitation. Previous researches reported a strong correlation between LA and ICP, and ICP with subsequent neurologic dysfunction.

Holbourn was the pioneer researcher who stated that RA-mediated brain injury was caused by shear stress and strain. Impact duration should also be taken into account as different combinations of impact duration and magnitude result in different injury types. Longer duration at a lower magnitude of RA generates diffuse axonal injury, and the opposite generates subdural hematoma. Although LA and RA are often described separately, the inherent coupling of both forces is inevitable in reality [16, 17].


*Article* **New Unequal Error Protection Strategy for Image Transmission Based on Bilayer-Lengthened PLDPC Code in Half-Duplex Relay System**

**Tian Gao 1, Min Xiao 1,\*, Pingping Chen 2,\* and Diyan Gao 3**

**Abstract:** To reduce the waste of energy in communications, unequal error protection (UEP) is used to provide asymmetric protection for messages with different levels of importance. This paper proposes new efficient strategies of UEP based on bilayer protograph-based low-density parity check (PLDPC) codes in decoding-and-forward (DF) relay systems. In particular, we jointly utilize source coding and channel coding to design UEP strategies and then save transmission energy. According to the different levels of importance of discrete cosine transform (DCT) coefficients of image and variance statistical characteristics of image sub-blocks, bilayer-lengthened PLDPC codes are exploited to protect the transmitted image information with different importance levels at the half-duplex relay system. In the end, the simulation result shows that the proposed UEP schemes achieve excellent performance gains compared to conventional equal error protection (EEP) scheme. Additionally, the complexity analysis of the UEP strategies is given.

**Keywords:** bilayer PLDPC; unequal error protection; joint source-channel coding; image segment

#### **1. Introduction**

In recent years, many research activities both on the coding and decoding of cooperative communication schemes have attracted a lot of attention [1–3]. Relay co-operative communication has won increasingly broad applications for its high ability of anti-fading in wireless multi-path channels, improving the reliability of information transmission [4,5]. Since the wireless co-operation communications utilize additional relay nodes, the cost of energy increases accordingly. Thus, improving the energy efficiency is one of the important issues in this co-operation system. Reference [6] considered the joint utility-based uplink power and rate allocation to raise the efficiency of energy in communication, and reference [7,8] studied the performance of resource allocation in non-orthogonal multiple access- (NOMA) based networks to solve the efficiency maximization problem of the downlink NOMA-based, massive multiple-input-multiple-output (MIMO) system.

As information is becoming more diversified and complicated, distinguishing information of different importance levels and providing asymmetric protection is essential to cater to the requirements of high performance and low transmission power nowadays. Reference [9] proposed a concept of unequal error protection (UEP) for channel coding that reduces energy consumption by providing different levels of protection for information with different levels of importance. Reference [10] presented rate allocation optimization algorithms based on rate-compatible codes for embedded image bit streams transmitted over noisy channels under UEP. Reference [11] proposed a UEP scheme by tracing the mapping between the important information data and the elite bits of an irregular LDPC code.

**Citation:** Gao, T.; Xiao, M.; Chen, P.; Gao, D. New Unequal Error Protection Strategy for Image Transmission Based on Bilayer-Lengthened PLDPC Code in Half-Duplex Relay System. *Symmetry* **2022**, *14*, 1662. https://doi.org/ 10.3390/sym14081662

Academic Editor: Dumitru Baleanu

Received: 6 July 2022 Accepted: 3 August 2022 Published: 11 August 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Reference [12] proposed a good tradeoff UEP-scheme between reliability and spectrum efficiency by using sixteen quadrature amplitude modulation (QAM) mapping. Reference [13] realized UEP by classifying the bit-channel type based on the delayed bit-interleaved coded modulation (DBICM). Reference [14] took advantage of the adaptive segmentation and weight-increase parity check (WIPC) LDPC code to achieve UEP for image sources. A UEP scheme based on the Luby transform (LT) codes was proposed in [15] for image transmission over multiple-input-multiple-output (MIMO) channels. Reference [16] presented a novel autoencoder-based approach for designing codes that provide UEP capabilities, and reference [17] proposed a type-aware coding approach to achieve UEPs for multiple classes of messages.

In this paper, we design two UEP strategies based on bilayer protograph-based LDPC (PLDPC) codes in a half-duplex relay system. PLDPC code is a subclass of LDPC codes [18,19], which benefit from simple structures and desirable performance in wireless applications [20–25]. Bilayer PLDPC code was put forward in decoding-and-forward (DF) relay systems. It is an especially useful class of structured LDPC codes and more general multi-layer codes and allows decoding of the same codeword with two (or more) different decoders [26–28]. We find that most existing UEP strategies focused on the implementation of channel coding without considering the characteristics of the source, and the optimization methods of these UEP-based codes are relatively complex. Thus, to address this issue, we exploit lengthened bilayer-lengthened PLDPC codes in UEP to transmit the information of different source characteristics. Bilayer PLDPC code can perform remarkably in this case due to its advantages, such as low encoding complexity, modular structure for easy design, and rate compatibility. Moreover, bilayer PLDPC code under the UEP scheme in relay systems can match a set of channel conditions without extensive re-optimization. Based on this, we propose two new UEP strategies with excellent performance. The main contributions of this work are summarized as follows:

At last, the simulation results show that the proposed UEP-1 scheme has 0.8 dB and 0.3 dB gains, and the proposed UEP-2 scheme has 1.6d B and 1.1d B gains compared to EEP and the traditional UEP scheme in low and high SNR regions, respectively. Compared to the traditional UEP scheme, both UEP-1 and UEP-2 schemes can achieve better performance. Moreover, we compare the FSIM between the recovered image and the original image under different SNRs, which shows that the performance of proposed UEP scheme is superior to that of EEP scheme. The complexity analysis of UEP strategies is given by discussing the usage of modules and computing the average number of decoding iterations.

#### **2. Preliminaries and Notations**

The table of notations in this section is shown in Table 1.

**Table 1.** Notations in Section 2.

#### *2.1. Protograph LDPC Code*

Protograph LDPC codes define a subclass of multi-edge type LDPC (MET-LDPC) codes, which allow extending a base matrix or graph prototype (base graph) to a complete matrix or graph [28]. A well-designed protograph LDPC code can achieve better performance and is suitable for an efficient encoding/decoding implementation [29,30]. A protograph *B* = (V, C, E) can be represented by a tanner graph with a relatively small number of nodes, which consists of three sets, V, C and E, corresponding to *Np* variable nodes (VNs), *Mp* check nodes (CNs), and the connecting edges, respectively. Each edge *ei*,*j* ∈ E connects a VN *vj* ∈ V to a CN *ci* ∈ C. A graphical example of generating the derived graph is shown in Figure 1. An (*N*, *K*) protograph code (an equivalent LDPC code) is derived by using a process known as *lifting*, where *N* and *N* − *K* equals the number of VNs and CNS in the derived tanner graph corresponding to the base protograph graph, respectively. The *lifting* process utilizes the copy-and-permutation operation. The number of copy times is decided by the lifting factor Z =*N*/*Np* = *M*/*Mp*, where *M* = *N* − *K*.

#### *2.2. Bilayer-Lengthened PLDPC Code*

*Graph Structure*: Geometrically, the variable nodes are divided into two layers: *layer-1* and *layer-2*, and the check nodes are all in one set in a bilayer-lengthened protograph [27]. Figure 2 shows that the edges of the base graph are connected in the first layer of variable nodes with the set of check nodes forming a base graph with a lower rate. The entire edges and nodes constitute a base graph with a high rate. The rate of bilayer-lengthened PLDPC code can be increased by adding the number of variable nodes in *layer-2*.

The entire protograph base matrix has the form

$$B\_{sr} = \begin{bmatrix} B\_{sd} \vert B\_{\mathcal{C}} \end{bmatrix} \tag{1}$$

where *Bsd* is the protograph base matrix with a lower rate corresponding to *layer-1*, and *Be* is the extension base matrix corresponding to *layer-2* in the tanner graph.

**Figure 1.** A graphical example of generating the derived graph.

**Figure 2.** A tanner graph of bilayer-lengthened photograph. Black circles and circles with plus represent VNs and CNs, respectively, and the blank circle denotes the VNs which have been punctured.

#### *2.3. Half-Duplex Relay System*

According to the classic work of Cover and EI Gamal [31], DF protocol describes that the relay completely decodes the transmitted message from the source and partially forwards the decoded message to the destination. In the destination, the receiver recovers the message by processing the signals transmitted by the source and relay. Half-duplex relay system is widely studied system in practice. This paper exploits the novel UEP scheme for the half-duplex relay system, where the relay can communicate with only one node in a time slot. According to [31] and Figure 3, the received signal in a half-duplex relay channel can be given by

$$V\_1 = h\_2 X\_1 + Z\_{sr} \tag{2}$$

$$Y\_1 = h\_1 X\_1 + Z\_{d1} \tag{3}$$

$$Y\_2 = h\_1 X\_2 + h\_3 L\_2 + Z\_{d2} \tag{4}$$

where *X*1, *Y*1, and *V*1 denote the transmitted signal from a source (**S**), the received signal in the destination (**D**), and the relay (**R**) during time slot one (a fraction *t*1 of the transmission interval), respectively. *X*2, *L*2, and *Y*2 denote the transmitted signals from source, relay, and the received signals in the destination during time slot two (a fraction *t*2 = 1 − *t*1), respectively. *h*1, *h*2, and *h*3 are **S**-to-**D**, **S**-to-**R,** and **R**-to-**D** channel coefficients, respectively. *Zsr* ∼ *N*(0, *σsr*), *Zd*1 ∼ *N*(0, *σsd*), and *Zd*2 ∼ *N*(0, *σsr* + *σrd*) denote additive Gaussian noises at the relay and at destination for time slot one and time slot two, respectively. In time slots one and two, the communication channel can be seen as a broadcast channel and a multi-access channel, respectively. The source has power constraint *PS*1 = *E X*2 1 in time slot one and power constraint *PS*2 in time slot two. *PR*2 represents relay power constraint in time slot two. Thus, signal-to-noise ratios (SNR) *SNRSR*, *SNRSD*, and *SNRRD* can be defined at the relay and destination at time slot one and at the destination at time slot two, respectively.

**Figure 3.** Half-duplex relay channel.

#### **3. New UEP Strategy**

#### *3.1. UEP System Model*

For practical purposes, we consider gray images as research objects for the UEP strategy in this paper. A new UEP scheme (UEP-1) system model in a half-duplex relay system is shown in Figure 4. After block discrete cosine transform (DCT) [32,33] processing of the input image, we found that each DCT coefficient *Q* can be divided into two parts the integer part *Qi* and the decimal part *Qd*, where *Qd* is approximated by retaining the binary number of *k* bits. The recovery performance of the image is dependent on the size of *k*. The degradation coefficients *Q*can be represented as

$$Q' = \begin{cases} \ Q\_i + Q\_{d'} \text{ if } Q \ge 0 \\\ Q\_i - Q\_{d'} \text{ if } Q < 0 \end{cases} \tag{5}$$

where if *Q* ≥ 0, *Qi* = *Q* and *Qd* = *Q* − *Qi*; else *Qi* = *Q* and *Qd* = *Qi* − *Q*. This step not only conserves transmission quality significantly, but also facilitates the combination of image transmission and UEP strategy. *Qi* and *Qd* have different attribution to *Q*- . In binary, *Q* has a deviation of 2*i* when an error happens in the *i*-th bit of *Qi*. In contrast, only 1 2 *i* deviation in *Q* when an error happens in the *i*-th bit of *Qd*. Thus, the proposed UEP strategy provides two transmission paths for *Qi* and *Qd*. For *Qd* with less attribution to *Q*- , a traditional point-to-point channel (S-D link) coding and decoding mode is adopted. For *Qi* with much attribution to *Q*- , the relay transmits additional mutual information to help

the destination decode the source message. In the destination, estimated information *Q*"*i* and *Q*"*d* are decoded, and the estimated DCT coefficient *Q*" can be estimated by

**Figure 4.** An UEP system model based on half-duplex relay system.

At last, the image can be restored by two steps, such as inverse discrete cosine transform (IDCT) and inverse normalization.

#### Encoding/Decoding of UEP System

The encoding of the UEP strategy only needs to store the bilayer protograph base matrix *Bsr*, extending by a lower-rate bilayer protograph base matrix *Bsd*, *Bsr* = [*Bsd*|*Be* ]. The signal *i*1 of integer parts and the signal *i*2 of decimal parts are encoded by *Hsr* (*lift* from *Bsr*) to generate the codewords *x*1 and *x*2 by encoder1 and encoder2, respectively. Encoder2 sends the codeword *x*2 = *GT sri*2 to the destination, and encoder1 broadcasts the codeword *x*1 = *GT sri*1 to relay and destination. *Gsr* is the generating matrix of parity check matrix *Hsr*. The relay encodes the syndrome *is* and transmits codeword *x*3 to the destination by

$$\mathbf{x}\_{\mathfrak{J}} = \mathbf{G}\_{sd}^{\mathrm{T}} \mathbf{i}\_{\mathfrak{s}} \tag{7}$$

where *is* = "*i* - 1*HT sd*, and "*i* - 1 is the estimated information corresponding to variable nodes in *layer-2*, which is extracted from the estimated information "*i*1. Estimated information "*i*1 have been decoded from *x*1 at the relay. *Hsd* is lifted from the base matrix *Bsd*.

Figure 5a,b show the iterative decoding factor graphs in decoder1 and decoder2. In Figure 5a, the variable nodes in *layer-2* are checked by the parity check matrix *Hsr*. The additional Log-Likelihood Ratio (LLR) of variable nodes in *layer-2* provide help for decoding the variable nodes in *layer-1.* We can see that the message from the *j*-th check node to the *i*-th variable node is

$$L(r\_{ji}) = 2 \tanh^{-1} \left( \prod\_{i' \in R(j) / i} \tanh \left( L\left(q\_{i'j}\right) / 2 \right) \right) \tag{8}$$

where *qij* is the message from *i* - -th variable node to *j*-th check node, and *i* belongs to set *R*(*j*)/*i*. The elements in *R*(*j*)/*i* can be divided into two parts corresponding to *layer-1* and *layer-2.* Compared to decoder2 in Figure 5b, decoder1 has a much more reliable message from the variables nodes that are connected to the syndrome in *layer-2.* It suggests a more reliable LLR *L*(*qi*) for the *i*-th variable node, computed by

**Figure 5.** (**a**) Factor graph for decoder1. (**b**) Factor graph for decoder2.

#### *3.2. Image Segmentation UEP Strategy*

The image segmentation UEP strategy is illustrated in Figure 6. In this diagram, the classification map is generated by K-means clustering. In the source, the classification map is used to order sub-blocks of an input image and choose bilayer matrix with different rates for sub-blocks in different classes. Integer parts of DCT coefficients are encoded by bilayer PLDPC code with a fixed rate. Decimal parts of DCT coefficients are encoded by bilayer PLDPC code with a certain rate that is chosen from the classification map. Transmission message *xs* = [*x*1, *x*2] is broadcasted to the relay and the destination in time slot 1, respectively. The relay sends the message *x*3 = *GT sdis* to destination after decoding the message *xs* and computing syndrome *is*. DCT coefficients can be recovered after decoding *x*ˆ*s* in destination. A recovery image is obtained by reordering the sub-blocks with a classification map known at the receiver. We describe the main two steps of the UEP scheme (UEP-2) in this section, such as the image segmentation and the encoding procedure.

**Figure 6.** The frame diagram of the image segmentation UEP scheme.

#### 3.2.1. Image Segmentation

To segment the original image of size (*M*, *N*) and distinguish sub-blocks of different levels of importance from all sub-blocks, we can discover the intensity of the pixel of sub-blocks change by defining the variance *σ* of the sub-blocks,

$$\sigma = \frac{\sum\_{i=1}^{m} \sum\_{j=1}^{n} \left(\mathbf{x}\_{i,j} - \overline{\mathbf{x}}\right)^2}{m \times n} \tag{10}$$

$$\overline{\mathbf{x}} = \frac{\sum\_{i=1}^{m} \sum\_{j=1}^{n} \mathbf{x}\_{i,j}}{m \times n} \tag{11}$$

where *xi*,*j* represents the value of the pixel of the sub-blocks, and *m* and *n* are the size of the sub-blocks. An original image can be segmented into *z* = *M*/*m* = *N*/*n* sub-blocks, and an array of variances *σ* = [*σ*1, *σ*2, ... , *σz*] can be computed corresponding to *z* sub-blocks. Then, the variance matrix of sub-blocks of *k* images can be represented by

$$\begin{pmatrix} \mathbf{s}\_1 & \dots & \mathbf{s}\_z \end{pmatrix} = \begin{pmatrix} \sigma\_{1,1} & \dots & \sigma\_{1,z} \\ & \ddots & \\ \sigma\_{k,1} & \dots & \sigma\_{k,z} \end{pmatrix} \tag{12}$$

where *σi*,*j* denotes the variance of the *j*-th sub-block in the *i*-th image, and column vector *sj* represents the variances of the *j*-th sub-block of all the images. The classes are developed by K-means clustering [34] to classify sub-blocks from multiple images (except for the images waiting for transmission).

#### 3.2.2. Encoding of Image Segmentation UEP Strategy

Assuming that sub-blocks of the input image are divided into four groups by classification map, for sorted sub-blocks of the input image, we match the integer parts signal *i*1 of DCT coefficients with a fixed lower-rate bilayer PLDPC code *Hsr*,1 and decimal parts signal *i*2 of DCT coefficients with diverse rates bilayer-lengthened code *Hsr*,*i*, *i* ∈ [1, 2, 3, 4], by

$$\mathbf{x}\_1 = \mathbf{G}\_{sr,1}^T \mathbf{i}\_1 \tag{13}$$

$$\mathbf{x}\_{2,i} = \mathbf{G}\_{sr,i}^T \mathbf{i}\_{2,i} \tag{14}$$

where *i*2 = [*i*2,1, *i*2,2, *i*2,3, *i*2,4] are the decimal parts of DCT coefficients after ordering all of the image sub-blocks, and *i*2,*i* corresponds to the *i*-th group that decimal parts of sub-blocks belong to. The source broadcasts codeword *xs* = [*x*1, *x*2] to the relay and destination, where *x*2 = [*x*2,1, *x*2,2, *x*2,3, *x*2,4]. *Gsr*,*i* denotes the generator matrix of the parity check matrix *Hsr*,*i* , lifting from *Bsr*,*i*. *Bsr*,*i* is a sub-protograph base matrix with a higher rate extended by

$$B\_{sr,1} = \begin{bmatrix} B\_{sd} \left| B\_{c} \right. \end{bmatrix} \tag{15}$$

$$B\_{sr,2} = \begin{bmatrix} B\_{sr,1} \vert B\_{\mathfrak{e},1} \end{bmatrix} \tag{16}$$

$$B\_{sr,i} = \left[B\_{sr,i-1}|B\_{c,i-1}\right] \tag{17}$$

As can be seen in Equations (15)–(17), diverse rates can be achieved for the decimal parts of DCT coefficients of sub-blocks with different levels of importance by the matrix expansion method, and only one base matrix *Bsr*,*i* needs to be stored. *Bsr*,*i*−1 and *Be*,*i*−1 corresponding to *layer-1* and *layer-2* are combined to create a capacity-approaching code for image transmission.

Relay decodes the codeword *xs* and extracts the second layer information ˆ*i* - 1 and ˆ*i* - 2 from *x*1 and *x*2 and then computes syndrome *is* = [*is*1|*is*2 ], *is*1 = ˆ*i* - 1*HT sd*, and *is*2 = ˆ*i* - 2*HT sd*, respectively. As shown in Figure 6, codeword *x*3 = *GT sdis* is decoded at the destination, and

the syndrome *is* is recovered during the second time slot. With the recovered syndrome, we have bilayer PLDPC codes *Hsr*,1 and *Hsr*,*i*, as shown in Figure 7. The check relationship between *layer-2* variables nodes and syndrome nodes helps the destination with forming lower rate codes to decode the codeword *xs* from the source.

**Figure 7.** The tanner graph of bilayer PLDPC codes with the syndrome. (**a**) Bilayer PLDPC codes *Hsr*,1 with the syndrome; (**b**) Bilayer PLDPC codes *Hsr*,*i* with the syndrome.

#### **4. Results**

#### *4.1. Simulation Result*

This part demonstrates the simulation performance of the proposed UEP schemes. The software and hardware platforms of simulation are C++, Matlab, Intel i7, and Nvidia 3060, respectively. The preset parameters are shown in Table 2; we compared three strategies, and the length of codes was 1296 in simulation. The first strategy (EEP) protected the integer and decimal parts of DCT coefficients of the image by the classical AR3A code with a 3/4 rate equally in the point-to-point channel (S-D link). The second strategy (UEP-1) provided UEP for the integer and decimal parts of DCT coefficients of the image. The integer and decimal parts were encoded by bilayer-PLDPC code *Hsr* with a 3/4 rate. The integer parts were transmitted in the relay channel while decimal parts were transmitted in the point-to-point channel (S-D link). The third strategy (UEP-2) utilizesd the image segmentation scheme and applied diverse rates (2/3, 3/4, 4/5, 5/6) of bilayer PLDPC codes for the decimal parts of DCT coefficients in four groups (classified by K-means clustering 40 images). The integer parts were encoded with a 2/3 rate bilayer PLDPC coded and were transmitted together with decimal parts in the half-duplex relay channel. The protograph base matrix *H*1/2 and the corresponding extended sub-protograph base matrices *H*2/3, *H*3/4, *H*4/5, and *H*5/6 were opitimized by protograph extrinsic infromation transfer (PEXIT) alogrithm [28] as

$$H\_{1/2} = \begin{pmatrix} 1 & 2 & 0 & 0 & 0 & 1 & 0 \\ 0 & 3 & 1 & 1 & 1 & 1 & 0 \\ 0 & 1 & 2 & 2 & 2 & 1 & 1 \\ 0 & 2 & 0 & 0 & 0 & 0 & 2 \end{pmatrix} \tag{18}$$

$$\begin{aligned} H\_{2/3} &= \left( H\_{1/2} \begin{vmatrix} 0 & 1 & 1 \\ 1 & 1 & 1 \\ 2 & 1 & 2 \\ 0 & 1 & 0 \end{vmatrix} \right) , H\_{3/4} = \left( H\_{2/3} \begin{vmatrix} 0 & 0 & 2 \\ 2 & 2 & 0 \\ 1 & 1 & 2 \\ 0 & 0 & 1 \\ 2 & 1 & 1 \\ 0 & 0 & 0 \end{vmatrix} \right) \\ H\_{4/5} &= \left( H\_{3/4} \begin{vmatrix} 0 & 1 & 1 \\ 1 & 2 & 2 \\ 2 & 1 & 1 \\ 1 & 0 & 0 \end{vmatrix} \right) \end{aligned} \tag{19}$$

where *H*2/3, *H*3/4, *H*4/5, and *H*5/6 were lifted 216, 144, 108, and 87 times to achieve the 1296 code length corresponding to bilayer-PLDPC full matrices *Hsr*,1, *Hsr*,2, *Hsr*,3, and *Hsr*,4 respectively. The end-to-end relay channel error can be presented as a function of the three SNRs (*SNRsd*, *SNRsr*, and *SNRrd*) of its constituent channels, represented by

$$SNR\_{SR} = SNR\_{SD} + a\_\prime \, SNR\_{RD} = SNR\_{SD} + b \tag{20}$$

where *a* and *b* are variable parameters [28].

**Table 2.** Simulation parameter setting.

Figure 8 shows the end-to-end performance comparison of different bilayer PLDPC code and the conventional AR3A code in half-duplex relay system. It is observed that the bilayer PLDPC codes had performance gains of 0.3 dB and 0.2 dB over the AR3A code at rates of 2/3 and 3/4, respectively.

**Figure 8.** The end-to-end performance comparison of bilayer-lengthened PLDPC code and AR3A code in in half-duplex relay system.

Figure 9 shows the performance of recovery image of the three strategies with *SNRSD* = 1.3, 1.9, 2.1 dB, *a* = 1.4, and *b* = 1.6. We can see that the recovery image qualities of the UEP-1 and UEP-2 strategies were significantly better than that of the EEP strategy under different SNRs. The UEP-1 and UEP-2 strategies achieved 19 dB and 31 dB peak signal-to-noise ratio (PSNR) gain over the EEP scheme for image 'Pepper' at *SNRSD* = 2.5 dB, respectively.

**Figure 9.** The comparison of recovery images in 3 strategies.

Figure 10 demonstrates the comparison of the PSNR of recovered images in four schemes under different SNRs. The AR3A code with a threshold at 3.1 dB was utilized for both integer and decimal parts of DCT coefficients in the EEP scheme. The UEP-0 scheme is the mainstream UEP method in joint source-channel coding system, which provides UEP for the high and low frequency of DCT coefficients [14]. The UEP-1 and UEP-2 schemes were designed in Sections 3.1 and 3.2, respectively. As can be seen in Figure 10, the 'Lena' image can be recovered at 3.1 dB and 3 dB by EEP and UEP-0 schemes, respectively. Compared to EEP and UEP-0 schemes, the UEP-1 scheme can achieve 0.3 dB and 0.2 dB gains, and the gains are higher in the low SNR region, reaching 0.8 dB and 0.6 dB, respectively. The UEP-2 scheme provides a delicate UEP strategy for decimal parts of DCT coefficients by image segmentation. As shown in Figure 10, UEP-2 had 0.8 dB and 0.7 dB gains in high SNR regions and 1.3 dB and 1.1 dB gains in the low SNR region, in contrast to the EEP and UEP-0 schemes, respectively.

**Figure 10.** The PSNR comparison of 'Lena's recovery image in 4 protection strategies.

Furthermore, Figure 11 shows the comparison of the feature similarity index measure (FSIM) between the recovery image and original image in three schemes under different SNRs. We can see the FSIM achieved 0.99 at 1.5 dB in the UEP-2 scheme, which is superior to those of UEP-1 and EEP of 1 dB and 1.3 dB, respectively. Moreover, it is interesting to note that the FSIM goes up to the top very quickly in the EEP scheme, compared to the proposed UEP schemes. This is due to that the decimal part of the DCT coefficients focuses on describing the details of the image, and this part of information can be recovered at high the SNR region in the proposed UEP schemes.

**Figure 11.** The FSIM comparison of 'Lena's recovery image in 3 protection strategies.

#### *4.2. Complexity Analysis*

The complexity of proposed joint source-channel coding frameworks is discussed in this section. As shown in Table 3, we tracked the usage of different modules in three strategies. In UEP-2, the module of reordering image sub-block is needed as compared to EEP and UEP-1. Since K-means clustering classifies the image sub-blocks into *p* groups, additional *p* times reordering operations are required. Moreover, both UEP-1 and UEP-2 strategies require the module to distinguish image source and additional *l* rounding operations and *2l* addition operations for telling the integer and decimal source apart, where *l* is the number of the transmitted DCT coefficients. Furthermore, we considered the complexity of channel decoding in the three strategies. As shown in Table 3, both UEP-1 and UEP-2 strategies required the relay decoding and the joint decoding modules at the destination.

**Table 3.** The usage of modules in three transmission strategies.

Morever, we show the convergence of the BP decodings by calculating the average number of decoding iterations, as given in Figure 12. It can be observed that UEP-1 had about two more iterations in comparison to EEP, even if extra decoders were added in the relay and the desitination. While UEP-2 had significantly higher iterations than EEP, the main reason is that the relay and the destination need to use more decoding resources to decode the encoding message of the decimal part.

**Figure 12.** The average number of decoding iterations comparison in three strategies.

#### **5. Discussion and Conclusions**

A novel joint source-channel coding scheme is introduced into the half-duplex relay system to design a UEP strategy for image transmission in this paper. According to the different levels of importance of image DCT coefficients and variance statistical characteristics of image sub-blocks, two kinds of image non-symmetric protection strategies were proposed and realized based on a family of bilayer-lengthened PLDPC codes. The first UEP scheme is designed for different parts of DCT coefficients with different transmission strategies. The second UEP scheme provides non-symmetric protection for image subblocks with different levels of importance that are segmented from the original image. The simulation results show that the proposed UEP schemes both have excellent performance compared to the conventional EEP and UEP scheme in the half-duplex relay systems. In the end, some prospects are put forward. Note that it is hard to achieve the optimal image segmentation technique for UEP strategy. More excellent UEP strategy needs to be studied, such as the joint design of the image feature extraction technique [35–38] and channel coding technique. It is expected that the unequal error protection for the integers and decimals can be applied to various occasions, in addition to image transmission, when applying source-channel coding methods. Additionally, note that the optimization design for source structures and the bilayer PLDPC codes in UEP strategy deserves our further study.

**Author Contributions:** Conceptualization, T.G. and M.X.; methodology, T.G.; software, T.G.; validation, M.X., P.C. and D.G.; formal analysis, D.G.; investigation, T.G.; resources, M.X.; data curation, T.G.; writing—original draft preparation, T.G.; writing—review and editing, T.G. and P.C.; visualization, D.G. and P.C.; supervision, M.X.; project administration, M.X.; funding acquisition, M.X. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was supported the by Natural Science Foundation of Fujian Province, China under Grant no 2018J01569.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

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**4. Path forward**

Nowadays integration is moving away from unit operations and focuses on phenomena; like reaction, heat and mass transfer that occur within a single piece of equipment. Future systematic techniques for process integration will not only explore for integration between units but also integration within units.

Process sites produce useful products in one or more process units and use a centralized utility system to satisfy the heat and power demands of the process

units. Improvements in process technology, heat recovery philosophy and enhanced throughput are a number of the various reasons why the process changes must be implemented in an exceedingly site. Because of the interactions that exist between the various subsystems (e.g. processes, heat exchanger networks and utility systems), a change in one has a knock-on effect on the other subsystems. Many of the concepts and methods developed within the past for grassroots design, operational management, retrofit and debottlenecking scenarios, have focused on utility systems and process units independently. A clear strategy and systematic approach therefore must be developed to integrate all processes and utility systems and determine the synergies among them. Developing an efficient design of energy systems (utility system) requires an honest understanding of every subsystem in compass different processes. An effective design method is one that integrates the various subsystems within the site and captures the advantages instituted on interactions between them. Another element which needs attention is that the energy available finally after all integration i.e. energy which could not be employed in the present form and will be utilized through energy recovery technologies to the form energy which is required within the site. Physical insights and graphical methods of research is accustomed to study these interactions between the various parameters within the site and estimate the impact of process changes on site targets. However, as they do not consider the prevailing constraints within the site, they are less rigorous compared to mathematical programming techniques.

The approach (**Figure 7**) are going to be very effective in achieving energy efficient facility design because it will unify all processes, utilities, heat recovery and waste energy utilization to come up with targets and lay the inspiration to capture direct/indirect/hybrid integration among the plants. The resultant designs are going to be optimized for the full facility as even the plot plan is going to be optimized from direct and indirect integration perspective. Moreover, the retrofit-ability aspects of the design are going to be also covered within the approach, the resultant design will not only energy efficient today but easily modified as per trade-off to stay energy

#### **Figure 7.**

*Approach to facility design via integrated process-recovery-utility systems.*

### *Sustainable Energy Efficient Industrial Facility Design DOI: http://dx.doi.org/10.5772/intechopen.108829*

efficient throughout its life cycle. Because it is extension to the Pinch approach it has all its benefits and further improvement by unifying all facility design, low-grade energy recovery and utility synthesis. It's very difficult to magically establish such a global solution to figure from scratch. First, there should be the fundamental ingredients in situ, namely the desire of site-wide plants to participate and second proper tools and insights to conduct the analysis. These basic ingredients can then be enhanced and improved upon, with correct support structure in situ. The key to developing a successful sustainable energy efficient design is to determine the best integration among different plants and its utility system. Specifically, it's the material and energy flows relationship among the various plants which allow establishing optimal linkage to method a fruitful inter-dynamic structure. The other element is that it also looks to the application of energy technologies to the facility which starts with the quantification of the available waste energy that will not be utilized for integration during its life-time.

The method should be consisting of the holistic approach for total site targeting supported on the pinch technology accompanied by mathematical programming techniques, which is that the most generally used, where it allows waste heat from processes to be used as a source of heat in other processes. The waste heat sources are converted to steam, and then passed to processes that are in an exceedingly heat deficit condition via steam system infrastructure. To spot the external heating and cooling requirements of a group of individual plants from the central utility system, the temperature/enthalpy data from individual plants are first required to be extracted from the plant after the thermal integration of its hot streams to be cooled and cold streams to be heated using individual plant' grand composite curve. These grand composite curves define each plant' thermal heat deficiency and thermal heat surplus after intra-plant heat integration.  Such two curves are superimposed on one graph with the present and/or suggested steam generation levels and steam supplying levels to search out the minimum total site external energy utilities requirement and naturally best indirect inter-plants thermal integration, using the site steam system. During this method, intra-integration is completed first, which implies only waste heat of one plant is shared with other plants' members (which is not proactive form of cooperation). In this method the direct integration among adjacent plants, even using steam as a buffer, is not systematically addressed, where plant A, for example, with a surplus heat shall generate steam from its hot streams after its integration with its cold streams and send it first to the central utility and then the central utility sends it back to plant B leading to energy quality degradation and potential for mismatch between supply and demand. In this method, the mismatch within the number of steam levels required by the site users' generation and utilization leads to energy loss with very high possibility [12, 13].

The worldwide commercial software for transitioning industrial complexes to integrated-processes-utility-energy recovery facility does not exist and even the software for planning synthesis/design of the new ones for energy efficiency optimization do not seems to be much. The current state-of-art methods focus only on indirect integration using steam, after all for obvious reasons.

In brief, a mathematical programming formulation-based software is solved successively to enumerate all possible combinations of solutions ranked from best objective function value to least for every "user-selection" type of plants' integration

#### **Figure 8.**

*Future methodology to achieve energy efficient facility design.*

(membership in an alliance to avoid wasting energy) to spot the plants for inter-plants integration and also the ones for intra-only integration together with waste energy utilization technologies as shown in **Figure 8**. This may give an energy efficient design for a given economic trade-off and also has capability to optimize facility plot-plan for better integration opportunities but nevertheless it must be developed to be capable of life-time retrofit-ability. This needs solutions to be generated for all future economic trade-off supported on capital and energy costs forecasts, these solutions shall be compiled together to urge a design which can be modified from initial to final design with none hindrance. Provisions shall be provided for all the longer-term future modifications within the current design to form it a "Sustainable Energy Efficient Facility Design". The end result of the analysis is going to be highly integrated design as shown in **Figure 9** which is retrofit-able throughout its lifecycle and incorporated waste energy utilization technologies.